Mover & Shaker Interview with SAP Fioneer, Future Digital Awards Platinum Winner for Banking-as-a-Service Innovation

Juniper Research interviewed Anna Koritz, Global Head of Transaction Banking at SAP Fioneer, in September 2025.

Anna Koritz has extensive experience in Transaction Banking from EY Management Consulting, from NatWest where she was a Managing Director in Global Transaction Services and from Capita where she led significant operational payments and treasury teams and also delivered large Customer Experience solutions to prominent Financial Services clients.

Why is core banking transformation still such a strategic priority?

Because it’s the foundation of everything a bank does – regulatory reporting, risk management, and product innovation all rely on the core. With rising compliance costs and margin pressures, banks cannot afford to run on legacy systems anymore.

What should a good core banking solution deliver today?

Flexibility, scalability, and real-time processing. But also, compliance-by-design, because regulatory change is constant. And ecosystem readiness—banks need to plug into fintechs, corporates, and embedded finance models seamlessly. At SAP Fioneer, we combine deep banking expertise with modular architecture to deliver exactly that.

What makes SAP Fioneer’s approach different?

We are built for banking. Our platform is powered by S/4HANA’s technology, which provides real-time data processing and faster access to data – thanks to HANA’s in-memory database. We also offer a full suite of finance solutions. By also offering a full suite of banking and finance solutions, we provide a holistic platform that enables clients to deliver truly personalized experiences—like our behavioural banking engine —and embrace AI with a high degree of confidence.

Cloud is often seen as the end goal. What’s your view?

Cloud is indeed the destination for many financial institutions—and we fully support that. Our platform is cloud-agnostic, meaning it can be deployed on any cloud environment a bank prefers. However, we also believe in meeting banks where they are. If a bank wants to stay on-premises for part of its journey or even permanently for certain functions, we support that, too. It’s about finding the right approach that aligns with a bank’s unique strategy, risk appetite, and regulatory environment.

How do you see regulation shaping core banking transformation?

Compliance is a key driver—whether it is PSD2, ISO 20022, or data residency laws. Fioneer Core Banking system make compliance easier, cheaper, and faster. Instead of compliance being a cost burden, it becomes an enabler of trust and differentiation.

What are the biggest technical challenges banks face?

The biggest hurdles are often legacy integration, data migration, and ensuring continuity during transition. Banks have deeply embedded legacy systems that must be carefully integrated or replaced without disrupting daily operations. Moving vast amounts of historical data accurately and securely is another immense undertaking. The good news is that these are solvable, and we are doing this everyday, with the right modular architecture, with our expertise, meticulous planning, and a strategic approach like progressive transformation, parallel runs etc.

And culturally—what holds banks back?

More than technology, it is mindset. Transformation is often seen as disruptive, risky, or too expensive. But transformation doesn’t have to be disruptive. The key is to build confidence, align teams around a shared vision, and demonstrate that change can be an incremental, controlled process that delivers quick wins.

Where’s a good place to start the transformation journey?

We advise starting with high impact, non-mission-critical functions that can deliver immediately, with tangible value. Think about areas like product engines, digital onboarding, or internal service platforms. Modernizing these functions can reduce manual effort, improve efficiency, and demonstrate the value of the new technology without risking the core, mission-critical flows. These quick wins can build momentum and stakeholder buy-in for the larger transformation.

What’s your advice to banks who are hesitant?

Start small but start now. The longer the delay, the more complex and costly transformation becomes. The key is choosing the right partner and approach—one that balances short-term wins with long-term strategy. Transformation is not just achievable; it is essential to remain competitive.

Final thought—Is it worth the effort?

Absolutely. We have seen it firsthand. With the approach we discussed, our customers have achieved faster innovation, reduced cost-to-serve, improved resilience, and have found new revenue opportunities. Transformation is not about replacing technology for its own sake—it is about enabling your business and your customers to thrive in the next decade.

The post Juniper Research interview SAP Fioneer about the future of core banking appeared first on SAP Fioneer.

Outdated payment systems are draining bank resources and failing to meet modern customer demands. While millions are spent annually just to keep legacy infrastructure compliant, these systems still fall short of delivering the speed, transparency and agility today’s customers expect.  

AI is changing that. It’s transforming how banks operate, from dynamic routing and payments reconciliation to liquidity forecasting and fraud detection. With adoption growing at over 30% per year, banks are already seeing tangible benefits from AI like faster settlements and more scalable operations. 

More importantly, AI is helping shift payments from a cost center to a strategic function – one that delivers faster, more transparent experiences for customers and deeper value for the business. 

This article takes a closer look at how AI is reshaping the payments industry and what banks need to do to keep up. 

What is the cost of relying on outdated payment systems? 

Banking’s relationship with payments is changing fast. Customers now expect to send and receive money instantly. Businesses want smoother operations and better liquidity. But many banks are still trying to deliver 21st-century experiences with infrastructure that was built decades ago.  

The cost of this legacy burden is clear: banks are still investing a significant amount of money into keeping systems compliant with initiatives like SEPA, which requires standards such as ISO 20022. More than half of the average IT budget in payments is spent simply on staying operational rather than driving innovation. 

SEPA shows just how high the costs can climb. The total spend on this transition reached £10.2bn, with two-thirds of that tied directly to ISO 20022 XML. It’s a considerable cost for banks, but one they had little choice but to pay — compliance is essential not only to satisfy regulators but also to remain competitive and relevant in the market.  

Hype or help? The truth about AI in payments 

AI is no longer just a buzzword in banking. It’s actively improving core processes like routing, reconciliation, liquidity forecasting, and fraud detection. Banks are actively building AI into the foundation of their operations, not just using it as an add-on.

Historically, the term AI has been used loosely in the financial sector (mainly in payments) without clearly defined or proven use cases. But this is changing due to ongoing industry challenges, new innovations and evolving customer expectations.

Despite years of digital transformation talk, friction remains a persistent problem in payments. Transactions are often slower and more manual than expected, with many systems still relying on fixed routing rules, clunky file formats and batch-based processing. The complexity increases significantly with cross-border payments. Multiple intermediaries, time zones, checks make today’s payment systems feel anything but modern. Worse yet, it ties up capital. According to Oliver Wyman and J.P. Morgan, more than $120 billion per year is spent on cross-border transaction costs, with additional hidden costs from trapped liquidity in the correspondent banking system. This is money that could be working but remains idle due to outdated processes.

The shift towards intelligent payment systems

Some banks are changing how payments move through their systems entirely by using third-party payment platforms. Instead of using fixed routes, AI models dynamically adjust routing based on fees risk exposure, and network performance. In tests and early rollouts, it’s already cutting processing costs by 10-15%. More importantly, it’s offering agility that banks didn’t have before.

Then there’s reconciliation. Matching payments to invoices has long been a pain point in corporate payments. AI now handles this in seconds using machine learning and natural language processing (NLP) techniques. In a recent conversation, one corporate banking team shared with me that they’ve reduced their reconciliation windows from two days to near real-time matching with accuracy over 98%.

That’s not just about efficiency; it frees up working capital and improves the customer experience.

Liquidity forecasting is also moving out of the spreadsheet era. Capital costs are rising, and balance sheet pressure is increasing. As a result, treasury teams are starting to rely on AI models. These models can predict payment volumes with surprising accuracy—up to 85% in some cases. That enables more precise liquidity buffers and reduces excess reserves.

Fraud detection is another area where AI is finally outperforming old systems. Rules-based tools can’t keep up with new fraud patterns, resulting in too many false positives. AI can spot subtle anomalies across millions of transactions and adjust as patterns shift. This results in fewer false alerts, stronger fraud detection, and a smoother customer experience. Still, human oversight remains essential, and no compliance team should assume the machine always gets it right. Third-party payment and core banking applications are now adding their own fraud detection tools. These tools are part of end-to-end solutions designed to further safeguard each payment.

Customer interactions are shifting too. People are already comfortable talking to their bank through a chatbot. That’s not new. What’s changing is that AI is getting better at proactively helping customers. It can nudge them when they’re heading toward an overdraft, suggest better ways to structure payments, or even flag irregular subscription charges. These are small moments, but they build trust. What matters most is giving users control and being transparent about how technology makes decisions. Customer and business experiences have become top priorities in recent years and AI is one aspect helping banks meet rising customer expectations.

Why 30% growth in AI payments signals 3 big wins for banks

Banks are beginning to see real returns from investing in AI. The AI-in-payments market is expected to hit $340 billion by 2028, with a growth rate upwards of 30%. And this isn’t just hype. Banks that have prioritized AI aren’t just seeing cost savings. They’re also achieving:

1. Faster settlements
2. Better data quality
3. More scalable operations

But these leading banks are not just treating AI like a plug-and-play feature. They’re treating it as a long-term infrastructure shift. In some cases, they are working closely with third party payment application providers to embed AI into their core systems.

How to accelerate AI adoption in payments

For AI in payments to reach its full potential, banks need to get three key things right:

1. Data: You can’t run powerful models on unreliable inputs. Clean, structured, accessible data is the foundation. More banks are realizing this, but it’s still a work in progress.
2. Integration: Most core banking systems were built long before real-time APIs or event-driven architecture. Connecting them to modern services takes effort. Middleware can help, but it needs real investment and strong governance to avoid turning into a patchwork.
3. Culture: Technology alone doesn’t guarantee success. If the teams using it don’t trust or understand it, adoption will be slow—or won’t happen at all. Success depends on breaking down silos and building a culture where business, tech and compliance work together on data-drive decision-making.

AI in payments is no longer theoretical

We’re past the point of theory. AI is already shaping how banks move money, manage risk, and serve customers. Payments used to be a cost center. Now they’re becoming a strategic differentiator. And with as much as 80% of digital payments expected to involve AI by the end of 2025, the question isn’t whether to act, it’s how quickly you can. Finding the right reliable payments partner—one that enables easy integration and a seamless go-live—is now a top priority for banks.

Discover the future of payments. Request a demo today.

Many banks still run their payments infrastructure on outdated, disconnected systems—expensive to maintain, slow to scale, and difficult to adapt. In a world of accelerating change, banks need modern technology that is resilient, high-performing, and ready to support complex, real-time demands without disruption.​

SAP Fioneer’s Payment Central helps banks move faster, scale smarter and deliver better payments experiences.

See it in action: https://www.sapfioneer.com/request-a-demo/

The post How AI is redefining payment efficiency in banking appeared first on SAP Fioneer.

As insurers more focus on embedded insurance, real-time servicing and ecosystem integration, PAS is evolving from a system of records into a foundation for innovation.

Investment trends support this shift. Global insurance technology spending (which often includes updating PAS) is expected to reach $230 billion in 2025. The majority of this financing is for IT services and software as insurers modernize core systems, enhance digital experiences and launch more personalized products.

Meeting today’s demands requires more than migrating to the cloud or adding features. A modern PAS must be configurable, scalable, interoperable and built to adapt — serving as both operational backbone and strategic enabler.

What sets modern PAS platforms apart isn’t just the technology, but how effectively they solve real business challenges. This article explores those challenges and the capabilities insurers need to move forward with speed, control and confidence.

How a modern PAS enables competitive advantages

Supporting digital basics, such as online quotes or paperless policy management, is no longer enough to stand out in a competitive environment. The real differentiator is how quickly insurers can adapt to changing trends and customer expectations.

Meeting that bar requires more than incremental upgrades. It calls for a policy administration system that aligns closely with business priorities and equips insurers to move with speed and flexibility.

1. Increased speed to market with no-/low-code tools

Delivering new products fast and adjusting to pricing shifts requires more flexibility than most legacy systems allow.

Traditional legacy and homegrown systems often require weeks of IT work for product launches or even minor updates (e.g., adjusting pricing). Modern platforms shift that power to business teams by offering low or no-code tools. Teams can independently configure rules, pricing, processes, transactions and documents, cutting lead times and removing technical bottlenecks.

The result? Faster launches, shorter feedback loops and the ability to respond to shifting demands rapidly.

2. Improved efficiency through automation and integration

Manual processes, disconnected data and batch-based updates make it harder to scale operations or maintain accuracy.

For example, many policy workflows, such as endorsements, still rely on manual tasks like retyping data, checking documentation and triggering multiple downstream updates. This slows turnaround times, increases error risk and limits scalability.

A modern PAS integrates policy, customer and behavioral data into a single, consistent data model for consumption. This foundation supports predictive analytics and faster decision-making, which reduces the number of manual tasks, minimizes errors and increases efficiency.

While batch processing creates delays in customer service and data updates, open APIs enable instant responses to changes, such as claims activity or customer data updates. This allows for real-time pricing and policy adjustments and automated service updates without manual intervention, improving operational efficiency and customer experience.

3. Reduced infrastructure costs and IT overhead with SaaS

Insurers are increasingly looking to reduce infrastructure overhead and shift IT resources away from maintenance towards innovation.

Cloud-optimized deployment provides an elastic infrastructure that supports faster implementation of system updates and new capabilities, while lowering total cost of ownership. Moving away from capex-heavy, on-premises systems frees IT teams to focus less on maintenance and more on innovation.

For example, SAP Fioneer’s Cloud for Insurance delivers a modern policy administration system as a SaaS offering, backed by services that support deployment, integration and day-to-day operations. This model helps insurers scale efficiently, stay current with minimal internal IT effort and reduce infrastructure costs.

While the benefits are clear, it’s important to acknowledge that cloud migration comes with complexity — from data transfer and legacy integration to organizational change. A successful transition depends on a clear migration strategy and experienced partners to manage risk and ensure smooth execution.

4. Better ecosystem participation through open and interoperable architecture

As distribution shifts beyond owned channels, insurers must support embedded products, partner pricing and digital integrations, without compromising compliance or core stability.

A future-ready PAS supports this, while remaining compliant across multiple jurisdictions and regulatory environments.

Open APIs connect products, partners and platforms across functional domains like underwriting, claims and embedded distribution. To keep the policy administration system at the center of this complex web, modern integration models and open APIs are not just beneficial. They’re essential.

While a PAS doesn’t deliver the omnichannel experience directly, it enables it behind the scenes. Through APIs and white-labeled insurance products and services, platforms like SAP Fioneer’s allow insurers to connect front-end tools, such as portals, mobile apps, or partner channels, to a single source of policy truth. This reduces duplication, ensures data consistency and supports smooth experiences across all touchpoints.

In a fast-moving, highly regulated market, insurers also need to adjust quickly to regional compliance requirements and partner-specific rules. Modern PAS platforms allow business users to update processes, transactions, rules and documentation without relying on developers—keeping embedded offerings compliant and adaptable at scale.

5. More customer-centric responsiveness with configurable workflows and embedded insights

Customers expect consistent, responsive service at every interaction or touch point, which legacy systems aren’t equipped to deliver.

State of the art PAS platforms embed analytics directly in workflows, giving underwriters, agents and product teams real-time visibility into product performance, quote-to-bind conversion and policy profitability. Instead of relying on delayed reports, teams can act immediately on timely, relevant insights.

6. A system that enables future readiness

Whether operating in a single market or across multiple regions and product lines, insurers need core systems that won’t limit future growth.

Traditional business models are currently shifting to embedded insurance and usage-based ones (e.g., dynamic pricing based on use). That’s why insurers benefit from a PAS that can scale across product lines, regions and channels if and when their business requires it.

Even those starting with a narrow focus gain from having a platform that won’t limit future growth or require rework as needs evolve.

SAP Fioneer is built for that breadth with a unified platform used across property and casualty (P&C), health and life insurances in markets as diverse as South Korea, the Netherlands and India.

Unlike monolithic legacy systems, today’s PAS platforms also support transformation through independently deployable modules. This allows insurers to adopt new capabilities, such as digital claims or new product lines, without replacing or rebuilding the entire system at once.

SAP Fioneer’s architecture supports this phased approach, enabling full components to be introduced or updated without disrupting core operations. As noted in Celent’s 2025 assessment, this “allows for independent updates and enhancements, ensuring the system remains current and adaptable to changing business needs.”

A new PAS must be able to adapt easily, whether it’s to changing regulations, third-party integrations, or entirely new business models. Open frameworks, scalable infrastructure and configurable rules ensure the platform can grow with the business without system overhauls.

Strategic PAS is the infrastructure for digital growth

Once seen as an operational necessity, policy administration systems are now becoming strategic enablers of speed, flexibility and innovation.

In a landscape defined by embedded insurance, ecosystem distribution and rising customer expectations, speed and scalability are no longer optional—they’re strategic differentiators. A PAS must provide the foundation to deliver both, without tradeoffs.

And for insurers ready to lead, the future starts at the core.

The post What sets modern policy administration systems apart  appeared first on SAP Fioneer.

Modernizing with greater clarity and control begins by focusing on business value, modular design, and long-term adaptability. That means understanding where hidden costs creep in, asking the right questions beyond the Request for Proposal (RFP), and choosing solutions that reduce risk without slowing down innovation.

For many insurers, the real challenge isn’t whether to transform. It’s about doing so in a way that drives more tangible and relevant outcomes while keeping the business running.

Is the organization truly ready to modernize?

One of the biggest risks in modernization isn’t choosing the wrong technology or implementation approach. It’s moving forward before an organization is truly ready.

Many insurers overcommit too early. They invest in new platforms while underestimating the complexity of changing the way people work, think, and collaborate. Managing any resistance to change is vital to achieving organizational buy-in and facilitating a smooth transition to adopting new processes and technologies.

That’s why technical readiness is only part of the picture. Cultural and operational readiness matter just as much.

One of the clearest signs that an organization is ready is a willingness to adopt proven solutions instead of insisting on a fully custom-built system – consume rather than define and build This means moving away from trying to design and control every process in-house, and instead trusting established platforms, pre-configured processes, and agile delivery models.

The value of having a modernization readiness checklist

Before committing to any modernization program, insurers should ask the following questions:

• Is data integrity in place?
  • Poor-quality data can introduce serious risks, from migrating inconsistent information or incomplete records into a new system to inaccurate decision-making. Cleansing, enriching and validating data before migration is essential.
• Are the right internal capabilities available?
  • Readiness requires more than IT expertise. Business analysts, change leaders and cross-functional teams are needed not only to bridge technology with day-to-day operations, but they must also have the time and availability to commit to the modernization effort.
• Can the business absorb operational change?
  • Frontline teams need sufficient time, support and training to adopt new tools and workflows. Phased adoption strategies can help minimize disruption while increasing success rates.
• Is there committed executive sponsorship that can lead organizational change?
  • Effective leadership goes beyond budget approvals to actively champion change. Insurers do this with clear communication of strategic goals and visible, hands-on involvement to motivate, foster engagement and adapatability and achieve buy-in. This includes continuously monitoring progress, gathering employee feedback and addressing obstacles to smooth adoption.

Modernization delivers value only if the entire organization — people, processes and leadership — is ready to work in a new way.

Uncovering the hidden costs of insurance modernization

Even if an organization appears ready to modernize, many insurers fail to account for the full cost of doing it well.

The consequences of underestimating modernization challenges aren’t just budget overruns. They’re solutions that are difficult to scale, expensive to maintain, and fragile in real-world conditions.

Here are four of the most overlooked costs that, if detected early, can reduce risk, improve planning, and ensure a smoother path to long-term value:

1. Integrating with given systems can be more complex than expected

Integration with given systems can derail modernization if not planned for. Connecting new tools to existing core systems, homegrown tools, or point solutions may reveal hidden incompatibilities. These integrations can consume far more time and budget than expected.

Addressing these risks early through architectural planning, API-first design – overcoming point-to-point integration, phased approach and modular rollouts help prevent delays and ensures smoother modernization.

2. New systems need to be able to support evolving compliance needs

Legacy platforms often fall short on auditability, data transparency, and reporting capabilities required to meet today’s regulatory and business demands. But modernization isn’t automatically a fix. Without flexible architecture, even new systems may struggle to keep up with evolving regulations, especially across diverse jurisdictions.

3. Poor scoping leads to increased technical debt

Modernization projects that are rushed, under-scoped, or poorly aligned with business priorities often create new technical debt instead of resolving the old. This risk is especially high in “Big Bang” transformations when delivery timelines, organizational readiness, or stakeholder alignment are unclear.

Whether rolling out in phases or all at once, success depends on clear prioritization, defined ownership, and the ability to adapt as conditions evolve. Without that, systems become over-engineered, under-used, or outdated by the time they go live.

4. Disconnected strategy weakens even good technology

Even the best technology will fail if stakeholders don’t know how to operate it. A lack of clarity around ownership, workflows, or success metrics can erode value quickly.

What makes a modernization strategy successful and scalable?

Modernization in core insurance systems is a high-stakes, high-impact transformation. With large budgets, long timelines, and business-critical systems on the table, it’s closer to open-heart surgery than surface-level change.

The major challenge is modernizing core systems that power underwriting, claims, policy admin, and customer experience without risking operational downtime or customer disruption.

Unlike tech peers in other sectors, insurance leaders operate in a high-compliance, low-margin-of-error environment where mistakes could be expensive and highly visible. They must weigh innovation choices not only against strict regulatory demands and the need for operational continuity, but also against competing strategic goals. Should they focus on delivering the best product, the most efficient operations, or the most personalized customer experience?

Successful modernization strategies balance these pressures rather than chasing just one at the expense of others by:

1. Driving measurable business impact

To be effective, every modernization effort must be anchored in a specific, cross-functional outcome—whether that’s reducing product launch times, cutting maintenance costs, or improving customer retention. That means aligning IT investment with priorities from strategic business KPIs and objectives.

For example, replacing hard-coded product configurations with a flexible product engine enables faster launches across different lines of business.

2. Being technically feasible within the existing ecosystem

Digital transformation efforts often fail because they underestimate how tightly existing systems are intertwined. Scalable strategies account for the current architecture and build toward a future-ready one by using modular platforms, API-first solutions, and cloud services that can evolve alongside your business.

Instead of replacing core systems, a more effective approach is to layer in a cloud-first policy administration system that integrates with legacy billing or claims systems, avoiding a full replacement from day one.

3. Preparing the organization for change now and in the future

Insurance tech leaders must modernize amid ongoing operations, regulatory reporting and the departure of institutional knowledge as long-serving experts retire. But successful modernization must also position the organization to thrive in the years ahead.

That means making systems intuitive for new talent, reducing reliance on bespoke knowledge and creating an environment where future employees can build, adapt and innovate.

One way to reduce risk is to start with a single line of business or customer segment. This allows teams to gradually adopt new ways of working while reducing their reliance on aging systems that are hard to maintain.

How to choose the right path to modernization

The risks that come with modernization — rising costs, rigid systems and misaligned strategies — often stem from poor prioritization. Instead of trying to fix everything at once, successful insurance tech leaders categorize their systems and initiatives to focus their efforts where they deliver most value.

1. Use a framework to prioritize modular and phased modernization

The framework below helps categorize modernization initiatives based on their relative effort and impact. Effort refers to the complexity and time required to deploy a solution; not how technically difficult it is to build. Quick wins typically affect isolated systems or workflows, while foundational investments involve core platforms and cross-functional change.

A framework also reflects how modular transformation can scale, whether insurers start with a targeted quick win or plan a core system upgrade over time.

By mapping each initiative to its impact and effort, insurers can focus on what delivers value fastest and avoids unnecessary complexity.

For example, an insurer might begin by automating document handling for claims—a lower-effort, high-impact quick win. With early success and team buy-in, they could then move on to a phased rollout of a new claims management system, starting with a single line of business to minimize disruption.

2. Start where the business feels the pain

Instead of starting where the tech is oldest, successful insurers start where the business feels pressure. That might be high maintenance costs, slow product launches, compliance risk or low efficiency in processing.

Internal KPIs like time to market, operational cost, or customer satisfaction guide where to begin.

Imagine an insurer struggling with rising costs and slow processing times in its claims department. Despite having older systems in other areas, the business impact of claims delays (e.g., customer complaints, manual workloads and reputational risk) was more urgent. By targeting claims first for modernization, the company automated routine tasks, improved turnaround times and freed up staff for higher-value activities.

3. Use agile delivery to accelerate learning

Even with a clear roadmap, modernization rarely goes exactly as planned. Agile delivery methods reduce risk by breaking initiatives into smaller, testable increments that can be brought to production. This enables teams to gather feedback early, adjust based on results and build confidence before scaling further.

This approach aligns with how SAP Fioneer supports modernization, enabling insurers to start with one line of business or a certain capability, deliver value quickly and expand based on proven outcomes rather than assumptions.

For example, one of our insurance clients launched a new core insurance system — from quote to claims — for a select group of property and casualty (P&C) products in just a few months. By starting with a defined scope and iterating based on user feedback, they validated their modernization strategy early and used it as a blueprint for broader transformation.

4. Reassess each initiative continuously

Priorities may shift as adoption grows, business scales and markets change. An adaptive approach allows insurers to double down where results improve, pivot when friction emerges and pause if business value stalls.

Consider a scenario where a new underwriting system is rolled out in one market with strong adoption. When expanded to another region, however, the team encounters unexpected integration challenges due to different regulatory workflows. Rather than pushing forward, the rollout is paused, adjustments are made to address local needs and the program resumes with better alignment—avoiding wasted effort and improving long-term success.

What to consider when picking a technical solution

After identifying the right areas for modernization, the next challenge is choosing the right technical solution. Leading insurers look beyond product demonstrations to assess how effectively they support their strategic, operational and technical goals.

Four key assessment criteria are:

1. Modularity and scalability

Modernization isn’t a one-time project. Platforms need to support phased rollouts, which allow insurers to upgrade individual capabilities or lines of business without disruption. Flexible, cloud-first architecture makes this possible, enabling teams to evolve at their own pace.

2. Ecosystem integration

The ability to connect with legacy systems, external data sources and partner ecosystems is critical, especially in an embedded insurance context. An API-first, event-driven design helps ensure smoother integration across the insurance value chain.

3. Insurance-specific breadth and depth

Generic platforms often fall short in areas like localization, regulatory compliance and product complexity. Industry-specific solutions that come pre-configured with insurance content can reduce time to value, support compliance out of the box and adapt more easily to regional requirements.

4. Long-term efficiency

Licensing is only one part of the equation. Long-term value depends on maintenance effort, implementation complexity, training needs and adaptability. Platforms that reduce reliance on custom code and support ongoing automation can lower operational costs and minimize lock-in risks.

Together, these four capabilities help insurers avoid the hidden traps of overspend, complexity and rigidity while laying the foundations for modernization.

Smart modernization involves strategy, cost clarity and the right technical partner

Modernizing core insurance systems is no longer optional — but how insurers approach that transformation will define whether it becomes a long-term asset or a costly misstep.

This guide has shown that smarter modernization isn’t about bold bets or wholesale system replacements. It’s about ensuring organizational readiness, aligning transformation with business priorities, uncovering hidden costs early and choosing solutions that support agility, scalability and continuity.

Insurers that succeed take a phased, modular approach and start with urgent pain points. They don’t aim for perfection on day one. They prioritize outcomes, empower cross-functional teams and invest in platforms built to evolve.

Ultimately, smarter modernization delivers more than new systems: it enables faster innovation, better customer experiences and a foundation insurers can build on for years to come.

SAP Fioneer supports this journey through Cloud for Insurance, an end-to-end platform that enables faster product launches, lowers implementation risk, ensures compliance and supports continuous evolution across the enterprise.

The post A guide to making smarter modernization for insurers  appeared first on SAP Fioneer.

In the race to modernize, insurers are confronting a hard truth: improving and upgrading technology isn’t a one-time event — it’s an ongoing business function.

For decades, insurers treated modernization only as technological improvements to be completed every 10 to 15 years. Today, real-time customer demands, digital-first competitors and embedded ecosystems require insurers to rethink how they keep technology up to date.

That shift must start with architecture. Insurers need systems that enable rapid product launches, fast testing cycles and swift responsiveness to regulatory changes or customer feedback. But legacy infrastructure often holds them back. According to Deloitte’s Insurance Outlook 2024, outdated technology remains one of the biggest barriers to speed, innovation and improved customer experience.

To modernize in a way that lasts, insurers need flexible architectures for seamless integration, disciplined execution to deliver at speed and organizational agility to respond to change at scale.

Why modernization programs falter

To make modernization a continuous capability, insurers need to understand why so many transformation programs fall short.

Inflexible foundations

At the heart is rigid core architecture. Without fully re-architecting existing systems, insurers face constant bottlenecks — especially when launching new products or enabling digital partnerships.

That’s why basic system changes often drag on for weeks, stalling innovation and eroding insurers’ agility. For example, a usage-based pricing initiative in auto insurance may be delayed because adjusting pricing logic requires a full-system reconfiguration, something their current architecture simply can’t support without extensive development and testing.

Insurance transformation programs often fail to deliver continuous modernization for several key reasons:

Teams underestimate the cost of technical debt

Many insurance core systems are tailor-made, based on outdated business models. They are difficult to adapt and update due to point-to-point integrations, outdated custom codes and poorly documented data relationships.

Aged systems are also largely dependent on quickly shrinking talent pools. The IT staff who built them are retiring, creating knowledge gaps that newly graduated experts can’t bridge since they specialize in modern solutions and techniques, not homegrown and outdated ones.

These highly customized systems are not easy to maintain or update without creating additional costs. Without a full view of this technical debt, modernization efforts risk spiraling over budget or collapsing under scope.

Fragmented data environments make it harder to adapt and move quickly

Homegrown systems often also create fragmented, outdated data environments that slow insurers down. Many organizations still rely on separate policy administration systems for each line of business, making it difficult to consolidate data or gain a unified view of customers (360° view). Real-time insights are often unavailable because changes require batch processing or manual updates.

This lack of transparency makes it harder to respond quickly to market changes or meet new regulatory demands and customer requirements. Without centralized, real-time access to data, insurers face operational delays, compliance risk and poor decision-making.

The opportunity cost of disruption often outweighs the perceived benefit

Modernizing without fully understanding how deeply legacy infrastructure is anchored in core systems can cause major service disruptions. Even small mistakes can introduce significant risks for policy and claims management, at the heart of an insurer’s operations.

Tight regulatory obligations and customer trust demand uninterrupted service even during transformation. That requires running parallel systems, layering new capabilities over old and maintaining security and compliance at every step.

What are the people-related blockers?

Even the most advanced architecture will fail without the organizational readiness to adopt it.

As a business transformation, the involvement of full-time staff is key to ensuring success. Yet many insurers see insurance modernization as a part-time project internal experts can manage in parallel to their main duties.

This can lead to obstacles, such as employee resistance. Staff may hesitate to adapt to new tools and processes and is often skeptical about the benefits of the changes. Morale and productivity decline while larger scale implementation is delayed. Product teams may also lack the skills to fully use new platforms, leading to low adoption or heavy IT reliance.

Weak executive sponsorship is another blocker that can undermine modernization attempts. For example, a multi-national organization may struggle to agree on a single IT layer that all local teams can use unless there’s agreement on shared standards. Regional units could end up duplicating systems, processes and data structures.

Without ongoing, cross-functional leadership commitment, reinforcement and governance, initiatives lose momentum. This can delay cultural change, stalling the formation of agile, cross-functional teams made up of business, IT, risk and compliance.

Without a shared roadmap, modernization efforts become uncoordinated, leading to siloed initiatives, mismatched priorities and missed opportunities.

How leaders succeed: building modernization into everyday operations 

As covered earlier, making modernization a continuous capability starts with rethinking the underlying architecture. Without a foundation that supports speed, flexibility and integration, even the best transformation efforts will struggle to scale. There are two key ways insurers can design architecture to enable this:

1. Build a platform foundation that supports ongoing modernization

In Adacta’s 2025 survey of European insurers, just over half of modernization initiatives (50.5 %) opted for software-as-a-service deployment models. This reflects the growing confidence in modular, standardized and scalable platforms designed for insurance complexity, such as SAP Fioneer’s Cloud for Insurance. This kind of architecture-led foundation supports large-scale changes or even simple updates (e.g., adjusting underwriting rules or launching new products) without requiring deep reconfiguration, especially when paired with robust application management services (AMS) to execute and oversee these updates. This reduces costs and accelerates time to market.

To enable continuous modernization, insurers should prioritize platforms that enable architectural transformation by:

• Offering open APIs to integrate ecosystems with banks, insurtechs and embedded insurance distribution partners
• Supporting real-time data access, automated compliance and scalability without needing full replatforming
• Allowing for modular rollouts, from claims and policy admin to billing, helping insurers align with business priorities
• Supporting the handling of historical data and integration with legacy infrastructure during transformation, minimizing disruptions and helping create a smoother experience for customers and internal stakeholders
• Being compliance ready with built-in support for auditability, data security and financial traceability and designed to flexibly comply with different regulatory frameworks
• Enabling low- or no-code solutions, allowing product teams to launch offerings, tweak underwriting rules or adjust pricing logic directly without routing everything through IT

Standardization is also key in an insurance platform because it enables scalability, maintainability and alignment across business units, especially in complex or decentralized organizations. It brings fragmented teams together under one IT layer while enabling faster time to value through proven, out-of-the-box processes. It also has a significant impact on maintenance and costs.

An architecture-first strategy supports steady modernization by allowing insurers to improve and update components over time with scalable, interoperable modules. This gradual, coexistence-based approach ensures continuity for customers while steadily building toward a more modern foundation.

2. Turn architectural vision into business outcomes

Technology alone doesn’t deliver continuous modernization. Leaders back these architectural decisions with clear operating models, disciplined execution and clear outcomes.

They create operational roadmaps aligned with the organization’s strategic goals and plan migrations by evaluating existing technical infrastructure. This helps identify gaps in technology, the need for early investment in data tools and avoid downstream bottlenecks during execution.

Successful insurers secure long-term executive sponsorship from day one. This support fosters experimentation and cross-functional collaboration and makes sure business and IT work toward shared goals.

Leaders also treat change management as a priority. They assess cultural resistance, clearly communicate the reasons for modernization and invest in training and support to enable confident adoption across teams.

Insurers that treat modernization as a continuous capability, grounded in flexible architecture and reinforced through operational discipline, build the infrastructure to lead change.

And to lead change, they must also redefine what success looks like.

A new definition of success: adaptability beats delivery

Modernization used to mean delivering a system on time and on budget. But in today’s market, those metrics don’t reflect resilience.

Winning insurers now measure success by how quickly and reliably they can change, with key indicators such as:

• Release frequency, speed of launching new products or services
• Ease of configuration, scaling or integration without IT bottlenecks
• Reusability of components, such as product configurations or service layers that cut duplication and accelerate delivery across lines of business

That level of adaptability does not happen by chance. It’s built into the foundation of how leading insurers operate.

Modernization that sticks starts with the right foundation

Insurers that succeed don’t treat it as a milestone. They treat it as an organization- and a system-wide capability: the ability to change continuously and confidently. That capability is built on modern architecture, reinforced by operational discipline and sustained through committed leadership.

The ones who get that right will outpace disruption.

The post Building insurance modernization that sticks  appeared first on SAP Fioneer.

In commercial real estate (CRE) lending, risk often creeps in when a KPI quietly slips below target, a key tenant moves out, a break clause looms, or a debt service starts to dip. Inevitably, these signals will be buried in rent rolls, occupancy rates, and covenant trackers, and scattered across departments. If no one sees the problem in time, a routine deal can quickly become a write-off with a significant impact on the bank’s bottom line. 

The European CRE market faces over €300 billion in refinancing by the end of 2026 as low-interest legacy loans collide with tighter covenants and rising repayments. At the same time, average cost-to-loan ratios have jumped from 55% pre-2022 to 64% by the end of 2024, reducing the buffer banks have to absorb shocks. 

With each missed breach, banks face increased NPL ratios, deeper regulatory scrutiny, and potential losses in the hundreds of millions. In extreme cases, continuous failure to identify red flags and manage risk can even put a bank’s license to lend at risk. 

This article explores the three key reasons NPLs escalate, plus how a platform approach to credit risk can help teams reduce NPLs as well as identify otherwise hidden opportunities. We’ll cover the consequences for banks with spreadsheet-based tracking, how risk, lending, and portfolio teams can tap into real-time data to uncover profitable deals and mitigate losses and how SAP Fioneer’s Credit Workplace enables early detection and smarter restructuring.

Explore SAP Fioneer’s Credit Workspace to see how banks are reducing NPLs today. 

The consequences for banks with spreadsheet-based tracking 

In CRE lending, credit risk management should start long before a borrower defaults. Yet in many banks, risk is still being treated as a reactive function and the systems in place are part of the problem. 

Even today, a typical CRE loan can still take months rather than weeks just to reach a decision – mainly due to the complexity of the process. 

Origination, servicing, covenant tracking, and risk management often live in separate systems or spreadsheets where there is no unified view of a loan across its lifecycle, plus no audit trails of how a covenant breach was handled. The time that risk analysts spend copying and pasting data between platforms is also an invisible operational cost and one that leaves banks unable to respond to deterioration until it’s too late. 

The cost of this late action is staggering. To put this in context, a single €50 million loan default requires the interest income from €2 billion in new lending or 40x new €50m loans at a 2.5% margin just to offset the capital loss. 

The inability to spot borrower distress early enough can lead to failure across three critical areas: regulatory compliance, profitability, and capital efficiency.  

1. Siloed systems increases regulatory risk
When key risk functions are split across siloed systems and spreadsheets, banks may struggle to demonstrate that they’ve acted early or appropriately. Without integrated risk monitoring, real-time visibility into deteriorating performance or auditable trail of intervention, teams may struggle to provide assurance that they are meeting fair treatment obligations.  
Together, this puts banks at intensifying regulatory scrutiny, additional capital buffer requirements, potential fines and in extreme cases, loss of their license to lend. 

2. Missed signals means rising NPLs and lower profitability 
NPLs are one of the biggest drags on bank profitability, with even a single mid-sized corporate default needing enormous new lending volumes just to recover the capital loss.
Yet, most banks still track key risk indicators like DSCR, rent rolls, and occupancy rates in asynchronous tools like Excel – often on shared drives, manually updated by relationship managers.
Analysts in multiple teams may track metrics in multiple different ways, and just one broken formula or miskeyed cell could significantly distort exposure metrics. What’s more, it’s all too easy to miss key information or early warnings like a tenant moving out then have to act after the breach, driving NPLs up even further. 

3. Poor visibility erodes capital efficiency
Credit risk monitoring isn’t just about avoiding losses. When a bank’s risk oversight is weak, regulators may require them to hold higher capital reserves to absorb potential losses – tying up funds that could be generating returns elsewhere.

Rather than force banks to put excess capital in reserve and drag down performance even if defaults never materialize, banks with strong credit systems and higher certainty can boost return on risk-weighted assets (RoRWA). 

How risk, lending, and portfolio teams can tap into real-time data to uncover profitable deals and mitigate losses 

If early warning signs are falling through the cracks, it’s no surprise if profitable lending opportunities are too. In a siloed system, originators are unable to see the full picture of portfolio exposure; risk teams lack insight into borrower behavior beyond the deal; and portfolio managers are stuck reviewing stale data once it’s already too late to act. Inevitably, promising deals will be delayed or declined not because they’re too risky, but because teams lack the information to fully assess them. 

To reduce NPL ratios and scale CRE lending sustainably, banks need a connected view of every deal. That means unifying front and back-office teams (originators, risk analysts, credit approvers, and portfolio managers) around the same, structured data in real time.  

Here are four principles for operational alignment that unlock both risk mitigation and revenue growth: 

1. Make structured data the foundation 
CRE lending generates a huge volume of paperwork: title deeds, valuation reports, insurance certificates, and environmental audits. 
Traditionally, these documents will be manually reviewed, summarized, and rekeyed into local systems: an approach that slows underwriting with approval bottlenecks and disconnects monitoring data from origination insight. 
Leading banks are moving to a data-first approach that uses AI to pull key facts and figures from documents, organize them into structured, machine-readable fields, and automatically populate risk and lending systems. 
Rather than have skilled analysts spend their time copying and pasting data, they can instead double down on high-value work like assessing creditworthiness or advising clients. 

2. Automate covenant and KPI monitoring across the loan lifecycle
Too often, monitoring is done at a local, end-user level.. Yet, as portfolios grow, so do the risk signals – especially when these projects might span multiple quarters or involve complex tenant arrangements.
Without automation, analysts rely on memory, spreadsheets, or calendar reminders to track covenant thresholds and tenant milestones, making it easy to miss critical triggers.
Instead, the banks that implement event-based lifecycle monitoring will receive automated notifications. For example, do we need a covenant review when occupancy drops below 90%? Or DSCR is nearing the soft covenant limit? Or a critical lease break clause is due.
Building these steps into the workflow means that banks can surface issues before they escalate. Likewise, teams can spot high-performing borrowers early and identify prime moments to upsell or restructure.  

3. Make cash flow forecasting visual, intuitive, and collaborative
In many banks, scenario planning is still performed in static spreadsheets or buried in code-heavy risk tools – formats that may be difficult to first understand or second communicate to other teams or clients. Its code-heavy nature also limits who can contribute to it.
With integrated, visual forecasting tools, analysts can run “What if” scenarios in real time, model the impact of market shifts, tenant exits, or interest rate hikes, then share results instantly with risk committees, credit approvers, or client teams. 
Ultimately, when forecasts are simple to create and easy to share, they become strategic tools across the workflow.

How SAP Fioneer’s Credit Workplace enables early detection and smarter restructuring  

In commercial real estate lending, distress is very rarely a single catastrophic event. Rather, it’s a slow decline and sequence of KPIs drifting below threshold, key tenants exiting, or lease break clauses approaching. When these critical risk signals come without warning and are hidden in spreadsheets or static documents, it’s easy to miss the window when a deal could have been saved or even when a more profitable deal arises. 

SAP Fioneer’s Credit Workplace gives banks the visibility and control to intervene before it’s too late – enabling real-time, asset-level monitoring, automated risk detection, and structured decision-making across the full lifecycle.  

Unlike generic credit systems that require costly customization, the platform is designed for the complexity of CRE – supporting smarter, faster responses across the front, middle and back office. 

Banks using Credit Workplace are able to: 

Spot risk before it escalates with real-time monitoring 

With the Credit Workplace, credit teams no longer need to wait for quarterly reviews or manually track performance metrics to identify emerging risks. The platform continuously monitors every CRE exposure, automatically flags early warning signs and triggers follow-up actions to give lenders more time and more confidence in their decision-making. 

Here’s how it works: 

• AI-powered document extraction: Rather than manually rekey data from tenancy schedules, valuation reports, or insurance documents, the system uses AI to extract and structure the data automatically.  

• Automated covenant and KPI tracking: Built-in rules monitor financial and non-financial metrics (like LTV, DSCR, occupancy levels, and lease break clauses). When a metric crosses a threshold, the system triggers an alert and assigns a follow-up task.  

• Visual cash flow forecasting and scenario analysis: The platform includes intuitive dashboards and bar charts so analysts can forecast cash flow impacts, stress test various outcomes, and instantly share results with credit teams or risk committees. Teams can quickly model market shocks or tenant exits, simulate payment plans or term extensions, and recommend solutions that reduce loss exposure. 

Together, these capabilities shift risk management from a retrospective task to a dynamic, always-on function – so that teams can have the upper hand. 

Unlock more restructuring options with earlier insights 

By surfacing issues earlier in the loan lifecycle, teams gain the time and clarity needed to structure borrower support plans that are both commercially smart and regulatory sound.  

That might mean offering an interest-only period, extending the loan term, adjusting repayment schedules in line with a tenant shift or market disruption, or initiating proactive client conversations about upcoming lease events. 

To support this, the Credit Workplace includes:  

• Asset-level visibility and lease-level drilldowns: Dashboards help teams quickly identify which tenants or leases are driving risk at the asset level, allowing for targeted interventions like adjusting cash flow models based on a key tenant exit or renegotiating terms.  

• Role-based workflows for credit and risk collaboration: When early warning signs are detected, the platform routes follow-ups to the right team – whether it’s a relationship manager, credit analyst, or risk lead – accelerating response times. 

Real-time data is the key to reducing NPLs without slowing down CRE lending 

Ultimately, NPLs often arise from missed opportunities to act and no system to track the subtle shifts like a drop in occupancy, a lease expiry, or a breached covenant that might otherwise go unnoticed in a spreadsheet. Once the moment to intervene has passed, options narrow fast. 

SAP Fioneer’s Credit Workplace gives banks the tools to stay ahead of risk with: 

• Automated alerts for covenant breaches and performance dips 
• Real-time monitoring across asset, lease, and portfolio levels 
• Structured workflows to support fast, auditable decisions 

With earlier insight, banks can restructure deals while they’re still viable, reducing defaults without slowing down lending. 

Ready to see how Credit Workplace could work in your organization? Request a personalized demo here. 

The post Using data to reduce NPLs and identify profitable deals earlier appeared first on SAP Fioneer.

And yet, if done well, commercial real estate loans offer a large opportunity for banks. In 2024, European CRE investment volumes surged to €206 billion – a 23% year-on-year increase. Meanwhile, more than €300 billion of existing loans will need to be refinanced by the end of 2026: a major funding gap for banks to step into. Therefore banks have opportunities at both ends, with new originations and existing lifecycle deals that are due to expire. 

To scale sustainably and take advantage of this opportunity, banks need a process that’s fast, aligned, and built for complexity. In this article we’ll explore the operational cracks that stop CRE lending from scaling, what scaling commercial real estate (without the equivalent cost increase) really looks like and how a real-time, scalable solution for CRE lending looks like.

Explore SAP Fioneer’s Credit Workplace to see how banks are scaling CRE lending without scaling risk or complexity. 

The operational cracks that stop CRE lending from scaling 

Most commercial real estate teams are structured to win individual deals, not for scale across the business unit. Risk, servicing, and origination typically work in silos, with separate systems, documents, and definitions of the truth.  Beneath every loan lies a stack of processes (origination, underwriting, servicing, covenant tracking, and portfolio oversight) that still run through disconnected systems and manual workarounds. 

Here’s where the cracks begin to show when banks are looking to scale these types of loans: 

1. Risk accelerates faster than most banks can respond 
Volatility in CRE markets is rising – with interest rate fluctuations, tenant churn, hybrid working, and asset devaluations moving faster than traditional credit processes can track. Indeed, according to Savills, average office vacancy rates across Europe reached 8.4% in Q1 2025 – a modest rise, yet still one that is shifting faster than many landlords can keep up with. 
Alongside this change, most banks are still flying blind. Manual covenant checks, spreadsheet-based tracking and siloed data mean it can take months to spot changes in key metrics like occupancy drops, rising loan to value (LTV), or falling debt service coverage ratios (DSCRs). By the time a problem surfaces, the window to work with the borrower on corrective measures has closed. 
In fast-moving markets, that lag turns manageable issues into potential defaults and without real-time monitoring or automated alerts, credit deterioration could accelerate beyond the bank’s ability to stop it.

2. Regulation complexity increases while margins are shrinking 
Tightening regulatory demands, from IFRS9 / IFRS17 to ESG, are increasing the compliance burden across CRE portfolios.
At the same time, cost pressures are mounting. With margins under huge pressure, it’s getting more expensive to maintain regulatory compliance, particularly when everything is manual. Siloed data, lack of auditability, and fragmented approval workflows make it harder for banks to keep pace without adding more headcount or operational risk. 

3. Inefficiency is baked into every step of the process 
CRE lending remains one of the most complex workflows in banking, with long deal cycles, multiple stakeholders, and repeated data entry. If there’s still dual keying across systems, the customer information is entered multiple times – resulting in wasted time and rising operational risk.
To solve these challenges, banks need full transparency across the entire lifecycle. That means building a single source of truth, and enabling smarter, faster decisions at every stage from origination through to early risk detection.

What scaling commercial real estate lending – without the equivalent cost increase – really looks like 

Historically, the only way to grow CRE lending has been to grow teams and throw more people at the problem. But with tightening margins, that approach is no longer sustainable. The business opportunity may be growing but unless operations evolve, the cost base grows right alongside it.  

If you have one core system with shared data, automated alerts, and integrated workflows, banks can make faster, smarter decisions with fewer workarounds, fewer one-off fixes, and fewer end-of-quarter surprises. It also means that the front and back office are working from the same playbook with shared data, shared workflows, and shared visibility into what’s coming next. 

In practice, this looks like:  

Digitalization of CRE lending workflows: Much of CRE lending is still slowed down by paper trails and siloed information. Full digitalization fixes that. It connects the whole workflow so documents are uploaded once, key data is pulled out automatically, and teams spend less time chasing files and more time making decisions.

Transparency of deal data: In most banks, deal data is scattered across spreadsheets and different tools. With full transparency across the credit lifecycle, all the key information is captured once and shared across teams – meaning credit, risk, and portfolio managers are working from the same numbers, the same deal view, and the same reality in real time.  

Early warning signals of credit risk: When tenant churn, falling coverage, or covenant breaches happen, rather than rely on someone spotting it in a spreadsheet, smart triggers flag these risk signals automatically. This means teams can act early rather than react after the fact. 

A single workplace for collaboration: Instead of moving between systems or duplicating work, teams collaborate in one place. That means fewer emails, fewer handoffs, and less duplication. Everyone – wherever they’re based – can see the same deal, update the same data, and move faster. 

Compliance that’s built into every process: Audit readiness and access controls are already baked into the platform. Because it’s cloud-native, it’s also more cost efficient and easier to run. 

Together, these capabilities mean that banks are no longer stuck choosing between growing their commercial real estate portfolio and keeping their cost base under control. 

Rather, instead of following the well-trodden path of cyclical driven ‘hire and fire’ policies, they can handle more volume with their existing team. Analysts aren’t wasting hours on admin, risk teams aren’t buried in spreadsheets, and leadership gets a clear, real-time view of what’s happening across the entire book. 

How SAP Fioneer brings a real-time, scalable solution to CRE lending 

A central, transparent workspace is the missing foundation in most CRE lending teams, and it’s exactly where SAP Fioneer’s Credit Workplace delivers the biggest impact. 

Instead of relying on disconnected systems and manual covenant tracking, Credit Workplace gives banks a single digital environment to manage the full lending lifecycle. From origination through to servicing, amendments, and credit risk management, everything happens in one place – purpose-built for the complexity of CRE lending. 

Here’s how it helps banks scale without scaling risk or cost: 

• Digital workflows that reflect CRE lending: Unlike retrofitted platforms that rely on static templates and customized workflows, Credit Workplace is digitally engineered for the complexity of commercial real estate from day one. Every step – from origination to servicing – is fully digitized with structured workflows tailored to how CRE teams actually work. Granular metrics like lease breaks, expiry dates, vacancy levels, and rent rolls are tracked automatically in one shared system, risk assessments are applied consistently, and approvals are managed in-platform, so deals can be made faster and cleaner. 

• Real-time visibility into deal health: With volatile markets and illiquid assets, CRE lenders can’t afford delays. The Credit Workplace provides real-time visibility into deal performance, automatically surfacing risk indicators such as covenant breaches, falling DSCR, or market-value changes. Teams can quickly assess exposure and take action, whether that’s restructuring a non-performing loan or adjusting capital allocation, before risk compounds. 

• Scalable efficiency to grow without drag: With automation, intuitive interfaces, and seamless data flow across the lifecycle, Credit Workplace removes the need for dual keying or siloed data entry. Experts are freed up to focus on value-add tasks such as decision-making and relationship management. By standardizing how teams collaborate, and embedding auditability and compliance into the process, banks can scale their loan book without inflating their operational cost base and enhance property insights with both internal and market data. 

What’s more, the modular, cloud-based Credit Workplace can be integrated easily into banks’ existing infrastructure, unlike many legacy competitors that require complex transformation programs. 

Case study: How pbb improved both front and back-office efficiency  

When Deutsche Pfandbriefbank (pbb) – a leading European specialist lender in commercial real estate – set out to modernize its credit operations, the goal was to create a platform that could scale deal volume without scaling complexity. 

Like many legacy banks, pbb faced a common bottleneck: while the deal pipeline was growing, the underlying operating model couldn’t keep up. CRE lending processes across the lifecycle were disconnected, siloed, and inconsistent. 

From disjointed workflows to a single source of truth 

Seeing that CRE growth depends on operational control, not just capital, pbb partnered with SAP Fioneer to co-develop Credit Workplace: a fully integrated, end-to-end lending platform.
In just 18 months, the team delivered a live, scalable solution that underpins pbb’s commercial real estate operations.  

From incremental improvements to 20% efficiency gains and scalable growth 

Since going live, pbb has seen a 20% increase in credit process efficiency, faster, more consistent decision-making, stronger collaboration across origination, credit, and risk, and a modern data foundation ready for AI and predictive analytics. 

“By combining standard capabilities with institution-specific needs, we improved both front and back-office efficiency – and built the operational backbone we need to scale,” said Andreas Hoschek, the Director of Operations and Digitalisation at pbb. 

Read the full case study here. 

The post Scaling CREF loans without increasing costs appeared first on SAP Fioneer.

In 2024, annual investment in EMEA commercial real estate reached €206 billion, marking a 23% YoY increase  driven by strong activity in sectors like logistics, mid-market real estate, and infrastructure projects. At the same time, a recent European Central Bank survey of major eurozone leaders found that corporate loan demand continued rising last quarter despite geopolitical uncertainty and high rates. 
Yet despite the growth opportunities that commercial and commercial real estate (CRE) lending represent, many banks are struggling to scale and meet the demand. Many institutions are still managing deals using a fragmented web of spreadsheets, shared drives, and siloed systems – slowing approvals, obscuring risk, and limiting growth. 

Risk and operations teams often work in isolation; deal data is inconsistent and often manually rekeyed; approvals are hard to track, and audit trails are not easily accessible. The result is a process that is slow, opaque and difficult to scale, particularly in high-stakes, asset-based lending. 
To scale commercial lending, banks need to connect origination and risk on one platform – structuring deal data at the source and embedding real-time visibility of the loan cycle. 

In this article, we’ll explore the opportunity for banks within commercial lending, what holds them back from investing in commercial lending and what a truly integrated commercial real estate finance solution would look like.

The opportunity for banks with commercial lending  

In a landscape of shrinking margins and rising cost of funds, commercial lending stands out as an increasingly stable opportunity. Margins are typically healthy and are accompanied by regular fee income, and unlike consumer lending, these relationships tend to be sticky and high value – particularly in the mid-market. 

A customer might begin with a term loan or revolving credit facility but as their business scales, so too does the opportunity for cross-sell across business and personal lines. That same founder could become a high-net-worth client or their company could enter capital markets. 

There’s significant growth potential not just in volume, but in lifetime value. And even more so for banks that modernize their infrastructure to enable modern tech features such as real-time risk insights, unified customer views, and event-driven workflows. 

Banks that embed real-time risk insights within loan origination – typically through automated scoring and data dashboards – see faster approvals, lower operating costs, and better controls. According to McKinsey, digital credit platforms deliver up to 40% lower costs while dramatically improving the customer experience. 

Instead of relying on static reviews or manual processes, deal teams can see the full picture of a borrower’s creditworthiness as financials are updated, risks flagged in real time, and dynamic pricing or terms dynamically adjusted as market conditions change. From the moment a deal enters the pipeline, teams gain a full view of the borrower’s exposure, collateral, and compliance – ultimately lowering the risk of non-performing loans (NPL) or at least having the ability to spot them as early as possible. 

Commercial lending remains one of the few areas in banking where margins are strong, cross-sell is high, and relationships are long-lasting. But the banks that win won’t just be those with the biggest balance sheets. They’ll also be those that lend smarter, faster, and at scale. 

That means building a commercial credit engine designed for today’s market that is: 

• Structured, auditable data from day one 
• Has real-time risk signals built into origination 
• Includes connected workflows that reflect how teams really operate 

By upgrading the infrastructure that supports commercial lending, not just the user interface, banks can unlock faster deal cycles, sharper risk assessment, and more responsive client service.  

What holds banks back from investing in commercial lending 

On paper, commercial lending is a clear strategic bet. But many financial institutions are still hesitant to invest. Why? It’s not the complexity of the deals; it’s the infrastructure surrounding how those deals are assessed, managed, and monitored. 

1. Disconnected data means teams aren’t working from the same playbook 

Unlike retail lending, commercial credit is low-velocity by design. Each deal is complex, often bespoke, sometimes syndicated and heavily reliant on expert judgement. Loan sizes are large, risk is concentrated, and approvals depend on multi-party workflows involving front office, underwriting, credit, risk, portfolio, and compliance. 

A typical deal may require 50 to 100+ data points – from borrower financials and industry trends to collateral details, profitability, ESG metrics, regulatory considerations, and more. But that’s only part of the challenge. The other is where and how that data is handled. 

Instead of flowing through a unified platform, deal data is scattered across a patchwork of disconnected systems. The front-end deal capture might sit in a CRM or loan origination tool, risk models may run on Excel or SAS, servicing data may live in legacy core banking platforms, and covenants tracked manually with heavy use of end-user computing. Some systems are cloud-based; others are still on-prem. There’s rarely a consistent view, let alone a real-time one. 

Each team – from relationship managers to credit officers to compliance – works with their own interface, their own data formats, and their own version of the truth. The result is manual rekeying, inconsistent inputs, approval delays, and missed insights. 

Even when demand is high, this fragmented architecture makes it hard to scale. And with clients expecting faster decisions and more responsive service, especially in mid-market and corporate segments, the cracks become even more visible. Without a unified, structured approach from origination through to monitoring, banks risk falling behind on both efficiency and customer experience. 

2. Risk assessments rely too heavily on the past and ignore what’s coming next 

Another major challenge is banks’ continued reliance on historic data to make forward-looking credit decisions. Most banks evaluate a customer’s last three to five years of financials but stop short of assessing what’s coming next. 

In volatile sectors like real estate, shipping, or aviation, that backward-looking approach quickly breaks down. To make smarter lending decisions, banks need a predictive lens: 

• Are there material changes expected in the borrower’s business? 
• How is the industry evolving? 
• What external factors, from oil prices to regulatory shifts, might impact performance? 

Banks often have the internal data to answer some of these questions but few are combining it with external insights like ESG ratings, sector benchmarks, or macroeconomic indicators to get a complete picture. 

This is where open APIs and third-party data providers come in. By integrating external intelligence into the credit process, banks can sharpen risk assessment, support sustainability-aligned lending, and stress test portfolios with real-world context. 

The issue isn’t a lack of data – it’s using the wrong data, in the wrong way, at the wrong time. In short, that’s what’s holding banks back: legacy decisioning models, limited external data use, and missed opportunities to modernize how risk is analyzed and acted on. 

How an integrated commercial real estate finance solution can look like  

SAP Fioneer’s Credit Workplace is designed specifically for commercial banks managing complex asset-based lending portfolios. It replaces spreadsheets, Word templates, and manual workarounds with a connected platform that unifies every stage of the credit lifecycle – seamlessly integrating multiple data inputs across origination, digital decisioning, risk monitoring, servicing, and reporting. 

Acting as the single source of truth for front and back office, Credit Workplace is a central operating system for asset-based lending helping banks act faster, manage risk more proactively, and scale without adding cost. 

Replace siloed systems with a unified source of truth 

Every stakeholder – from relationship managers structuring a new deal to a credit analyst reviewing risk metrics, or a portfolio manager tracking exposures – works in the same platform, on the same real-time data. 
Credit Workplace brings together origination, credit risk assessment, lifecycle management all in one solution. Built on an open architecture, it integrates seamlessly with existing Fioneer solutions (like CL/CML, CMS, SAP FI, and risk engines) as well as external data sources – enabling richer insights and smarter lending decisions. 

By consolidating fragmented tools into one unified environment, banks gain a more complete, real-time view of each customer and credit exposure. That means better decisioning, stronger risk controls, and ultimately, a higher-quality, more resilient loan book. For instance, a bank can automatically ingest property data from online property portals to validate real estate valuations or occupancy trends then combine that with internal credit scores or pricing models. The result is more accurate decisioning and real-time portfolio oversight. 

Spot the strongest deals and the biggest risks earlier 

Credit Workplace gives banks the insight and agility to identify the most promising opportunities and flag high-risk exposures sooner in the lending process before they impact the bottom line. It does this in two ways:

First, by integrating internal credit scores with external market feeds, the platform gives deal teams richer, context-aware insights into borrower quality, asset valuation, and market dynamics. That means banks can access the true potential of each opportunity, not just what’s on paper. 

Second, this data is delivered in real time. Rather than relying on static reports or end–of-day batches, lending teams get instant visibility into deal-level KPIs and portfolio-level risks – from tenant lease expiries to fluctuating loan-to-value ratios. That allows faster go or no-go decisions, earlier detection of NPL signals, and more confidence in complex lending environments. For instance, if a borrower begins to show signs of stress, banks can use SAP Fioneer’s automated KPI tracking, risk alerts, and scenario forecasting to flag early signs of NPL risk, laying the foundation for time-sensitive decisions based on live data.  

Configure workflows with more control, and take a deal from start to finish within one platform 

Every bank’s lending model is different. Credit Workplace supports tailored workflows no matter what lending model by asset class, jurisdiction, or deal type while preserving consistency through embedded guardrails and governance logic. 

Whether managing CRE, infrastructure, or sponsor-backed deals, banks can: 

• Configure layered approvals, version control and covenants 
• Connect pricing models and internal risk scores 
• Tailor workflows without compromising compliance 

Importantly, there’s no need for a full rip and replace. Credit Workplace can be deployed incrementally, keeping the systems that already work while establishing a clean data foundation that supports end-to-end transparency.  

While other solutions focus on analytics or loan origination alone, Credit Workplace connects every step of the credit lifecycle. 

How pbb Deutsche Pfandbriefbank modernized its credit processes 

Europe’s leading specialist lenders for commercial real estate and public sector finance, pbb Deutsche Pfandbriefbank (pbb) set out to modernize its credit operations. The goal was clear: replace manual workarounds and fragmented systems with a scalable foundation for growth. 

pbb managed high-value, cross-border deals but its internal infrastructure was slowing things down. Credit decisions were being made through a patchwork of spreadsheets, email threads, and disparate tools, making it difficult to track deal progress or enforce consistent risk policies across jurisdictions. 

SAP Fioneer’s Credit Workplace helped change that. Built for structured lending environments, the platform enabled pbb to consolidate its deal workflows, improve transparency, and build governance into every step of the credit lifecycle. 

By capturing decision-grade data at the point of origination, pbb could ensure clean, reusable information flowed through underwriting, approvals, and servicing. Custom workflows aligned with internal decisioning processes, while embedded documentation tools replaced the need for offline templates and email attachments. 

Perhaps most importantly, every stakeholder from front-office originators to portfolio managers gained live insight into the same credit risk data, enabling faster and more informed decisions. 

As a result, pbb: 

• Reduced time-to-decision on complex CRE transactions 
• Strengthened compliance and audit readiness across markets 
• Delivered a more streamlined, responsive experience to commercial borrowers 

The transformation not only modernized pbb’s credit operations, but also positioned the bank to grow its lending book without adding operational complexity. Read the full case study here.  

Modern commercial credit risk management starts with a connected solution 

Commercial lending is too important and complex to be managed across spreadsheets and siloed systems. From infrastructure and logistics to commercial real estate, demand is rising but without integrated tools, banks risk falling short on both compliance and speed. 

SAP Fioneer’s Credit Workplace offers a platform for commercial credit risk management with: 

• One workspace for high-quality, auditable deal data 
• Configurable workflows and approval logic 
• Seamless integration across origination, underwriting, and portfolio oversight 

Banks like pbb Deutsche Pfandbriefbank are already using Credit Workplace to update their lending stack, improve decision-making, and grow with confidence. 

Ready to see how Credit Workplace could work in your organization? Request a personalized demo here. 

The post Scaling smart: how banks can unlock growth in commercial lending appeared first on SAP Fioneer.

But liquidity management has grown more complex and not merely because of high interest rates. Market volatility and increasing demands for real-time settlements are the true drivers of the need for instant liquidity visibility.

So, how can banks navigate these market and instant-payment pressures to ensure financial stability and growth opportunities?

The answer lies in real-time liquidity intelligence.

By modernizing liquidity management, not only can banks improve forecasting, manage risk, and ensure compliance for corporate treasurers and liquidity managers. They gain a competitive edge, enabling senior management to take a proactive approach in understanding key business drivers and navigating crises more effectively.

Only a modern tool can enable banks to align their liquidity management strategies with their broader business needs, adding value to consumers and shareholders alike.

In this article, we explore the key challenges of managing liquidity, the value of advanced, real-time solutions, and strategic recommendations for implementation.

The challenges of bank liquidity management today

Bank liquidity management is the complex process of managing a bank’s cash positions, payment flows, and financial risks in real-time to ensure the bank has sufficient funds to meet its financial obligations and regulatory requirements.

The key parts of liquidity management in banking include:

• Cash position tracking. Banks monitor intraday cash flows across multiple payment systems and track funds across different currencies and legal entities to understand money movement and financial risk transfer.

• Forecasting and prediction. Banks need to anticipate liquidity pressures by predicting end-of-day cash positions so they can identify potential financial risks or crises.

• Regulatory compliance. Banks need to meet certain regulatory expectations around liquidity management, such as maintaining appropriate liquidity buffers, so they can demonstrate their ability to manage financial risks to regulators.

• Payment management. Controlling payment flows is crucial in a bank’s liquidity management process. They need to prioritize time-sensitive payment obligations and ensure critical payments are processed efficiently.

• Risk mitigation. To prevent potential liquidity crises, banks must detect and correct anomalies as they happen to ensure they meet the necessary cash reserves and collateral requirements.

So, what’s preventing banks from managing their liquidity adequately? Multiple factors play a part.

1. The impact of outdated systems on liquidity management  

Various mergers and acquisitions throughout the years have taken a toll on the banking world’s current liquidity management systems. Legacy treasury systems intertwined with modern payment software solutions and disparate data warehouses have created data silos, preventing banks from tracking liquidity in real time across their organization.

Fragmentation makes harmonizing liquidity-related data across disparate legal entities and multi-currencies a significant technical challenge.

Banks often rely on manual processes to gather data from these different sources, reconcile it, and then forecast their liquidity positions. Insights may come in batches or even at the end of day, making intraday liquidity forecasting impossible and delaying crucial information on which to base decisions.

For example, a bank with multiple automated clearing house (ACH) and wire systems must reconcile their balances manually. But this resource-intensive process introduces the likelihood of errors, increases risk, and slows decision making.

2. The cost of poor forecasting and liquidity visibility 

Without real-time insights, gaps in liquidity can prove costly.

A lack of holistic, real-time data on cash flows and positions has multiple ramifications. It forces banks to secure emergency funding at higher costs, undermining their profitability, financial health, and strategic financial planning.

Any inaccuracies in liquidity reporting and forecasting also impact business strategy (on local and international levels), cash product pricing, and capital allocation, ultimately influencing earnings and shareholder value.

For instance, a mid-sized bank that underestimates its liquidity needs will need to borrow cash at premium rates to avoid shortfall penalties, reducing its revenue.

External factors such as interest rate volatility, inflation spikes, market downturns, and geopolitical events only exacerbate these liquidity pressures and emphasize the need for advanced liquidity management systems.

3. Increased regulatory scrutiny on liquidity accuracy 

The liquidity crises of Silicon Valley Bank (SVB) and Credit Suisse have underscored the need for proactive cash management.

Considering these bank runs and the increasing demand for accuracy, the European Central Bank (ECB) ranked effective liquidity management as a key area of improvement and offers extensive best practices to help banks mitigate liquidity risk.

Even with additional guidance, banks still come under greater scrutiny because of these collapses. Stricter Basel III liquidity and capital requirements now extend to Tier 2 and 3 organizations and involve real-time liquidity monitoring even for banks with assets under $250 billion.

Banks must be more conservative with their liquid assets to meet these new requirements. But this is both capital intensive and an operational burden.

In addition, banks must now be able to demonstrate they can both understand and manage their cash flows and liquidity positions, and document these in real-time reporting that is not only accurate but offers valuable insights.

While this reporting meets regulatory requirements, it serves a dual purpose by also providing crucial intelligence that senior management should use to drive business-informed decisions.

The evolving regulatory landscape is forcing banks to transform liquidity management from a reactive, burdensome compliance exercise into a proactive strategic lever for sustainable growth.

The role of an advanced liquidity management system for banks

Only a ready-built solution that harmonizes bank data, automates liquidity monitoring, and offers real-time updates can manage the challenges of forecasting, reporting, and risk management across a bank’s operations.

An advanced, data-driven system enables treasury, liquidity, and payment operation managers to go beyond compliance. With business intelligence at hand, senior managers can create operational efficiencies and enhanced insights to improve a bank’s overall financial performance.

Here is how an advanced liquidity management system can turn liquidity management into a proactive and strategic business tool.

Real-time liquidity tracking and forecasting

An ideal liquidity management system (LMS) can provide automated, real-time monitoring of liquidity positions across multiple accounts. With it, banks gain visibility and control over cash flow, payments, receivables, and collateral, improving cash flow forecasting accuracy.

Banks can compare current liquidity to expected values and checking deviations (e.g., within one standard deviation or two percentage points), detect anomalies, and predict shortfalls.

For instance, a European bank identifies missing payments for the amount of $2 billion in real time. An LMS triggers an automated alert so the bank can move funds to cover the gap and prevent a shortfall.

Multi-entity, multi-currency data aggregation

An LMS can aggregate complex, multi-dimensional data to provide banks with a unified view of their liquidity position globally, simplifying cross-border liquidity management.

For example, an LMS would enable a multinational bank to consolidate cash positions across multiple currencies seamlessly.

This eliminates manual oversight and allows for rapid responses when tracking issues arise. Here, global banks can identify missing transactions from their key counterparties with an LMS, helping them take action immediately.

Compliance automation

An advanced LMS enables banks to stay on top of their regulatory compliance reporting.

Banks can fulfill requirements such as Basel III or the liquidity coverage ratio (LCR) with built-in reporting, automating this task and avoiding manual processes that lead to inaccuracies and errors.

This enables banks to proactively measure, monitor, and manage short-term cash flows and liquidity positions and meet required liquidity buffers to avoid fines and penalties.

Advanced optimization features for liquidity efficiency

An advanced LMS offers intelligent payment flow controls to prioritize time sensitive financial obligations. Automatic alerting and anomaly detection provides a methodical, statistically driven approach for alerting and forecasting.

For example, with an LMS, a bank can detect when their liquidity is off target (e.g., 10% over, 12% under) by receiving notifications that trigger when liquidity levels breach statistical thresholds.

This functionality enables banks to not only take timely corrective actions but also optimize liquidity costs by identifying which business units drive funding expenses and effectively manage excess cash.

Build vs. buy: making the right choice

Currently, banks can build their own LMS in-house or purchase an off-the-shelf system. We explore the reasoning between building an in-house LMS or buying a ready-to-use solution.

Why some large banks choose to build

Many large banks that have already invested millions in building their own liquidity management systems may be reluctant to switch to an off-the-shelf solution.

They currently have the ability to fully customize their cash flow management system to specific business and operational needs and processes. This allows them to remain in full control of their system’s development, maintenance, and future enhancements.

However, an advanced solution, like SAP Fioneer’s Liquidity Management System (LMS), can offer co-innovation packages, giving banks a foundational solution they can customize going forward.

The hidden costs and time constraints of custom-built solutions

Though in-house building lets banks tailor their liquidity management to specific business needs, it can cost millions of dollars and take years before arriving at an ideal system.

The frequently changing regulatory landscape is one factor that slows down customization and inflates costs. Each year, banks need to constantly integrate and customize systems just to meet new reporting requirements.

Customizing fragmented legacy systems is also resource intensive, typically needing 10 to 15 developers dedicated to this task over multiple years, increasing the investment needed to reach an optimal solution.

How off-the-shelf solutions provide faster, more cost-effective implementation

Ready-to-use solutions built specifically for bank liquidity management can offer lower investment and faster implementation.

For example, an advanced solution provides built-in functionality banks don’t need to develop from scratch. Multi-currency, multi-entity data aggregation, real-time forecasting, and payment flow controls are already available. Data is automatically integrated and harmonized, enabling enhanced accuracy for liquidity reporting and forecasting.

This means banks can deploy a ready-to-use LMS in months instead of years.

As a software solution, an advanced LMS includes vendor support, maintenance, and updates. This enables banks to adapt to new compliance standards and integrate with new systems more easily, with no need for specialized staff to customize the process, reducing costs.

Above all, an industry-specific LMS can help banks meet evolving regulatory requirements while benefiting from reporting that also acts as strategic business intelligence.

Three key benefits of an advanced liquidity management tool for banks

Banks can benefit from LMS in multiple ways.

1. Enhanced forecasting and real-time alerting

An advanced LMS offers a data-driven approach that provides enhanced forecasting and real-time alerting that regulators favor. With this data, banks can see their cash positions, payment flows, and liquidity across multiple currencies and legal entities.

2. Automated anomaly detection for early risk mitigation

By proactively detecting anomalies, LMS provides early warnings to banks about potential liquidity pressures or issues. This enables banks to quickly investigate the root cause and take action to mitigate any emerging liquidity risks.

3. Intelligent payment flow control for strategic liquidity positioning

Highly customizable payment flow controls enable banks to prioritize and manage time-sensitive payment obligations based on available liquidity. This helps honor critical payments during liquidity crunches while offering valuable business intelligence, such as insights into which business lines are driving liquidity costs, to enhance strategic decision making.

Paving the way to advanced bank liquidity insights

Managing liquidity in real time is no longer optional for financial institutions—it’s a must in today’s volatile landscape.

Instant insights do more than empower institutions to mitigate risks, optimize capital allocation, and swiftly respond to market changes. The valuable business intelligence real-time liquidity visibility provides is a necessity for all stakeholders—customers, management and shareholders alike—if banks want to survive turbulent times.

But how can banks future-proof their liquidity management strategies quickly without inflating costs?

SAP Fioneer’s Liquidity Management System (LMS) can be deployed in months instead of years at a fraction of typical in-house building costs. Designed specifically for banks, this ready-to-use solution provides the advanced liquidity insights, reporting, and forecasting functionality that enables banks to overcome their liquidity visibility challenges.

With SAP Fioneer’s LMS, senior management can future proof their regulatory requirements and gain the real-time liquidity insights needed to guide key business decisions and manage market turbulence efficiently. Banks can ensure customers remain confident in the institution’s financial stability and shareholders enjoy revenue growth.

Learn more about LMS and how it can transform your bank’s liquidity operations. Get in touch.

Sources:

1. Reuters – Central bank body calls for more detailed monitoring of bank liquidity risks

The post Revolutionizing liquidity management: Why banks need a more strategic approach appeared first on SAP Fioneer.

The second challenge: Compliance with rapidly evolving federal, state, and local laws and agency regulations

David Officer — In our previous article we introduced the “Five C’s” that challenge mortgage servicers. These are the critical and sometimes competing priorities of:

• Anticipating customer needs and providing a digital experience that enables self-service
• Ensuring compliance with evolving federal, state, and local laws and agency regulations
• Defending against new and emerging risks in cybersecurity
• Customizing services to their clients’ unique needs and preferences
• Controlling costs while addressing all of the above

This article will focus on the second C: Compliance with regulations. SAP Fioneer is serving the needs of banks and mortgage servicers globally and has partnered with Ranieri Solutions to assure we address federal state and local agency regulations appropriately.

Rob Lux — Mortgage Servicing is a highly regulated businesses in the world. There are over a hundred agencies and authorities that have implemented over 10,000 of regulatory compliance rules and there are nearly one thousand new regulations released each year. Mortgage servicers are expected to precisely follow these rules or risk severe fines and penalties.  Attempting to do so with aged technology puts servicers at risk for compliance violations including significant fines and penalties.

Cloud for Mortgage (C4M) enables mortgage servicers to remain compliant with the rapidly changing regulatory environment. With legacy systems, servicers are forced to cobble together workarounds outside of their core servicing system because those systems are built on legacy technology that is difficult to modify. Cloud for Mortgage is built on modern technology and is extremely configurable and flexible, which allows servicers using C4M to remain compliant with minimum effort and cost.

Mortgage legislative landscape

Mortgage servicers interact with a myriad of regulators such as the Federal Reserve, Federal Home Loan Banks (FHLB’s), Federal Deposit Insurance Corporation (FDIC), Office of the Comptroller of the Currency (OCC), Consumer Financial Protection Bureau (CFPB), Fannie Mae, Freddie Mac, Federal Home Finance Agency (FHFA), Department of Housing and Urban Development (HUD), Federal Housing Authority (FHA), Department of Veterans Affairs (VA), Ginnie Mae, 56 State Attorneys General, and various State Housing Authorities.

These entities have created over 10,500 rules that impact the mortgage industry and continue to create rules that servicers must adhere to. Prior to the pandemic, there were an average of about 250 new regulations per year.  That rate climbed to nearly 1,000 changes per year during the pandemic and that annual rate has continued.

Some examples of rules include the Fair Debt Collection Practices Act (FDCPA), Real Estate Settlement Procedures Act (RESPA/Reg X), Fair Lending Laws, Telephone Consumer Protection Act (TCPA), Fair Credit Reporting Act (FCRA), Equal Credit Opportunity Act (ECOA), and Truth in Lending Act (TILA/Reg Z). There were also many pandemic era rules and programs established, such as CARES and Homeowners Assistance Fund (HAF) as well as state and local laws that added to the complexity.

These rules are designed to protect consumers from unfair, deceptive, or abusive practices, which is an admirable goal. However, given the large number of different agencies involved and the extensive number of regulations, it is difficult for servicers to interpret the sometimes vague, ambiguous, and conflicting rules and their legacy technology was developed in a much simpler time in terms of regulatory oversight. Mortgage Bankers Association (MBA) President and CEO Bob Broeksmit said “…when it comes to regulatory agencies, working together is increasingly difficult. I’m not just talking about differences of opinion and priorities, which certainly exist. I’m talking more about the bureaucracy’s enormous growth, which has created a dangerous system of confusing and contradictory mandates. Put simply, Washington, D.C. is tying us in ‘regulatory knots.’ As these knots grow tighter, they restrict our industry and the millions of people we serve. They’re the real victims here—and they’re who we are trying to help.”

Challenges implementing the rules

In addition to interpreting the conflicting rules, the rules many times have aggressive implementation timelines, especially during emergencies such as the COVID pandemic. One example is the FHA Payment Supplement program that required significant time to implement in legacy systems. By contrast in Cloud for Mortgage, this program only required 45 calendar days from the time of announcement to implementation. Speed is critical when deploying new regulations into core servicing platforms and that requires modern technology.

Another example is the recently introduced Department of Veterans Affairs (VA) Servicing Purchase (VASP) program. A VA press release said the program will be available to all 40,000 veterans beginning on May 31.  However, on May 3 the Mortgage Bankers Association (MBA) and Housing Policy Council (HPC) sent a letter that servicers need at least six months more to deploy the programs changes and cited their technology as a limiting factor. This illustrates the challenge of keeping compliant with regulatory changes while utilizing older technology systems that are difficult to update, thus extending implementation timelines for an important program meant to provide assistance for our country’s veterans.

Challenges maintaining evidence of compliance with the rules

Further complicating matters, to comply with all the rules, servicers must maintain scrupulous records for each mortgage transaction and borrower interaction. They must provide timely and accurate information to borrowers and quickly respond to their calls and complaints. They must also be able to respond to audits from the various agencies. This currently requires significant staff and generates work for servicers that leads to higher costs to both the servicer and consumer.

Commenting on the increasing regulatory requirements and heavy reliance on manual labor, Chase CEO Jamie Dimon stated in a Bloomberg interview that “…some of these community banks now have more compliance people than loan officers.”

Like community bankers, mortgage servicers are attempting to cope with the ever-expanding regulatory rules. They need to learn of new rules, interpret the rules, and implement them in abbreviated timeframes with limited staff.  This is especially challenging since mortgage servicing systems were built in the last century using COBOL with VSAM files and run on mainframes.  These systems are notoriously difficult to update, which causes delays in implementing new rules.

These delays require servicers to implement rules changes outside of their core servicing system and either rely on third party applications or build their own workarounds using spreadsheets, robotic process automation (RPA) tools, or other “surround-ware” solutions. Data and other records such as documents and images are stored in multiple disparate systems outside of the core servicing system, making it difficult to respond to borrower questions and regulator audits quickly and accurately. This can lead to major gaps in compliance and result in significant fines and penalties.

An Answer to These Challenges – Cloud for Mortgage Servicing

To address the challenges of regulatory compliance, mortgage servicers need a modern servicing system that is able to quickly adapt to regulatory changes and can perform all the necessary work within the core servicing platform.  The system needs to store all the relevant information, including data, documents, and transaction history, to quickly respond to borrower questions and complaints as well as address exams and audits.

SAP Fioneer and Ranieri Solutions are addressing this challenge with our Cloud for Mortgage (C4M) solution, leveraging cloud technology to consolidate the fragmented US mortgage industry and provide servicers, borrowers, and regulators with an intuitive interface to all the necessary data in one place.

SAP Fioneer has successfully deployed enterprise class mortgage solutions across the globe and has now partnered with Ranieri Solutions to develop a best-in-class mortgage solution for the US market.

Cloud for Mortgage offers all the capabilities required for mortgage servicers to remain compliant and it significantly reduces the manual labor required.  Compliance rules and regulations are added and updated in a fraction of the time that older systems require, through configuration rather than coding.  This eliminates the need to build workarounds or create off-board systems which create data silos strewn across the enterprise. All data and supporting documents are housed in the Cloud for Mortgage system and accessible in real-time for servicers. There is also the capability to permission examiners and auditors to self-serve. This reduces the back-and-forth requests for information and files, speeds up the process, and inspires confidence with regulators and agencies that the servicer is responsive to requests and is running and safe and sound operation.

SAP Fioneer and Ranieri Solutions collaborate to service the modern mortgage market

David Officer — SAP Fioneer launched in 2021 out of SAP to drive innovation in financial services. With decades of experience serving the largest global banks in the world, SAP (and now SAP Fioneer) has seen significant change in technologies, platforms and markets. One market that we’ve observed as ripe for innovation is the US mortgage business. The segment is a significant and important part of the US economy, heavily regulated, but with just a few dominant service providers that rely on legacy technologies.

To effectively address this market, we sought local expertise from our partner Ranieri Solutions to help build out the servicing solution of our C4M (Cloud for Mortgage) platform. Combining the capabilities of SAP’s proven platform, SAP Fioneer’s extensive financial services industry expertise, and Ranieri Solutions’ mortgage servicing experience, we are rapidly bringing to market a modern, scalable and reliable platform for a new industry.

Learn more about Cloud for Mortgage

Now more than ever, customers are at the core of any good system design. As Rob described above, a new platform (with new capabilities) enables a new approach to customer engagement that has the potential to change servicer, customer, and regulator relationships. The C4M platform is built to provide ease of use – a great user experience without sacrificing the requirement for compliance, controls, and risk management.

If you’d like to learn more about C4M, please don’t hesitate to reach out to david.officer@sapfioneer.com to discuss your business challenges, organize a demo, or schedule a call.

Find out more about Cloud for Mortgage.

The post Compliance: The “Five C’s” that challenge mortgage servicers appeared first on SAP Fioneer.