AI: The next generation for commercial lending

Lending is evolving at an unprecedented rate. In fact, we could compare the present lending era to the industrial revolution. And the main catalyst? A combination of commercial lending automation and intelligence, driven by Artificial Intelligence (AI) technology.

AI is an exceptional innovation and the changes it has wrought throughout society, the economy and finance have already been profound. But these changes, coupled with the ascendancy of lending AI, have concurrently birthed a wealth of new lending opportunities.

This technology bears massive implications for all. It will change how customers interact with lenders, the products those lenders offer and the way the lenders in question function. Yet, despite the profound potential of AI, many businesses aren’t actually ready to fully embrace it. Not because they’re unreceptive to the tech. But because, on an organizational level, they’re bound to legacy infrastructure and processes that automation is increasingly rendering obsolete.

Transformative technology works best when the industries adopting it are actually willing to undergo a metamorphosis and question the fundamentals of their management, operations and infrastructure. Thus, commercial lenders must ask themselves: “What does an ideal lending platform look like in an AI era and how could I transform my operation longer-term?”

In this post, we’ll answer this question, discuss what AI can actually help proactive commercial lenders do and reveal why SAP Fioneer’s Commercial Lending platform is the best tool on the market to achieve this. Read on for more.

The evolution of the lending industry

In the last two decades, the lending industry has been impacted by much turbulence. This instability stemmed from worldwide events, such as the GFC, the global pandemic and international conflicts. Naturally, these all provoked economic shocks, such as interest-rate rises and supply chain disruption. Amidst this often-chaotic environment, banks focused on balance sheet strength, tightening their lending criteria.

But because these banks were being more cautious, a gap in the market arose. This gap was quickly filled by smaller, more agile fintech companies. These fintech lenders harnessed newly-available API technology. This technology gave borrowers access to fast credit decisions and allowed these alternate lenders to operate with reduced on-site operations and cost. In essence, borrowers have embraced these new options and increasingly opted for the improved customer experience over loyalty to traditional lenders.

Banks have since reacted to this challenge with large-scale digital transformations, embracing API technology at their heart. This investment has begun to level the playing field, but has been focused largely on new loan onboarding — through loan origination — rather than the overall lending ecosystem. Here, large operational teams who manually maintain loan contracts and data on fragmented and monolithic technology, remain commonplace.

But in the age of AI, Banks and lenders must embrace API technology throughout the lending ecosystem as the foundation upon which they can build their AI structures. Otherwise, they run the risk of being left behind.

How AI has changed the game

Today’s lending infrastructure is still largely dependent on manual operation and all the human error that entails. It is reactive by nature. The forecasting, insights and intelligent decision-making capabilities of AI means that its adopters can always stay ahead of their legacy-tech-dependent competitors.

Picture the disparity between a legacy lending environment and one powered by AI as an imaginary boxing match. The legacy enterprise is like a heavyweight with the fastest reaction times in the world. But the AI enterprise is a reigning champ who is a master at guessing his opponent’s punches. No matter how fast the heavyweight’s reaction time — how quick he can duck and dodge — he will always lose in a fight against someone who can find patterns in the opposition’s fighting style, accurately estimate where punches will land before they strike and move before they happen.

By the same token, an AI-powered lender who can anticipate where the market is heading based on data-driven probability will always outpace lenders who merely react to changes after they occur. And the more this technology gap widens, the harder it becomes to close. Thus, AI-ready systems have become imperative for lenders.

But AI doesn’t magically fix bad lending systems; it amplifies whatever is already there. Robust, modular platforms gain leverage, while legacy-centric ones are exposed. With that in mind, we need to consider what, exactly, AI can achieve for commercial lenders.

What AI enables

We’ve seen a massive investment from the financial industry into AI technology. Per Statista, the financial services industry has invested an estimated $35 billion in AI. This investment is expected to generate substantial returns, with AI contributing $2 trillion to the global economy.

But where, exactly, are these huge returns coming from? To date, much of this investment has been focused on the deployment of Generative-AI and agentic AI that reacts to user input and provides output based on available data.

Now, this valuable effort is improving operational understanding and efficiency. However, the actual impact is often limited to specific use-cases within specific functions of the lending lifecycle.

Broader, more fundamental impacts require a fundamental examination and application of AI across the lending enterprise as its evolution increases its pace. But the adoption of specialized agentic AI across the lifecycle can amplify benefits and ROI across the organization. A few examples of how agentic AI can be integrated include:

• Onboarding agents: These receive documents, extract data, validate against requirements and proactively request missing information from the borrower
• Underwriting agents: These AIs aggregate financial data, check covenants, build risk profiles and deliver a structured decision package to the underwriter
• Portfolio monitoring agents: These continuously monitor the loan book, react to events (rating changes, missed payments, market shifts), run analyses autonomously and surface actionable recommendations
• Collections/workout agents: These AI detect payment delays, calculate restructuring scenarios and present options to the workout team before manual intervention is even needed

Critically, Agentic AI now provides the opportunity to deliver autonomous management of complex tasks such as real-time risk assessment, compliance automation and execution of transactions.

Agentic AI has the potential to completely alter today’s lending environment. Lenders can focus their teams on more value-added efforts, rather than low-value, manual entry. AI allows lenders to move away from batch processing. Instead, they can embrace pro-active decision-making, with trigger-based actions throughout the lifecycle: starting from onboarding, through to underwriting, servicing and collections. As such, AI provides an opportunity to elevate the role of the lender, instead of replacing them.

But all these benefits aren’t instantly achievable for all organizations. Indeed, AI must be introduced to a system built on a data-rich foundation and an API-driven infrastructure. Particularly important for proactive, autonomous AI capabilities, this foundation must also be able to support event streaming. This refers to the continuous flow of events — such as rating changes, missed payments, or covenant breaches — being streamed in real-time across the system, enabling AI to instantly detect and act on them without human prompting.

Key attributes of an AI-ready system

So, what are the key attributes of an AI-ready lending infrastructure?

Firstly, it must be built with the long-term in mind and embedded into the entire lending ecosystem at the foundational level, along with the built-in flexibility to recognize ever-evolving business imperatives. Lenders must avoid investing in technology which locks them into achieving a single use-case amidst today’s constraints. Thus, a modular and adaptable solution, which can be modified to absorb data sources, regulations and new products as the business diversifies, is paramount.

Furthermore, it must be interoperable. Platforms operating in isolation are outpaced by those that can plug into existing core systems, third-party data providers and partner’s platforms.

Next, the system must be intuitive. Previously, specialists with plenty of experience had to navigate incredibly clunky systems to enter data and drive lending. If AI overhauls enterprises, human workers will have more freedom and time to concentrate on higher order responsibilities, rather than tedious manual tasks. This requires a cultural shift, with plenty of support for resources who may feel threatened.

The system must also be flexible enough to support diverse products, customer segments and risk strategies; while also functional enough to run multiple strategies, markets, or business models in one place and intuitive enough for quick onboarding. Lastly, the system needs to be frictionless and transparent. Visible, structured data is needed for clear audit trails, transparent decisions and the automation of manual steps.

If a commercial lender wants all these use cases, they have to either already have an AI-ready platform, or work on building one. Many institutions still try to build everything themselves. But there’s often a gap between ambition and reality, due to lack of budget, knowledge and the necessary specialized capabilities required.

But not all platforms are created equal and choosing the right one is critical if you want to get the most out of automation.

How SAP Fioneer bridges the gap

So, what makes our product offering so different? Well, SAP Fioneer’s commercial lending solutions have been built by people with decades of expertise in technology and finance, who understand the struggles faced by traditional banks and newer lenders alike. Getting the most out of AI depends on a strong API-first, native event-streaming foundation and this is exactly what SAP Fioneer’s platform can provide. Aided by our dedicated lending AI teams, we’re building the lending journeys of the future, right now, with full Agentic AI capability.

Because of our unique philosophy of design and engineering, our lending solution boasts these unique traits:

1. Longevity by design: Our platform is built for constant change in regulations, products and tech
2. Deep integration: Pre-built connectors and event-driven architecture provide seamless ecosystem participation
3. Embedded intelligence: Agentic AI is baked into the platform to power automation and intelligence
4. Usability: Designed for non-technical users to configure, test and deploy new propositions quickly
5. Diversity: The platform supports the entire lending lifecycle, from origination to loan management and for all lending domains, simple to complex
6. Frictionless adoption: Our implementation and migration approach significantly reduces risk and time-to-value
7. Openness to complexity: Our system is capable of running highly complex lending scenarios and intricate borrowing journeys

Because of this, our modular platform allows commercial lenders to quickly and easily get the most out of cutting-edge AI tools, while simultaneously scaling their organization and infrastructure at a pace that suits them.

Conclusion

Lenders can no longer design for “yesterday’s world.” They must be forward-thinking and architect for today’s and tomorrow’s realities. This may seem intimidating, but the good news is that this revolutionary tech has leveled the playing field. Smaller and mid-sized lenders can now access capabilities that were once the preserve of the largest institutions, while traditional banks and lenders are getting to grips with AI at the same pace of these fintech enterprises.

However, the cost, complexity and expertise needed to get a system AI ready and then integrate automation into an organization successfully, can still remain a daunting task. This is why working with experienced technology partners with a wealth of specialized knowledge of lending is key.

So, if you’d like to learn more, then please get in touch with one of our commercial lending experts and book a demo here.