Beyond Origination: The Missing Link in Modern Lending

Introduction

Modern commercial lending lifecycle management depends on balancing two demands: the speed and also the strategy underpinning the lending process – something which can vary according to the size and complexity of the loan in question.

Every reputable lender knows that, from the start of the loan approval all the way to the closing stage, there are always diversions and delays in the course of the lending journey. The story of a loan is rarely a straightforward one and a range of factors (like the lender and borrower’s financial situation, collateral value, risk assessment and conditions) can all shift during the course of a loan approval and, naturally, after it has been approved. And all these issues can become even more tumultuous the more complex each loan is.

These changing factors can all influence the end revenue of commercial lenders. The only way for them to overcome this is by making careful and considered strategic business decisions to achieve the most-favorable outcomes with each loan granted and until the point it reaches maturity. This is the mission behind the management of the lending lifecycle, but sadly these considerations can stall the process of the loan itself.

That’s because overcoming the many changing circumstances that usually affect a loan and thereby achieving better lending outcomes, depends upon more than speed. Instead, all relevant departments within the organization need to gain full visibility into the process of the loan; keeping the ongoing narrative of the lifecycle intact through an unbroken chain of continuity driven by business intelligence. Without that continuity and context, the lending process will inevitably falter.

With all that in mind, this article will explore the biggest roadblocks in more complex lending journeys and how SAP Fioneer’s innovative new lending lifecycle management solution can help.

Key obstacles in the lending journey

Successfully completing a loan and managing the ongoing borrower-lender relationship, means leveraging business intelligence, economic data and in-depth research into borrowers, to make tactical lending decisions.

Unfortunately, a number of obstacles typically tend to crop up in the course of the lending process, which can both obscure business intelligence and delay operations. And all these issues are more likely to crop up in complex, large-scale, or atypical loans. These include:

1. Market uncertainty:

Economic fluctuations like shifting interest rates, taxation and the financial stability of the borrower can all increase the risk of loan defaults. Lenders are typically forced to consider all of these changing factors during the loan application, which can draw out the process. However, the analysis doesn’t end there. Today, constant monitoring is the reality for most commercial lenders.

2. Increased risk scrutiny:

Commercial lenders are also usually forced to analyze a range of variable factors, such as industry trends, the viability and collateral valuation, before finalizing a loan. With traditional lenders spending more and more time analyzing financial records, rather than executing quick decisions, more agile competitors (like online fintech companies) can grant loans to eager and time-poor customers far faster. The stricter criteria affordability stress tests also affect the number of loans lenders can offer, leading to traditional lenders losing more potential borrower acquisition opportunities to newer upstarts.

3. Rising costs:

Unstable interest rates, the rising cost of capital, increasing wages and the escalating cost of tech are all increasing revenue drains on lenders. As a result, financial organizations now have to do more work with less money and resources. This draws out the lending process and shrinks profits.

4. Data fragmentation:

Approving and completing a loan depends upon a wealth of aforementioned financial data. However, this data tends to be siloed across numerous different third-party organizations and variable external systems. Also, many of these systems are not designed with interconnectivity in mind. This means lenders could potentially overlook or lose crucial business intelligence and make sub-optimal loan decisions as a result.

5. AI and Automation:

Many lending organizations have attempted to integrate new AI tools into their workflow to automate the process and boost operational efficiency. However, due to the unstructured data, many lenders cannot harness AI effectively and are not reaping the benefits of automation or the insights needed to make more effective lending choices.

How to improve lending lifecycle management

Although modern loan origination has improved the overall speed and efficiency of very simple loans, these gains are largely limited to standard lending scenarios. When things are more complicated, balancing speed and decision-making becomes harder.

Lenders need to understand the full picture before making confident and informed decisions on the above issues; since the best outcomes depend on strong business intelligence and data visibility. They need an infrastructure that can support the loan lifecycle end-to-end (from initiation to processing to repayment/exit), while also merging seamlessly with their existing system.

But all of this means that lenders need an infrastructure that supports high-speed processing, informed decision-making, the agility to respond to changing circumstances and the transparency required to keep all stakeholders informed of a loan’s status.

Furthermore, this same system needs to ensure lenders can provide positive, supportive long-term credit relationships with borrowers after deal approval. And lenders must also focus on staying fully compliant and up-to-date with all lending regulations at the same time.

How can SAP Fioneer’s Credit Workplace help?

Credit Workplace is our integrated end-to-end platform, designed to holistically organize, analyze and centralize deal, asset/business partner data in one easy-to-navigate, transparent hub.

This solution supports underwriting, portfolio and risk management, through a combination of structured deal data, integrated processes and intuitive collaboration tools. It also boasts business intelligence embedded directly into the workflow; with flexible deployment options for cloud native and sovereign European cloud environments.

Credit Workplace also provides its own AI Agent to help users. It leverages Retrieval-Augmented Generation (RAG) to deliver real-time, domain-specific guidance that seamlessly combines product knowledge, customer-specific configurations and proprietary documentation directly within CWP.

SAP Fioneer’s Credit Workplace is the ideal answer for any lender looking to gain full visibility of every loan lifecycle. For example, in this case study, you can learn how a leading European specialist bank leveraged Credit Workplace to achieve an efficiency increase of approximately 20% over the entire loan process.

Would you like to learn more? Get in touch with one of our commercial lending experts or book a demo here.