Reflections on 25 Years in Loan Servicing

By Balada Reynolds

In some very obvious ways, the role of loan servicers in commercial real estate (CRE) has changed a lot over the past 25 years, moving from a straightforward payment processing role to a complex financial operation. Today we navigate diverse capital structures and manage, the increasing complexity of modern CRE financing and the growing sophistication of investors and sponsors.

?Yet, despite these changes, one thing remains: loan servicing is, and always has been, a people-driven business. The tools we use have changed dramatically – technology and data analytics have transformed workflows, due diligence, risk assessment, and scenario planning – but the core functions of servicing are still based on relationships. Our industry still thrives on trust, expertise, and collaboration, just as it did decades ago. I’m still working with some of the same people that I worked with in the late ’90s today. Together, we have been through all kinds of changes – from mergers and acquisitions to the global financial crisis and the COVID pandemic. Fundamentally, this is a relationship-based industry built on ethics and decision-making.

?However, that decision-making process has evolved. Today, in our tech-savvy world, the information we rely on is backed by powerful analytics that would have been unimaginable 25 years ago. Data is now the backbone of modern servicing – helping us accurately assess risk, monitor loan performance in real time, and address issues before they escalate. Managing risk proactively is now central to servicing, balancing the needs of borrowers, lenders, and credit investors while also focusing on reporting, compliance, and financial structuring. The fast pace of technological innovation in our industry is impressive but looking back reminds us why relationships and human expertise are still at the core of loan servicing.

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Loan servicing over three eras

?A simpler time (Late 1990s to Early 2000s)

Once upon a time, loan servicing was relatively straightforward. Banks directly managed commercial mortgages, and servicers relied heavily on personal relationships and local market knowledge. Standardized practices were rare, and servicing was mostly reactive addressing issues as they arose.

My first ever role in loan servicing was in 1997, on residential mortgages. Back then, temp agencies placed people based on their typing and data entry skills. My first job was inputting payments, entering data, and making sure borrowers’ checks were processed correctly. The most important skill in my role was accuracy with the data entry. That was it. No analysis, just making sure the numbers matched in the system.

The transition to CRE loan servicing in 1998 was an eye-opener. It was much more sophisticated and the terminology alone was overwhelming. But at its core, the job was still about making sure payments were made, taxes were covered, and insurance was in place. The biggest difference was how rigid everything was. We worked in siloed teams, each responsible for a specific function—such as payments, taxes, or insurance. We followed a pre-defined servicing agreement like a checklist. There were no analytics and little flexibility.

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Financial crisis and the aftermath (Mid-2000s)

The global financial crisis (GFC) was a turning point for our industry.. It exposed inefficiencies and forced a fundamental shift in how risk is managed. The surge in mortgage defaults and foreclosures overwhelmed loan servicers and exposed significant weaknesses in risk management and borrower communication. We didn’t have the datasets we have today, real-time information wasn’t easily available. It was all paper, pencils, and digging through physical documents. If you needed answers, you had to find someone with experience and ask.

Stricter regulations followed, bringing more transparency, stronger borrower protections, and better risk management practices. The lack of real-time data made restructuring slow and uncertain.?If today’s technology had existed back then – artificial intelligence (AI), predictive analytics, cloud-based workflow management platforms – workouts would have been faster, and decision-making even more accurate. It would have brought parties together sooner, reduced uncertainty, and allowed for better results. Back then, it took weeks to gather numbers from different paper documents to assess default risk and cash flows analysis.

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Rising complexity in loan structures (Late 2010s to Present)

In the years since the GFC, everyone involved, transactions and counterparties have become more sophisticated, influenced by lessons from the downturn and the rise of technology. We have become familiar with a much wider range of transactions, including bridge and mezzanine loans, syndications, and loan-on-loan structures. These transactions brought new complexities, requiring us to work together across departments to improve processes. One example is the speed at which we can move money today. Treasury management systems are automated, payments are processed in real time; what used to take days and sometimes longer now happens in an instant.

The biggest improvement is data.? We no longer have to search through documents or rely on experienced colleagues (although we still benefit from their expertise) – real-time analytics provide a precise foundation for decision-making. AI can analyze thousands of data points in seconds, and predictive models help us identify and address potential problems before they arise.

In the past, servicers would step in when a loan defaulted or a borrower fell behind on payments. Today, proactive risk management is immensely important to loan servicing. Much like our demand for real-time data, our clients also expect real-time transparency across the transaction’s lifecycle and events. From credit administration to restructuring, workouts negotiations, foreclosure or even liquidation, we as servicers are now positioned to provide deeper insights, faster responses, and greater flexibility.

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The role of technology

AI and machine learning are no longer just efficiency tools; they have fundamentally changed decision-making in loan servicing.?Predictive analytics allows us to assess borrower risks with greater precision, providing deeper insights into market conditions and enabling proactive approaches to the upcoming USD 1.3 trillion maturity wall. These technologies allow us to significantly upgrade analytics, scenario stress testing and investor reporting, enhancing operational efficiency across the board. Digital platforms also serve as all-in-one operating systems, centralizing loan management operations. Additionally, predictive analytics help identify potential defaults before they happen and assess the success outcomes of competing strategies.

Moreover, blockchain technology is also emerging as a transformative innovation, enabling secure, transparent, and fraud-resistant transactions. It can streamline payment processing and escrow management through smart contracts, reducing delays and operational risks.

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Harnessing the power of people and technology

With AI and machine learning advancing so quickly, there’s an open question about what the next five years will bring. The rapid pace of technological advancement presents many opportunities and we are actively integrating these advanced tools with the experience of our team. By using AI and data analytics, we can provide insights and proactive risk management. While technology enhances our capabilities, the judgement and expertise of our team remains indispensable.

As technology advances, Trimont continues to use and develop cutting-edge tools in combination with the deep expertise of our experienced team to navigate the industry. By using advanced data analytics and AI, we offer precise, real-time insights and proactive risk management. We recognize that while technology enhances our capabilities, it is the expertise and judgment of our team that is crucial. Each evolution over the last 25 years has taught me a skill that I use today and I'm excited to see what skills await me in the next chapter of servicing.

If you have questions about navigating the current CRE landscape, contact us at [email protected].

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