The spreadsheet trap: Why investor reporting still operates like it’s 2005

[ad_1] Manually updating spreadsheets. Coping with paper jams within the printer. Bear in mind what workplace life was like in 2005? If you happen to’re feeling nostalgic, yow will discover most of the identical practices nonetheless in place within the investor’s reporting places of work of mortgage servicers at the moment.

However why haven’t these places of work developed with altering expertise?

It’s partly cultural, however it additionally displays how the trade has developed over time. A lot of our methods have been by no means designed with knowledge transparency or real-time automation in thoughts – some servicing platforms even predate the invention of Excel.

After I began within the mortgage trade within the Nineties, knowledge administration remained largely guide – we have been nonetheless utilizing paper ledgers and fundamental spreadsheets. Excel started gaining traction as corporations transitioned from DOS-based to Home windows-based methods. On the time, it was revolutionary, giving us much more functionality and suppleness than we’d ever had earlier than.

That revolution modified how individuals labored. Over time, almost each division discovered how one can enhance their processes, construct automation, and shortly clear up issues utilizing Excel. These practices turned a pure method of working and ultimately became a part of the very tradition of investor reporting.

Quick ahead 15 to twenty years, and most of the identical individuals who relied on these strategies are actually trade leaders who’ve handed that information and mindset to the following technology, making certain that spreadsheets stay embedded in our operational DNA.

The consolation of visibility and the price of overreliance

There’s additionally a component of belief in play. Folks really feel extra comfy with what they'll see and confirm, even when it’s inefficient. A spreadsheet, in spite of everything, provides customers full visibility into their knowledge.

However that transparency may be misleading. We’ve all seen how a small method error affecting only a fraction of a % can turn into a pricey downside when utilized to hundreds of rows of knowledge. Some spreadsheets have turn into so complicated that, despite the fact that you possibly can technically hint every method, they exceed our capacity to actually perceive them.

The problem helps organizations acknowledge that automation doesn’t imply shedding management. It means transferring management, shifting from guide processes with restricted knowledge integrity and functionality to methods that guarantee accuracy, visibility, and ease. True automation doesn’t obscure the information; it clarifies it, releasing groups to concentrate on what actually issues.

Whereas Excel nonetheless supplies some stage of scalability, it solely scratches the floor of what’s attainable with fashionable, managed methods.

Why outdated workflows persist

So, what retains these legacy workflows alive? In my expertise, the largest culprits are knowledge fragmentation, restricted system interoperability, and dispersed methods of report.

Servicing knowledge lives throughout a number of platforms – core servicing, accounting, money administration, investor knowledge, and client-specific reporting templates – however these methods don’t talk cleanly, or typically even in any respect. Even when expertise distributors promise automation, their options can usually sit on high of inconsistent knowledge. Consequently, groups nonetheless find yourself manually reconciling the outcomes.

There’s additionally an comprehensible resistance to danger. In investor reporting, even a small error can have regulatory or reputational penalties. Many organizations select certainty over effectivity, at the very least till they see that fashionable automation can ship each.

After which there’s a price. Excel is inexpensive, and most servicers don’t acknowledge the hidden value of poor high quality in investor reporting. Many servicers nonetheless view investor reporting as a purely exterior obligation – a compliance deliverable, not a strategic asset. However that mindset overlooks a serious alternative.

By harnessing the ability of all the information collected via investor reporting, servicers can uncover precious insights to enhance upstream and downstream operations, from loss mitigation and foreclosures to money administration and mortgage boarding. The ROI turns into clear when organizations view investor reporting as an inside catalyst for enchancment, not simply an exterior requirement.

Utilizing AI to exchange guide processes

Servicers can make use of knowledgeable methods enhanced by AI that ingest and analyze lots of of stories from the servicing platform, investor information, and different associated knowledge sources in parallel. These methods use complete reconciliation, triangulation, and knowledge validation to detect even the smallest anomalies, successfully flagging points that always go unnoticed or require vital guide rework when recognized by conventional processes.

In contrast to instruments that automate solely surface-level duties, these new knowledgeable methods which can be enhanced by AI use superior, rules-based decisioning to routinely resolve almost 80% of exceptions and edits. Reporting analysts can due to this fact shift their focus to extra complicated or high-value analysis, understanding that the information stays clear, dependable, and aligned throughout methods. AI pushed insights counsel potential analysis paths primarily based on the patterns they’ve detected. This steering not solely will increase effectivity but additionally results in extra constant and correct conclusions.

High quality outcomes require high quality knowledge

Excessive-quality automation begins with high-quality knowledge. Too usually, organizations spend money on new methods with out addressing underlying knowledge points. And that’s the place breakdowns happen.

Automated platforms ought to strengthen, not substitute, human oversight. A well-designed system helps establish and resolve inconsistencies by triangulating info throughout a number of knowledge sources. Whereas that provides some preliminary effort, it creates a essential suggestions loop: operational groups can pinpoint and proper knowledge points or enhance processes on the supply, driving larger effectivity and accuracy over time.

Because the underlying knowledge turns into extra dependable, automation delivers even higher outcomes. Cleaner knowledge produces clearer suggestions, and clearer suggestions additional improves knowledge high quality, making a constructive cycle that compounds over time.

This ripple impact goes effectively past investor reporting. Servicers can leverage such suggestions to drive operational excellence throughout the broader group. As knowledge integrity improves, the complete servicing operation advantages.

How automated methods can earn belief

Finally, automation succeeds or fails on one issue: belief.

As soon as knowledge is constant and validated, organizations can extra confidently introduce automation. Whereas a system can technically function on unhealthy knowledge, belief in its outputs will erode shortly when the outcomes aren’t dependable.

Belief is earned via transparency, traceability, and efficiency. Groups want clear visibility into the information used, each processing step taken, and the reasoning behind every end result. Over time, constant effectivity features, auditability, and alignment with person judgment reinforce confidence – making automation not simply accepted however relied upon.

Modernization isn’t about abandoning the instruments that obtained us right here; it’s about evolving how we use them. Spreadsheets gave this trade its first style of digital empowerment. However the identical belief and visibility that made Excel revolutionary have additionally made it tough to maneuver away from.

As we enter a brand new period of clever automation, the mindset shift is already underway. Automation isn’t about taking management from individuals. It’s about giving them higher instruments. Instruments that guarantee accuracy, enhance oversight, and free them to concentrate on higher-value work.

After we can see automation as an extension of our experience moderately than a menace to it, that’s when actual progress begins. By eliminating spreadsheet-based exception administration and lowering reliance on end-user computing instruments, knowledgeable methods turn into foundational options, strengthening present workflows whereas positioning organizations for extra superior AI adoption sooner or later.

Jeff Choi is the COO at PMSI.This column doesn't essentially replicate the opinion of HousingWire’s editorial division and its house owners. To contact the editor liable for this piece: [email protected] .