My AI Loan Servicing Journey

Moving From Document Chaos to Decision-Making Clarity

Servicing is a Juggling Act

In my last post, I shared how we at Goldersun started learning to “stop worrying and love the robots.” It all began with the daunting task of sorting through thousands of documents for just one loan. AI came to the rescue, giving us a co-pilot that saved time and reduced headaches.But that was just the beginning. Once you get a taste of what AI can do, your mind starts to wander: Where else could these robots help?The truth is, commercial loan servicing isn’t just about storing documents and sending bills. It’s a daily juggling act—compliance deadlines, borrower requests, cash management, reserve tracking, tax and insurance monitoring, reporting for lenders and investors, and sometimes, putting out fires when loans go sideways.

So, in this second chapter of my journey, I want to talk about how AI can help move us from document chaos to decision-making clarity.

The Problem: Data Everywhere, Insights Nowhere

Here’s a simple fact: in commercial loan servicing, the data we need is usually there—but buried in mountains of paper, PDFs, spreadsheets, and emails.

- Loan agreements can be hundreds of pages long.

- Reserve accounts have their own agreements, triggers, and reporting rules.

- Borrower financials and rent rolls arrive in all shapes and sizes.

- Compliance calendars fill up fast with reporting and tax deadlines.

Historically, you’d need a team of analysts poring over documents, entering data by hand, and building custom spreadsheets. And as anyone in this business knows, mistakes slip in. A wrong interest rate, a missed reserve trigger, a late tax payment—that’s all it takes to cause big problems.

This is where the robots shine.

AI as a Document Whisperer

Let’s start with something that’s both simple and profound: AI makes documents talk.

Instead of treating every lease, mortgage, or guarantee as a separate mountain to climb, AI allows us to treat them as part of a searchable ecosystem. Here’s how it plays out in our shop at Goldersun:

1. Document Abstraction: Our AI program pulls out key terms automatically—maturity dates, extension options, debt yield covenants, reserve requirements. That used to take hours, now it takes minutes.

2. Bookmarking to Source: Every data point is tied back to the original document. When I’m asked, “Where did you get that?” I can click and show the exact page and clause.This is invaluable for data QC.

3. Spotting the Oddballs: AI is great at flagging the weird stuff. Non-standard clauses, carve-outs, and custom language jump out of the pile. That saves our legal team time and helps us avoid surprises.

We still trust but verify, but now we spend our time verifying, not hunting.

Compliance: Turning Deadlines into Dashboards

One of the quiet killers in servicing is missed deadlines. Regulatory reports, investor reports, tax deadlines, insurance renewals—it’s a minefield.AI helps us turn that minefield into a manageable dashboard:

- Smart Calendars: AI scans agreements and auto-populates compliance calendars.

- Regulatory Monitoring: Tools monitor for updates and flag what might apply.

- Exception Alerts: If a borrower misses a reporting requirement, we know immediately.

The result? Fewer sleepless nights and fewer “oops” calls to investors.

Borrower & Investor Data: From Spreadsheets to Insights

At Goldersun, a big part of our job is being the middleman between borrowers and investors. Both sides need information, but they want it packaged differently.

AI helps bridge that gap:

- Normalizing Data: AI standardizes borrower submissions, no matter the format.

- Custom Views: Reformatting the same dataset for different investors.

- Predictive Insights: Flagging trends like rising expenses compared to peers.

Instead of drowning in spreadsheets, we’re moving toward true portfolio intelligence.

Cash Management: The Last Frontier (For Now)

We’re not all the way there yet with AI and cash. Handling payments, escrows, reserves, and distributions is too critical to fully automate. But here’s what’s on the horizon:

- Smart Reconciliation: Matching payments against schedules in real time.

- Exception Handling: AI triages issues, staff handle the rest.

- Cash Flow Forecasting: Predicting shortfalls and prepayments.

We’ll get there—but with cash, we’ll always keep human hands in the loop.

Special Servicing: Seeing Trouble Before It Hits

If there’s one area where AI might really shine, it’s special servicing. When loans wobble, speed matters.

- Predictive Default Modeling: Spotting borrowers or property types most at risk.

- Automated Valuations: Scraping comps, analyzing property photos, generating benchmarks.

- Workout Scenarios: Modeling options like extensions, modifications, or foreclosure.

AI gives us early warning and sharper tools when things get tough.

The Human Element: Still the Heart of Servicing

As much as I talk about robots, servicing will never be a machine-only business. Our team’s experience is still the secret sauce. We’ve seen cycles, worked out deals, and know borrower behavior. AI helps us get there faster, but it doesn’t replace judgment, relationships, or negotiations.

If anything, AI frees us to focus more on the human elements.

Lessons Learned So Far

If I had to sum up what we’ve learned on this AI journey, I’d say three things:

1. Start Small, Scale Fast: Begin with one pain point, then expand.

2. Trust, But Verify: Always tie back to source documents.

3. Keep It Human: AI is a co-pilot, not a pilot.

Conclusion: From Chaos to Clarity

When I look back at where we started—drowning in documents, scrambling for deadlines, buried in spreadsheets—it’s clear AI has already changed our business.

We’re not perfect. We’re still learning. But we’re moving from chaos to clarity. From endless hours of paperwork to faster, smarter decision-making.

That’s the heart of this journey.

If you’re in the loan servicing business, or an investor relying on accurate reporting, I’d encourage you to start your own AI journey. The robots aren’t perfect, but they’re already making us better.

Let's Talk

Have you started experimenting with AI in your servicing or asset management work? What’s working for you? What’s not? Drop me a line—I’d love to compare notes and trade lessons from the field.