My Ai Loan Servicing Journey
- joebeggins
- Sep 3
- 4 min read
Updated: Sep 8
Commercial Loan Servicing is Hard
The other day, we took over servicing for a loan our client had purchased from another lender. The loan had a maturity default—which, sadly, is pretty common these days. It was in cash management, so there was a tenant collection lockbox and a dedicated cash management account. On top of that, there were numerous reserve accounts, each segregated. Again, not unusual.
Our client financed the purchase with a loan-on-loan lender. That means we service the existing loan until our client forecloses, takes title to the real estate, and we also handle payments to the loan-on-loan lender in the meantime.
Before we even started servicing, we had to gather 1,030 documents. Sure, you’ve got the big ones—the Loan Agreement and the Cash Management Agreement—but hundreds of others contain nuggets of information we need to set up and service the loan properly. That’s 1,030 documents and counting for one loan.
Now imagine that the largest servicers in our industry might manage 50,000 loans. Yeah—this is hard work.
How Do You Digest 1,000+ Documents?
One of our clients recommended a program that helps read and synthesize data from mountains of documents. With it, we load everything into the system and let the “robots” scan the stack for answers.
Suddenly, this impossible job became manageable. I started to really like these robots.
Like many folks, I’d dabbled in AI tools—ChatGPT, Gemini, you name it. What AI can do is not only mind-blowing, it’s a little creepy too. Just look at the photo at the top of this article. I was riffing on Dr. Strangelove and asked ChatGPT to create that image. The result? Eerie, dark, and full of undertones about the existential risks AI might pose. But hey—I didn’t have to read 1,000 documents. That felt like a pretty good trade-off.
So maybe this is a love/hate relationship with the robots.
You Be the Judge
If I hand you a 100-page loan agreement and a promissory note, can you determine the loan’s interest rate in under 10 minutes with traditional tools? If you’ve read your share of loan docs, you know the struggle.
With the robots, though, we can search all documents simultaneously and pull the answer in seconds. Not only that—they cite multiple sources and bookmark the original docs so we can check their work.
In loan servicing, we’re required to abstract hundreds of data fields from documents. The robots give us the gift of time. And you’ve got to love anything that gives you that kind of gift.
Where We’re Loving the Robots
Here are just a few areas where AI is already making our lives easier:
1. Automating Loan Setup: Document Abstraction & Data EntryLoan documents—mortgages, notes, leases, guarantees—are long, dense, and complex. Extracting the critical data has always been labor-intensive and expensive, requiring highly skilled staff. Now the robots can:
Identify key clauses automatically.
Populate servicing systems with accurate data.
Flag unusual or non-standard language for review.
And best of all? They give us bookmarks to the original sources so we can double-check their work. As Ronald Reagan said: “Trust, but verify.”
2. Integration with Legacy Servicing PlatformsOur industry runs on legacy systems that are expensive and disruptive to replace. AI offers a bridge:
APIs and middleware that sit on top of existing systems.
Robotic process automation (RPA) to mimic keystrokes and move data.
Cloud-based overlays that add dashboards, reports, and predictive analytics.
This layered approach lets us modernize at a fraction of the cost.
3. Automating Core Loan AdministrationAt the heart of servicing is cash flow—collecting borrower payments, allocating funds, disbursing to investors. Traditionally, this requires armies of analysts. We’re still cautious about letting robots handle cash, but AI could eventually:
Reconcile payments automatically.
Triage exceptions in real time.
Forecast cash flow disruptions.
When it comes to cash, we may never stop worrying completely—but the possibilities are exciting.
Looking Ahead: The Future of AI in Loan Servicing
We’re only scratching the surface. Some of our peers are further along, but as the technology matures, we see AI reshaping even more of our work:
Compliance & Risk Management
Monitoring regulatory changes.
Flagging anomalies before they become violations.
Detecting fraud through pattern recognition.
Borrower & Investor Communications
Chatbots answering routine questions.
Personalized investor reporting.
Faster, more tailored communication.
Special Servicing & Asset Management
Predictive models flagging early defaults.
AI-powered valuations and market comps.
Scenario analysis to evaluate workout options.
Portfolio Management
Forecasting delinquencies and prepayments.
Stress-testing portfolios against market changes.
Giving managers a portfolio-wide lens, not just a loan-by-loan view.
The Human Factor
AI is powerful, but it’s not a replacement for human expertise. Loan servicing depends on judgment, relationships, and negotiation—especially in distress.
AI’s role is to augment us, not replace us. Analysts can spend less time on data entry and more on problem-solving. Asset managers can blend predictive models with local market knowledge. Compliance teams can focus on interpreting rules rather than chasing missing data.
Think of AI as a co-pilot. That’s where the real magic is.
Conclusion
Commercial loan servicing sits at the center of real estate finance. As portfolios grow more complex and investors demand greater transparency, we have no choice but to embrace technologies that improve accuracy and efficiency.
Artificial intelligence isn’t just a buzzword—it’s already reshaping payment processing, compliance, risk management, investor relations, and asset workouts. The question isn’t whether to use it, but how fast and how far.
For me, the answer is clear: it’s time to stop worrying and love the robots.
Would love to hear about your own AI journey. Drop me a line—I’d be glad to compare notes.
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