The 1996 Problem: Why Commercial Lending is Living in the Past

TL;DR: Commercial lenders are operating with technology from 1996. Manual data entry, PDF-based workflows, no API integrations. This isn't laziness—it's market economics. And it creates massive opportunities for vertical SaaS founders who actually understand the industry.

What 1996 Looks Like in 2024

Let me paint you a picture of a typical equipment finance workflow today:

1. Loan application arrives via email with PDFs attached (sometimes scanned, not searchable)
2. Someone manually types borrower info into their loan origination system
3. Credit reports are ordered from a separate portal, downloaded as PDFs, reviewed manually
4. Underwriting uses Excel spreadsheets for debt service coverage ratios and financial analysis
5. Documents are generated from Word templates with mail merge
6. Signatures collected via DocuSign (this is the "modern" part!)
7. Closed loans tracked in another Excel file or basic database
8. Servicing done manually: Payment tracking, payoff calculations, collections—all human-powered

There are approximately 6-8 different systems involved in this workflow, none of which talk to each other. Data is re-entered 3-4 times. PDFs are the primary data format.

Sound inefficient? It is. And it's been this way for 25+ years.

Why Commercial Lending Got Left Behind

1. Fragmented Market = No One Vendor Can Win

The commercial lending industry is massive in total ($1.5 trillion) but incredibly fragmented:

• ~5,000 equipment finance companies in the US
• Most have 10-50 employees
• Top 100 companies control ~60% of market share
• Everyone else is tiny, regional, specialized

This means: Each lender is too small for Salesforce to care about. But the market is too fragmented for a single platform to dominate. So lenders cobble together generic tools (Excel, email, basic CRMs) that weren't built for lending.

2. Complex Workflows That Don't Fit SaaS Templates

Commercial lending isn't like B2B SaaS sales. The workflows are bizarre and specific:

• UCC filings: Every loan requires filing a lien with the state. Each state has different forms and processes.
• Equipment appraisals: Is this excavator worth $80K or $120K? Depends on hours, condition, market demand.
• Day count conventions: Some loans use 30/360, others Actual/365. This matters for interest calculations.
• Prepayment penalties: Can be percentage-based, tiered, declining over time, or yield maintenance calculations.

Generic software can't handle this. You need domain expertise and software development skills. That combination is rare.

3. Legacy Systems Are "Good Enough"

Here's the uncomfortable truth: Excel works.

Yes, it's slow. Yes, it's error-prone. But lenders have been using the same Excel templates for 15 years. They know them. They're comfortable. And switching to new software is risky.

"If it ain't broke, don't fix it" is the dominant mindset—even though it IS broke, just slowly.

4. Regulatory Complexity Creates Risk Aversion

Financial services is heavily regulated. Lenders worry about:

• Data security (GLBA compliance)
• Audit trails (need to prove every calculation)
• Data breaches (borrower info is sensitive)
• Software liability (what if the software makes a mistake?)

This creates extreme caution around adopting new technology. Lenders would rather stick with the devil they know (Excel) than risk compliance issues with new software.

The Cost of Living in 1996

This technological stagnation isn't free. Here's what it costs commercial lenders:

For a typical mid-sized equipment lender ($50M-200M annual originations):

• $150K-300K/year in wasted labor
• $50K-100K/year in error-related losses
• $200K+/year in lost opportunities (deals they couldn't close fast enough)

Total: $400K-$600K/year in inefficiency costs.

And they know this. But switching costs are high, and good alternatives don't exist.

Why Big Tech Won't Solve This

You might wonder: why hasn't Salesforce, ServiceNow, or some well-funded fintech built solutions for this market?

Three reasons:

1. TAM (Total Addressable Market) is too small for them. Salesforce wants $1B+ revenue opportunities. Equipment finance software might be a $100M market—worth pursuing for a startup, irrelevant for a public company.
2. Domain expertise required. You can't build lending software without understanding lending. Big tech doesn't have that knowledge and won't invest to acquire it for a "small" market.
3. Horizontal platforms don't fit vertical workflows. Salesforce is great at generic sales pipelines. It's terrible at UCC filings, day count conventions, and equipment appraisals.

This is the opportunity. The market is too small for big tech, too complex for generic software, and desperate for modern solutions.

The Vertical SaaS Opportunity

Commercial lending's 1996 problem is actually a massive opportunity for vertical SaaS founders who:

1. Understand the industry (have worked in it or have deep access)
2. Can build software (or partner with someone who can)
3. Start narrow (solve one painful problem extremely well)

Examples of winnable niches:

• Payoff calculation automation (this is what I built with PayoffAgent)
• Automated credit decisioning for specific loan types
• Equipment appraisal software using market data + AI
• UCC filing automation (handle state-by-state complexity)
• Lease vs. loan comparison tools for brokers
• Portfolio analytics for lenders managing 1,000+ active loans

Each of these is a $5M-20M annual revenue opportunity for a bootstrapped founder. Small enough to build solo or with a tiny team. Large enough to be life-changing.

How to Win in This Market

1. Pick one painful workflow

Don't try to build a full platform. Find the single most painful 30-60 minute process and make it take 2-3 minutes.

2. Make it 10x better, not 20% better

Lenders won't switch for marginal improvements. You need to deliver dramatic value: 95% time savings, near-zero errors, instant results.

3. Start with one lender as a design partner

Get deep access to one lender's workflow. Build exactly what they need. Then sell to others with the same pain.

4. Charge based on value, not seats

If you save them $26K/year, charge $5K-8K/year. They get a 3x-5x ROI immediately. You build a profitable business.

5. Use AI to do the hard parts

PDF extraction, complex calculations, data validation—this is what AI is excellent at. Use Claude, GPT-4, or similar to handle the cognitive heavy lifting.