Into The Lender's Mind #4 How AI Shapes Lending Decisions

A business is a pure strategy game.

Ten years ago, the fate of your loan rested in the hands of a single credit officer. They’d review your file, weigh the pros and cons, and decide over a cup of coffee.

Fast forward to today: your first reviewer might be a machine.
No coffee. No small talk. No second chances if your data doesn’t make sense.

Artificial intelligence has quietly become the first gatekeeper in lending, scanning, sorting, and scoring applications before a human ever sees them. And while AI brings speed, efficiency, and (mostly) objectivity, it also means borrowers need to think differently about how they present themselves.

How AI is Changing Lending Decisions

1. Instant Scoring – speed with consequences
AI can process thousands of applications in minutes.

• For straightforward loans, decisions can now be made in near real-time.

• But speed cuts both ways, missing documents, inconsistent figures, or unusual patterns can lead to instant rejections with no initial human review.

2. Beyond the Big Three Numbers
Old lending models focused on credit score, assets, and debt.
New AI models go deeper:

• Transaction patterns

• Industry health

• Digital footprint

In short , AI doesn’t just see numbers, it sees the story behind them.

3. Automatic Red Flags
AI is trained to flag anything unusual:

• Sudden jumps or drops in revenue

• Mismatched details between documents

• Frequent changes in directors or shareholders

Without context, these raise risk alerts instantly.

The Human Override – Why Relationships Still Matter

Behind the scenes, there are strong negotiations. First between broker and relationship manager, then between relationship manager and the credit team.

Credit officers intentionally keep professional distance to avoid personal bias.
But professional trust is earned:

• Relationship managers who consistently submit impeccable, well-documented applications gain credibility.

• Brokers who regularly deliver quality files see their names strengthen a credit paper.

A “no” can turn into a “yes” when solid arguments and proof are provided.

Real story – “The Ugly John” story

Years ago, when I joined the commercial division at Lloyds Bank, during my first credit training, I met the most feared credit officer in the company: The Ugly John.

Not his real name and he wasn’t ugly at all. This is how my training colleagues, Relationship Managers who were doing a refresh of the course, were calling him. He was a smartly dressed gentleman in his 40s, razor-sharp, and relentless with credit papers. Nothing got past him without being analysed, discussed, and questioned. Relationship managers who worked with him were truly intimidated.

He wasn’t eating people, but he was eating credit applications.

I never had him as my underwriter, but two lessons from him stuck with me:

1. "If your work is impeccable, nobody will think otherwise."

2. "When you feel you need clarification, go and get it, otherwise others will ask it from you."

Those lessons matter today more than ever, whether your application is reviewed by AI, a credit officer, or both.

How to Work With AI, Not Against It

1. Keep information consistent – Addresses, turnover, and details should match everywhere.

2. Tell your story early – Explain anomalies before they raise questions.

3. Maintain a strong digital reputation – Your online presence matters.

4. Clean your data – Remove outdated or unused accounts.

5. Think like a machine – Clarity and clean formatting win.

Takeaway

AI it’s reshaping the lending landscape and not replacing it.
Think of AI as the strict receptionist to the credit team. If you pass that first gate, the real conversation and professional trust can begin.

Case Study Corner 

A manufacturing business applied for a £250k working capital finance deal. AI instantly flagged them due to a 40% revenue jump in one quarter.
To the algorithm, it looked risky.

In reality? They’d secured a long-term contract with a global client.
After rejection I added a clear explanation. The relationship manager took the case to be reviewed by human eye. A Credit Officer manually re-reviewed the application and approval came in 48 hours.

Lesson: AI sees patterns. Humans understand context. Give both what they need.

Quick Win Tip

Google your business before applying for finance.
If the search results don’t project stability and professionalism, fix them before the lender looks.