1-The Revenue You’re Leaving on the Table

📊 Example Client Impact

💡 With Soyaka AI, this Saudi client unlocked over SAR 100M in new lending opportunities — from the same applicant base

A Day in the Life of a Lender

It’s 4:00 p.m. and you’re still waiting for risk to clear that file. The applicant’s been in manual review since yesterday. You know they’re a strong candidate — salary in place, good payment history — but your process can’t move faster than your tools.

By the time you get the green light, the customer may have already gone to a competitor who gave them an instant answer.

The Hidden Leak in Your Revenue

This isn’t just about one file. Multiply that delay across every case stuck in manual review, every applicant rejected by a static SIMAH score, every opportunity that slips away.

Lost approvals aren’t just lost deals — they’re months of recurring interest, repayment revenue, and cross-sell potential disappearing from your balance sheet.

Why SIMAH Isn’t the Whole Story

SIMAH plays an important role, but it’s designed for a broad market, not for your exact portfolio, product rules, and customer patterns. It can’t account for the nuance in your data — income class differences, POS behavior, regional repayment patterns, or industry-specific risk signals.

When SIMAH says “reject,” the real question is: could you still safely approve something smaller, shorter-term, or backed? Right now, that answer is invisible.

Manual Review: The Productivity Sinkhole

Manual review teams are expensive and slow. And they’re only as good as the data in front of them. The longer a file sits on their desk, the higher the chance of applicant drop-off — especially in today’s lending environment where “instant” is the norm.

It’s not that your team isn’t good. It’s that they’re being asked to win a race while dragging a dead weight of outdated tools behind them.

The Competitive Gap

Fintechs, neobanks, and even traditional lenders in other markets have shifted to real-time decisioning engines that can match offers in seconds — not days.

In Saudi Arabia, this speed advantage is still rare. That means there’s a gap you can exploit — if you have the right decisioning infrastructure in place.

The Risk You Don’t See

Approvals aren’t just about saying “yes” or “no.” They’re about controlling the type of “yes.” Without dynamic scoring that adapts to your portfolio, you risk approving customers who won’t pay — or rejecting customers who would have been perfect.

Both cost you money: one through defaults, the other through missed profit.

The Point of No Return

Every time an applicant leaves without an offer, they take their potential lifetime value to someone else. And once they’re gone, you don’t just lose one loan — you lose every product they could have taken from you in the next five years.

This is why lenders who fix their decisioning gap see an immediate and disproportionate jump in revenue.

The Big Question

So, what if you could:

• Approve more of the right customers instantly?

• See exactly where risk hides in your portfolio?

• Recover safe approvals that SIMAH and static rules are missing?

• Do it without hiring more analysts or waiting months for integration?

You’d stop leaking revenue, start winning deals your competitors miss, and finally give your customers the instant, confident answer they expect.

Coming Next:

2. Behind the Scenes: How We See Risk Differently

In the next article, we’ll lift the hood on how we see risk differently — and why that difference translates directly into revenue, faster approvals, and safer lending decisions.