2. Behind the Scenes: How We See Risk Differently

Most credit decision systems in the market—even those built for mature financial ecosystems—treat risk as a static number. A bureau score comes in, and the system bins applicants into “approve” or “reject.” That’s where we diverge.

Our EAD/LGD framework doesn’t just assess if someone is likely to repay; it calculates how much exposure, or loss might occur if they don’t. EAD (Exposure at Default) tells us what’s truly at stake in riyals, while LGD (Loss Given Default) models how much of that would actually be lost after recovery. This transforms risk scoring from a one-dimensional approval filter into a multi-dimensional decision tool.

Global Intelligence, Locally Tuned

Our models aren’t hypothetical—they’ve been trained on $50B+ in real-world lending decisions across SME finance, POS lending, personal loans, micro-lending, and alternative credit products.

But global success means little without local precision. That’s why we’ve retrained these models with over a decade of Saudi credit history and billions of SAR in lending data—capturing repayment patterns unique to the Kingdom.

This dual training—global breadth plus local depth—means our models can anticipate repayment behavior across every segment, from salary-backed loans in Riyadh to Tawarruq in smaller cities.

Why We Handle Messy Data Others Can’t

In many real-world cases, your applicant data isn’t perfect—it’s incomplete, inconsistent, or formatted differently for each source. That’s where most risk systems stall.

Because we’ve deployed in messy, incomplete data environments worldwide, we can clean, structure, and extract high-value insights in days, not months. While others are still “preparing” their data, we’re already simulating approvals, recoveries, and fallback offers for your market.

The Outcome: Clarity and Confidence

With SoyakaAI, risk is no longer a black box. Your team sees why an applicant’s score looks the way it does, what the projected exposure is, and how to maximize safe approvals without increasing losses.

In other words: we don’t just score—we illuminate.

Coming Next:

3. Mapping the Opportunity (RiskInsights™)

we’ll put your portfolio under our lens to reveal the 60% medium-risk majority, underutilized high-income segments, and SIMAH misses, so you can see where safe approvals are hiding.