Soyaka AI™ | Full Tech Demo: Inside Our Credit Risk Engine

📌 Editor’s Note:

This page is designed as a reference library for those who want to go beyond the highlights. It contains our full technical demo — covering how Soyaka AI models assess risk, explain every decision, digitize existing rules, and go live fast in regulated markets.

1 - How does your AI actually assess risk? What’s going on under the hood?

Inside the Console, we have a library of AI models that function like hiring the top risk experts in the world — only they work for you full-time, they never leave, and you retain the intellectual property. These models cover various lending scenarios including microfinance, crowdfunding, POS financing, and even auto insurance. Since 2018, we’ve been building and refining these risk models tailored for different lending needs.

Now, imagine hiring the best risk expert in the world — they bring decades of experience and proprietary methods, but when they leave, their expertise leaves with them. With our AI models, that IP stays with you. These models replicate expert-level thinking and decision-making, including analyzing metrics like accuracy, KS score, and area under the curve (AUC). These are not generic models — they’re built specifically for financial risk, using real market data.

2 - How accurate is this model, really? Can you trust it with real decisions?

Accuracy in credit risk is critical. It’s about minimizing two mistakes: giving loans to people who won’t repay, or rejecting those who would. If a model is 95% accurate, it means 95 out of 100 loan decisions are correct. Our AI models are trained to meet these high standards, with performance continuously measured by domain-specific KPIs.

Unlike traditional models that are static, ours are dynamic. We use a “champion-challenger” system where new models continually test and outperform existing ones. You can track how each model evolves, how each decision is made, and even drill down into performance by applicant or product. This is a level of transparency and adaptability that traditional models just don’t offer.

3 - Can I see & understand how the AI made the decision? Is it a Black Box?

Let’s run a decision example. With typical enterprise AI solutions, you often get black-box outcomes — you don’t know how decisions are made. With ours, not only is the code open, but every decision variable is traceable and audit-ready. You can see how the risk score was calculated for every profile — from income and marital status to debt ratios.

What enables this is the architecture we’ve built — a set of machine learning models optimized for speed and transparency. You can see exactly how every decision was made. That’s what we mean by “explainable AI.”

4-What do decisions look like across different applicants?

We also offer premade profiles for different product types — whether it’s mortgage, auto leasing, or Murabaha. Even within the same risk segment, different applicants yield different scores depending on their inputs. This shows how finely tuned and responsive our model is to each applicant’s context.

5-What if we already have our own rules and no AI yet?

Now let’s talk about decision tables. This is the core of how we help clients digitize their existing policies. Before implementing full AI, we start by capturing your current rules and converting them into digital logic. This allows you to speed up underwriting almost immediately.

Take an example from POS lending or high-net-worth scoring. Right now, most firms use manual rules — pulling SIMAH data and applying static formulas. We digitize this process so it runs automatically. And it’s fully customizable: you can plug in any data source — API, legacy system, or even scanned documents — and define your own metrics.

6-Can we go live even without much data?

Some clients worry about having too few variables. Don’t worry — we’ve got a robust variable library covering common risk drivers across SME lending, POS, microfinance, and more. We also use synthetic data to fill in any gaps, just like how AI tools complete images when a background is missing. This helps you go live fast, even with minimal historical data.

With our growing model and variable library, you can easily expand into new lending products. If you’re currently doing microfinance, for example, and want to add POS or auto lending, we’ve already built those models — ready to deploy when you are.

7-How does it all connect — from my data to a real decision?

Let’s now talk about how everything ties together — what we call the “workflow.” A workflow brings together data ingestion, the AI engine, your decision rules, and final reporting. Say someone applies for a loan: data can come in from your website, app, API, or even PDFs. From there, our system selects the right model based on the profile, applies the decision logic, and generates a risk score.

This risk score can be delivered wherever you need — your internal dashboard, an audit report, a message to the applicant, or even to lenders in a peer-to-peer system. Everything is seamless, transparent, and tailored to your process.

To wrap up: you’re essentially hiring the world’s best risk experts who never sleep, never leave, and keep getting better. We help you digitize your current process, make it faster, and layer AI on top — with everything from ingestion to reporting being fully explainable, auditable, and customizable.

8-Can I just talk to the system and get real answers, not only reports?

One more bonus: our Knowledge Base. Once your system is live, we turn every decision ever made into a searchable database. Imagine getting notified that a borrower might default — you can immediately ask our AI Agent, “Why did we approve this person?” You’ll get a clear, human-readable explanation instantly. You don’t need to learn technical jargon to ask questions — it works in plain language.

Even if your staff changes, the knowledge base remains. Any new employee can immediately access the history of past decisions. This dramatically improves operational continuity and transparency.

Finally, once everything is live, the Platform becomes your daily interface. You’ll see each applicant, their score, documents, and even have the ability to message them or rescore dynamically. If the applicant’s situation changes, the system alerts you and updates the decision.

9-How fast can we launch — and what’s the next step?

Implementation is immediate. After a 1-hour demo and a follow-up workshop, you’ll already have a full risk assessment tailored to your portfolio. In just 3 days, you can move from first call to live, explainable AI credit decisions — approving the right borrowers instantly.

Because everything — data, models, and decisioning — stays fully under your control, you get a world-class AI credit infrastructure, operational from day one, and scaling with you in real time.