🏗️ Client Stories | From Sandbox to System: How We Built Saudi’s First Real AI for Credit Risk

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📍 The Real Problem Isn’t “No AI” — It’s the Wrong Kind

In Saudi Arabia’s lending ecosystem, most financial institutions are stuck choosing between two bad options:

Legacy risk scorecards: manual, slow, Excel-bound
Buzzword AI vendors: vague promises, no local traction

The result? 30-day underwriting cycles, Excel sheets running billion-riyal portfolios, and AI projects that feel more like academic experiments than operational systems.

We decided to flip the model entirely. Instead of asking institutions to wait 12 months for “AI results,” we show them working models — in Arabic, on day one, with their data.

🧩 A Glimpse Into How Credit Risk Is Scored — and Why It’s Ready for Reinvention

Below is a redacted glimpse of how credit is still scored today

🔍 This table is a simplified example based on real client implementations in 🇸🇦 Saudi Arabia. It reflects only a subset of risk factors used in Tawarruq, Murabaha, SME, and HNW credit workflows. Actual scoring logic, weights, and thresholds are proprietary and not shown here.

⚙️ What Powers This Shift? A Base Model That’s Actually Useful

Most vendors pitch a sandbox. We ship a system. Here’s what makes ours different:

🧠 Pretrained Base Models for SME and personal credit — built on real data across markets
📍 Localized Tuning with CR numbers, bank statements, and Saudi merchant data
🧩 Embedded Decision Logic — fully auditable, explainable, and regulator-ready

Think of it like this:

They give you raw ingredients. We show up with the kitchen prepped, spices ready, and the stove already on.

🧠 A glimpse into our pre-trained and fine-tuned model suite — built for real-world credit decisions in Saudi Arabia.

“Other models start flat. Ours comes tuned — ready for Saudi terrain.” What you see here is just a subset. Behind the scenes, our platform hosts dozens of modular models spanning SME, personal, and product-specific lending. ⚡ From “Sole Proprietor” to “SaaS” to “Pre-Revenue,” each model is pretrained, localized, and ready to deploy — no sandbox, no guesswork.

🚀 What Happens When You Plug in Real Onboarding Data?

Here’s the “aha” moment:

With just a few weeks of onboarding data, your base model becomes a custom engine — tuned for your risk segments, your behavior profiles, and your regulator’s expectations.

Here’s why that matters:

⚡ Faster learning loops — 3 months of merchant activity is often more valuable than 3 years of legacy rules
🔍 Live feedback builds trust — “Here’s how your portfolio would’ve scored, today”
🔐 Every deployment strengthens the model — you gain speed and defensibility
💰 You can monetize early — no need to wait for defaults to prove value

This turns a data request from a chore into a strategic unlock.

📊 Real Data = Trust

Your dashboard, live from day one — no guesswork, no black box.

✅ This is not a mockup. ⚡ Accuracy, default rate, turnaround time — all surfaced instantly, with explainability baked in. This is the moment when our clients stop asking, “When can we see results?” “Can we go live this quarter?”

📉 Why Traditional AI Deployments Fail

Too often, “AI” projects in financial services fall apart because:

❌ They require 12 months of IT alignment

❌ They force institutions to guess the ROI

❌ They speak English only — and barely speak compliance

Our approach eliminates all that:

✅ 10x faster go-live

✅ Transparent, tunable scoring

✅ Runs in real production — not theory

🔄 From Black Boxes to Building Blocks

We’ve moved the market from:

📉 Static Scorecards → Dynamic Models
🧱 Black Box AI → Transparent Engines
⏳ 12-Month Builds → 8-12 Weeks Deployments

Our clients don’t ask for a POC anymore. They ask: “When can you run it on my data?”

🛠️ Saudi-First Design, Not Global Templates

This isn’t a stripped-down import. We built this system for:

Institutions giving 500K SAR loans with 3-month tenures
Analysts who use Excel to score merchant risk
Regulators who demand clarity and control

“A Saudi-first platform — built with local teams, language, and compliance in mind.”

“Global tools are like German sedans. Elegant — but they overheat in the desert. We’re the Land Cruiser. Built for this terrain.”

🎯 TL;DR: What Changes Now

Start With Strength — Our base models remove the “cold start” problem.
Customize With Confidence — You only need weeks of data, not years.
Deploy With Trust — Explainability is built in, not bolted on.
Speak Their Language — Arabic-first, Saudi-aligned, SAMA-compliant.
Operate in Reality — Not labs, not slides — real institutions, real returns.