Credit Decisioning
Instant, high-quality credit decisions. On your framework.
Your policy rules and AI models trained on your own loanbook, in one engine that approves, prices, and documents every MSME application in seconds. Grow the book, price for risk, and bring NPLs down. Not a black box. On your framework, no core replacement.
Decision engine
Application #4821
Data sources
Risk score
742
Risk-based price
SAR 250k · 14.5%
Your credit policy is static, manual, and hard to govern.
Manual underwriting is slow, inconsistent, and expensive. The same applicant gets different answers from different analysts, and policy changes take months to roll out.
Manual underwriting
- Policy sits in documents and spreadsheets
- Different analysts, different answers
- Policy changes take months to roll out
- Rule-based scorecards that go stale
- No defensible record for regulators
Abwab Credit Decisioning
- Policy encoded once, enforced on every application
- Consistent, auditable decisions everywhere
- Faster rollout of products and policy changes
- Loanbook-trained models, continuously backtested
- Full decision logs for audit and SAMA
Decision strategy
Your rules and your models, one orchestrated decision.
Most engines hand you a black-box score. Abwab orchestrates your policy rules with your or our AI models into a single decision, approve, refer, or decline, with risk-based pricing and a full audit log. On your framework.
- Combine policy rules, PD models, and your in-house models
- One output: approve, refer, or decline, plus risk-based price
- Every decision versioned and logged for SAMA
Decision strategy
rules + modelsYour policy rules
- Eligibility & limits
- LTV · DSCR · sector
AI models
- PD / risk score
- Your in-house models
Not a black box. Your policy and your models in one decision.
AI credit modeling
Turn your loanbook into a live credit model.
Abwab builds PD, LGD, and risk models from your own historical loanbook and keeps them sharp: an ensemble of statistical, gradient-boosting, deep-learning, and language models spanning 150+ risk metrics, retrained on every booked file.
- PD, LGD, and risk models trained on your loanbook
- An ensemble of statistical, gradient-boosting, deep-learning, and LLM approaches
- Retrained on every booked file, shadow-tested before going live
Credit model
trained on your loanbookYour loanbook
approvals · defaults · recoveries
Models trained on your data, kept calibrated as the portfolio evolves.
Policies & lending products
Configure every credit policy and lending product.
Encode your credit policy once, then configure distinct lending products, each with its own limits, tenors, pricing bands, eligibility, and decision strategy per product, segment, channel, or campaign. No code, versioned, fully auditable.
- Per-product limits, tenors, and pricing bands
- Product, segment, channel, and campaign strategies
- No code, versioned, with full audit history
Credit policy
v12 · activeEncoded once. Enforced on every application.
Outputs & governance
Every decision, explained and documented.
Every decision returns a PD, a risk band, a recommendation to approve, review, or decline, and the top factors that drove it, with a pricing recommendation and an AI-drafted credit memo so analysts handle exceptions instead of writing every file.
- PD, risk band, recommendation, and top-factor explainability
- Pricing recommendation engine: tenor, amount, and rate
- AI-drafted credit memo and PDF reports for logging and record keeping
- Immutable logs, version control, SAMA-aligned validation reports
Capabilities
Everything you need to decision at scale.
Centralized, configurable credit policy
You own the rules. Encode your framework once and apply it everywhere.
Loanbook-trained models
PD and LGD models with champion-challenger testing and backtesting against your legacy rules.
Real-time orchestration
Real-time scoring and approve, refer, or decline orchestration per product, segment, and channel.
Risk-based pricing
Recommended terms and risk-based pricing on every decision.
Governance and decision logs
Version control and full decision logs for governance and regulators.
Human-in-the-loop
Shadow, co-pilot, or autonomous, configurable per strategy.
How it works
Your rules and models, applied in real time.
Rules engine
Centralize your credit policy (eligibility, limits, authority levels) and product or segment rules (LTV, DSCR, sector, collateral).
Models
Build probability-of-default and risk models from your historical loanbook, run challengers, and backtest against legacy rules. Plug in your in-house models where required.
Score and decide
Real-time scoring using bureau and financial data, with Agentic Credit Intelligence signals as an optional input. Approve, refer, or decline per product, segment, channel, or campaign.
Price and document
Risk-based pricing and recommended terms, with full decision logs of inputs, paths, and outputs for audit and regulators.
Outcomes
70%
Faster credit decisions
90%
Lower cost per assessment
10x
Analyst leverage
12
Production ML models
Frequently asked questions
No. Credit Decisioning is API-first and runs on top of your existing stack. There is no core replacement.