AI-Underwriting
Machine-learning credit scoring that blends bureau, bank-statement and alternative data — with explainable reasons for every score, ready for your risk committee and regulator.
- 1 · Bureau report & repayment historyComplete
- 2 · Bank statements analysed by AIComplete
- 3 · Alternative data signalsComplete
- 4 · Risk score with reason codesIn progress
- 5 · Sent to AI Rule EnginePending
What AI-Underwriting does
Automated credit assessment
AI evaluates borrower profiles using financial data, bureau reports, bank statements, transaction history and supporting documents to build a complete risk picture instantly.
Policy and rule execution
Apply credit policies consistently across every application. Eligibility rules, scorecards, risk thresholds and lending guidelines are checked automatically with full auditability.
Intelligent risk scoring
Machine learning models analyze multiple borrower attributes to identify credit risk, recommend lending limits and support more informed decisions.
Exception management
Route deviations, policy exceptions and high-risk cases to the right approvers while maintaining maker-checker controls and approval workflows.
Explainable decisioning
Every recommendation is supported by clear reasons, policy references and risk indicators, helping underwriters review and approve applications faster.
Portfolio insights
Track approval rates, risk segments, turnaround times and underwriting performance through real-time dashboards and analytics.
Where AI-Underwriting sits in your stack
AI-Underwriting sits between loan origination and core banking systems, turning verified applicant data into fast, consistent and auditable credit decisions.
- CHANNELSBranch · Agent · Web · Mobile · Partner APIs
- AI-LOSCapture · Read · Verify · Route
- AI-UnderwritingAssess Risk · Apply Policies · Score Applications · Recommend Decisions
- AI Rule EngineDecision Automation · Exceptions · Approval Routing
- AI-LMS or Existing Core BankingDisburse · Service · Manage Portfolio
Seamlessly integrated with your origination, decisioning and servicing systems, AI-Underwriting automates credit evaluation while keeping human oversight where it matters most.
Loan products supported
AI-Underwriting supports retail, SME and Islamic finance products through configurable risk models, policies and decision workflows.
- Personal Loans
- Auto Finance
- Home Finance & Mortgages
- SME & Business Loans
- Credit Cards
- Loans Against Property
- Gold Loans
- Microfinance
- Murabaha
- Ijara
- Tawarruq
Faster credit decisions
Automated risk assessment and policy checks reduce manual reviews, helping applications move from submission to decision in minutes.
Improved portfolio quality
Consistent policy enforcement and advanced risk scoring help identify stronger borrowers and reduce credit risk.
Lower underwriting costs
Minimize manual analysis, repeated reviews and operational overhead while enabling teams to handle higher application volumes.
Deployment & licensing
- Standalone AI-Underwriting module or integrated with AI-LOS
- Cloud deployment on Microsoft Azure in your country's region
- Dedicated environment and database for your institution
- Annual licensing for banks; subscription plans for NBFCs and fintechs
- API-first architecture for seamless integration with LOS, LMS and core banking systems
- Configurable credit policies, scorecards and workflows without custom code
AI-Underwriting questions
Can we use our existing credit policies?
Yes. AI-Underwriting is designed to work with your current credit policies, scorecards and risk frameworks. Rules can be configured and updated without code changes.
Will underwriters still be part of the decision process?
Absolutely. AI-Underwriting automates routine assessments and recommendations while routing exceptions, deviations and high-risk applications to designated reviewers for approval.
Can AI-Underwriting integrate with our existing systems?
Yes. AI-Underwriting connects with AI-LOS, core banking platforms, credit bureaus, open banking providers and third-party decision systems through APIs and webhooks.
How are AI decisions explained?
Every recommendation includes supporting risk indicators, policy checks, score breakdowns and decision rationale, ensuring transparency and auditability.
Can we customize risk models by product?
Yes. Different products can have their own eligibility criteria, scorecards, risk thresholds and approval workflows, allowing underwriting strategies to be tailored for each portfolio segment.
Does it support maker-checker and approval hierarchies?
Yes. Multi-level approvals, delegated authority limits, exception routing and full audit trails are built into the underwriting workflow.