AI Credit Assessment System
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Illustrative preview (sample data, not verified outcomes): AI Credit Assessment landing page displaying pre-qualification amount (₦650,000), credit score gauge (780/900), and loan product catalog featuring Working Capital, Inventory Financing, Equipment Loan, and Emergency Credit options with terms and rates
Illustrative preview (sample data, not verified outcomes): Multi-agent analysis dashboard showing five AI agents (Alternative Data, Business Intelligence, Decision Synthesis, Transaction Analysis, Risk Assessment) processing in parallel with confidence scores, live analysis stream, and key insights discovered including revenue patterns and risk profile
Illustrative preview (sample data, not verified outcomes): Loan application form with amount slider (₦500,000), repayment period selection (3-12 months), real-time loan calculator displaying monthly payment, total interest, and repayment breakdown, plus AI analysis indicators for transaction history and business benchmarks
Illustrative preview (sample data, not verified outcomes): Assessment complete screen showing UNDER_REVIEW decision with composite credit score (88/100), 85% confidence level, 39-second processing time, executive summary of 5 specialized AI agents analysis, and step-by-step process timeline from application to multi-agent analysis
AI Agents
Specialized autonomous agents working in coordination
Transaction Analysis Agent
Lenders lack visibility into actual cash flow patterns and revenue consistency of informal businesses without traditional banking statements.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Numerical examples are scenario inputs or illustrative outputs, not validated performance results. Analyzes 6 months of transaction history to detect revenue patterns, calculate average monthly income, identify seasonal trends, and evaluate transaction velocity. Processes 487+ transactions to generate income stability metrics and payment behavior scores. Contributes 35% weight to composite score with typical scores of 85-90/100.
Business Intelligence Agent
Individual business assessment lacks context of market positioning and peer performance benchmarks for accurate risk calibration.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Numerical examples are scenario inputs or illustrative outputs, not validated performance results. Evaluates business model viability by benchmarking against 1,200+ similar businesses in the same sector. Analyzes market positioning, growth trajectory, competitive advantages, and industry-specific risk factors. Calculates peer percentile ranking and sector performance deviation. Contributes 25% weight with typical scores of 80-85/100.
Alternative Data Agent
Credit-invisible borrowers with no formal credit bureau records cannot demonstrate creditworthiness through traditional documentation.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Numerical examples are scenario inputs or illustrative outputs, not validated performance results. Mines non-traditional data sources including utility payment history (electricity, water, telecom), digital footprint analysis (social media presence, online reviews), and supplier relationship assessment. Tracks payment punctuality rates and business reputation signals. Contributes 20% weight with typical scores of 88-92/100 for consistent payers.
Risk Assessment Agent
Manual risk evaluation misses subtle fraud indicators and fails to quantify default probability with statistical precision.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Numerical examples are scenario inputs or illustrative outputs, not validated performance results. Executes multi-model risk profiling combining fraud detection algorithms, default probability calculations, and anomaly detection. Computes risk metrics including 8.2% baseline default probability, fraud indicator flags, and exposure-at-default estimates. Runs velocity checks and pattern deviation analysis. Contributes 20% weight with typical scores of 90-94/100.
Decision Synthesis Agent
Disparate agent outputs require intelligent aggregation to produce coherent, explainable lending decisions with confidence bounds.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Waits for all specialist agents to complete (activates at T+20s), then synthesizes insights using weighted scoring algorithms. Calculates composite credit score, generates confidence percentages, determines final decision (APPROVED/UNDER_REVIEW/DECLINED), computes loan terms (amount, rate, monthly payment), and produces human-readable decision reasoning. Typical scores of 86-90/100.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
6 technologies
Architecture Diagram
System flow visualization