Multi-Agent AI Credit Analysis & Financial Health Platform
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): Credit Risk AI Assessment - Consumer profile input with credit score 581, credit profile details showing 70% utilization, and 8 AI agents with workflow phases
Illustrative preview (sample data, not verified outcomes): Multi-Agent Processing - Real-time agent execution showing Executive/Technical/Analyst views, active agents progress, and 6 workflow phases including Open Banking analysis
Illustrative preview (sample data, not verified outcomes): Assessment Results Executive View - Credit score improvement projection from 581 to 690, showing 99 points to gain over 9 months timeline, 72% success rate, and £300 annual savings
Illustrative preview (sample data, not verified outcomes): Assessment Results Technical View - System architecture diagram showing presentation layer, 8-agent orchestration layer, GPT-4 Turbo intelligence layer, and processing metrics
AI Agents
Specialized autonomous agents working in coordination
Credit Assessment Workflow Coordinator
Complex credit assessments require coordination across multiple specialist agents with proper data flow, phase sequencing, and synthesis of multi-dimensional outputs into actionable recommendations.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Manages 6-phase execution flow: Data Ingestion, Open Banking Analysis, Credit Analysis, Risk Assessment, Recovery Planning, and AI Explainability. Coordinates agent execution, aggregates results, and produces final output including executive summary, key insights, and next best actions with overall confidence and data quality scores.
Credit History & Score Analyzer
Understanding credit history requires analysis of bureau data across multiple factors. Identifying improvement opportunities helps consumers build better credit profiles.
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. Fetches credit bureau data and calculates FICO scores using 5-factor model: Payment History (35%), Credit Utilization (30%), Credit Age (15%), Credit Mix (10%), New Credit (10%). Identifies positive and negative factors, performs historical trend analysis, and rates score as Poor/Fair/Good/Very Good/Excellent. Uses `credit_bureau_fetch` (~1200ms) and `fico_calculator` (~150ms) tools.
Default Probability & Risk Tier Specialist
Lenders need accurate probability of default calculations and risk tier classifications to make appropriate credit decisions and set pricing strategies.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Calculates Probability of Default using logistic regression models, assigns risk tiers (Super-Prime ≥720, Prime 660-719, Near-Prime 620-659, Subprime 580-619, Deep Subprime <580), estimates confidence intervals, and determines product eligibility. Uses `pd_model` (~200ms) and `risk_stratifier` (~50ms) tools.
Credit Recovery & Action Plan Specialist
Consumers with suboptimal credit need actionable, personalized improvement plans with realistic timelines and success probability estimates.
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. Creates month-by-month recovery timelines with milestone-based progress tracking. Prioritizes opportunities by impact/effort ratio, estimates success probability (42-95%), and calculates potential savings (monthly, annual, lifetime). Uses `opportunity_ranker` (~300ms) and `timeline_generator` (~250ms) tools to produce actionable step-by-step plans.
Financial Scenario & What-If Analyzer
Consumers need to understand how financial decisions impact their credit scores. What-if analysis enables informed decision-making about credit management actions.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Performs Monte Carlo simulation of 4+ scenarios: Pay Down Credit Cards, Become Authorized User, Open New Credit Card, Close Oldest Account. Predicts score impacts with confidence intervals, analyzes risk-benefit tradeoffs, and recommends optimal strategy. Outputs include pros/cons analysis and specific recommendations for each scenario.
Open Banking Transaction & Income Analyst
Declared income often differs from actual income. Real-time transaction analysis through Open Banking provides verified income, spending patterns, and financial resilience indicators.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Connects to PSD2-compliant Open Banking APIs to analyze 12 months of transactions. Performs income verification (declared vs. verified), spending categorization across 175+ categories, cash flow health scoring, and financial resilience assessment. Identifies risk indicators including gambling spend, BNPL usage, payday loans, and crypto transactions. Uses `open_banking_analyzer` (~2500ms), `transaction_categorizer` (~800ms), `affordability_calculator` (~350ms), and `income_verification` (~450ms) tools.
FCA Consumer Duty & Regulatory Compliance Specialist
Lenders must comply with FCA Consumer Duty, GDPR, and AML regulations. Non-compliance results in regulatory penalties, reputational damage, and consumer harm.
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. Performs FCA Consumer Duty assessment including fair value, suitability, and vulnerability identification. Validates GDPR compliance (consent, data minimization, retention). Conducts affordability stress testing (+2% interest rate scenario). Executes AML/KYC checks including PEP screening and sanctions verification. Uses `regulatory_compliance_check` (~600ms), `consumer_duty_assessment` (~400ms), and `gdpr_data_processor` (~250ms) tools.
Payment Behavior & Financial Habits Analyst
Credit scores alone miss important behavioral signals. Payment patterns, financial habits, and digital engagement provide predictive insights beyond traditional bureau data.
Core Logic
Illustrative workflow design. Validate capabilities, performance, controls and integration requirements before implementation. Analyzes payment behavior (on-time rate, early payment tendency, autopay, consistency), financial habits (budgeting, savings, impulse risk), and digital engagement (app usage, alerts, budget tools). Incorporates alternative data (utility payments, rental registry, subscriptions). Generates ESG scores for sustainable lending eligibility. Provides SHAP-style explainability with feature importance and counterfactual explanations. Uses `behavioral_pattern_analyzer` (~550ms), `xai_explainer` (~450ms), `alternative_data_fetcher` (~1200ms), and `esg_scorer` (~400ms) tools.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
8 technologies
Architecture Diagram
System flow visualization