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Online: 3K+ Agents Active
Digital Worker 8 AI Agents Active

Multi-Agent AI Credit Analysis & Financial Health Platform

Deploys 8 specialized agents analyzing credit history, Open Banking transactions, behavioral patterns, affordability, and compliance in parallel. Provides SHAP-based explainability, ESG scoring for sustainable lending, and personalized recovery plans with what-if scenario simulation.

8 AI Agents
8 Tech Stack
AI Orchestrated
24/7 Available
Worker ID: credit-risk-assessment-orchestrator

Problem Statement

The challenge addressed

Traditional credit scoring relies on limited bureau data and fails to capture real financial behavior. Lenders need comprehensive risk assessment using Open Banking data, behavioral analytics, and explainable AI while meeting FCA Consumer Duty requir...

Solution Architecture

AI orchestration approach

Deploys 8 specialized agents analyzing credit history, Open Banking transactions, behavioral patterns, affordability, and compliance in parallel. Provides SHAP-based explainability, ESG scoring for sustainable lending, and personalized recovery plans...
Interface Preview 4 screenshots

Credit Risk AI Assessment - Consumer profile input with credit score 581, credit profile details showing 70% utilization, and 8 AI agents with workflow phases

Multi-Agent Processing - Real-time agent execution showing Executive/Technical/Analyst views, active agents progress, and 6 workflow phases including Open Banking analysis

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

Assessment Results Technical View - System architecture diagram showing presentation layer, 8-agent orchestration layer, GPT-4 Turbo intelligence layer, and processing metrics

Multi-Agent Orchestration

AI Agents

Specialized autonomous agents working in coordination

8 Agents
Parallel Execution
AI Agent

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

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.

ACTIVE #1
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AI Agent

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

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.

ACTIVE #2
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AI Agent

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

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.

ACTIVE #3
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AI Agent

Credit Recovery & Action Plan Specialist

Consumers with suboptimal credit need actionable, personalized improvement plans with realistic timelines and success probability estimates.

Core Logic

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.

ACTIVE #4
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AI Agent

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

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.

ACTIVE #5
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AI Agent

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

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.

ACTIVE #6
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AI Agent

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

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.

ACTIVE #7
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AI Agent

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

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.

ACTIVE #8
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Technical Details

Worker Overview

Technical specifications, architecture, and interface preview

System Overview

Technical documentation

Comprehensive credit risk assessment platform coordinating 8 agents across 6 execution phases. Integrates traditional credit bureau data with Open Banking insights (PSD2), behavioral analytics, and ESG scoring. Delivers explainable decisions with ~6-8 second total processing time.

Tech Stack

8 technologies

Open Banking APIs (PSD2-compliant) for transaction retrieval

Credit bureau integrations (Nexgile, Experian)

NLP transaction categorization engine (175+ categories)

FICO score calculation engine with 5-factor model

Probability of Default (PD) modeling infrastructure

SHAP-style explainability engine for AI transparency

FCA Consumer Duty compliance assessment framework

ESG scoring and green product eligibility engine

Architecture Diagram

System flow visualization

Multi-Agent AI Credit Analysis & Financial Health Platform Architecture
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