AI Agentic Delinquency Prevention System
## The Solution A Fortune 500-grade multi-agent AI system proactively identifies at-risk employers through pattern recognition, predicts cash flow constraints, designs customized payment solutions, ensures regulatory compliance, and orchestrates personalized outreach—preventing delinquencies before they occur..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Configure Analysis Input form for employer delinquency prevention showing employer information fields (ID, name, industry, employee count), risk context with urgency level selection (Low/Medium/High/Critical), previous delinquency history tracking, and Launch AI Analysis action button
Agent Execution Console displaying completed analysis (35.9s, 3,340 tokens, $0.01 cost) with 7-agent fleet status, Chain of Thought reasoning trail showing OBSERVATION-THOUGHT-ACTION-CONCLUSION pattern, workflow phases, and preliminary results with 30% risk score and Flexible 3-Month Payment Plan recommendation
Analysis Results Summary showing LOW risk level (30/100 score), 29% delinquency probability, 91% AI confidence, key findings (Payment History Analyzed, Cash Flow Forecasted, Solutions Personalized, Compliance Verified), and recommended Flexible 3-Month Payment Plan with model accuracy metrics
AI Agent Analysis Executive Summary report for Metro Electric Services showing risk score visualization (30), $7,200 revenue at risk, $792 potential penalties, 32 employees affected, key findings with delinquency probability and cash flow analysis, and detailed payment plan recommendation with AI reasoning explanation
AI Agents
Specialized autonomous agents working in coordination
Supervisor Orchestrator Agent
Complex delinquency cases require coordinated analysis across financial, compliance, and communication domains with intelligent escalation and human-in-the-loop capabilities.
Core Logic
The Supervisor Agent (claude-3-5-sonnet, temperature 0.3) orchestrates the seven-agent workflow using ReAct reasoning. It manages execution phases, delegates to specialists, synthesizes cross-domain insights, makes autonomous decisions within configured thresholds, and escalates high-stakes cases for human review while maintaining comprehensive audit trails.
Data Analyst Agent
Identifying delinquency risk requires comprehensive analysis of payment history, contribution patterns, and operational anomalies across thousands of employer records.
Core Logic
This agent (claude-3-5-haiku, temperature 0.2) retrieves and analyzes historical payment records using statistical trend analysis and ARIMA models. It identifies payment pattern anomalies, detects early warning signals, calculates historical metrics, and prepares enriched data profiles for downstream risk assessment.
Risk Assessment Agent
Quantifying delinquency probability requires sophisticated risk modeling that accounts for employer-specific factors, industry conditions, and macroeconomic indicators.
Core Logic
The Risk Assessor Agent (gpt-4o, temperature 0.1) calculates comprehensive risk scores using Monte Carlo simulation engines. It evaluates multiple risk factors, generates probability distributions, compares against industry benchmarks, and produces explainable risk assessments with confidence intervals and peer percentile rankings.
Cash Flow Prediction Agent
Payment problems often stem from cash flow timing mismatches rather than unwillingness to pay—identifying these situations enables targeted solutions.
Core Logic
This agent (claude-3-5-haiku, temperature 0.2) employs Prophet-based forecasting to project employer cash positions. It identifies upcoming shortfall periods, models seasonal cash cycles, estimates payment capacity windows, and determines optimal intervention timing to maximize collection success.
Solution Architect Agent
Generic payment plans fail to account for employer-specific constraints. Effective solutions must balance fund recovery with employer business realities.
Core Logic
The Solution Architect Agent (claude-3-5-sonnet, temperature 0.3) designs customized payment solutions using multi-objective optimization. It generates payment plan options (installment, early discount, hardship programs), calculates cash flow fit scores, estimates success probabilities, and produces detailed proposals with reasoning chains explaining tradeoffs.
Compliance Checker Agent
Delinquency interventions must comply with ERISA fiduciary duties, DOL regulations, and fund-specific rules—non-compliant actions expose trustees to liability.
Core Logic
This agent (gpt-4o-mini, temperature 0.4) validates all proposed solutions against regulatory requirements. It checks ERISA compliance, DOL regulations, fund collection policies, and disclosure requirements. It identifies compliance risks, suggests modifications for compliant alternatives, and generates attestation documentation.
Communication Specialist Agent
Effective employer outreach requires personalized messaging, optimal channel selection, and strategic timing—generic collection letters achieve poor response rates.
Core Logic
The Communication Specialist Agent (gpt-4o-mini, temperature 0.4) crafts personalized outreach strategies. It selects optimal communication channels (email, phone, portal, mail), generates customized message templates, schedules multi-touch campaigns, and adapts tone based on employer relationship history and risk severity.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
8 technologies
Architecture Diagram
System flow visualization