Comprehensive fraud detection capabilities
Application Screening
Automatically screen loan applications in real-time as they enter the TLOS LoanApplication table. Our system triggers at pre-funding stage, flagging high-risk and fraudulent applications before they reach your review team. Integrates seamlessly into your existing OLL → TLOS loan lifecycle.
AI Co-Pilots that augment your fraud review team
Acts as an intelligent ride-along partner for your review team, providing real-time fraud probability scores (0.0 to 1.0) and plain-English explanations. Detects high-risk and fraudulent loan applications at pre-funding stage, helping your team make faster, more accurate decisions with data-driven insights.
Identifies three distinct applicant personas: "Digital Ghost" (70% fraud concentration, lacks verifiable data), "High-Friction Anomaly" (abnormally slow process with long pauses), and "Safe Bet" (100% legitimate, ideal for fast-track approvals). These behavioral patterns serve as powerful leading indicators of risk.
Unsupervised Isolation Forest algorithm that studies all applications to build a mathematical profile of normal applicants. Sounds the alarm when it sees applications that are mathematically weird or do not fit in, even if it is a type of fraud never encountered before, providing crucial protection against new fraud tactics.
GenAI-powered PDF reports that translate complex model logic into plain English. For every flagged application, provides risk probability, primary risk factors (e.g., "unusually high number of digits in email address"), and mitigating factors, turning raw data into actionable intelligence.
The power of
explainable AI
Our AI Co-Pilot doesn't just detect fraud—it explains why. Get real-time risk scores with plain-English explanations that help your team make faster, more confident decisions.
50% fraud detection on test set
Our ensemble "Task Force" model successfully detected 50% of never-before-seen fraudsters in the holdout test set. This was achieved by combining the XGBoost "Detective" (25% fraud recall) with the Isolation Forest "Watchdog" in a 50/50 ensemble, dramatically outperforming single-model approaches.
Three distinct applicant personas discovered
Unsupervised analysis using UMAP + HDBSCAN revealed three clear behavioral personas: "Digital Ghost" (70% fraud concentration, lacks verifiable data), "High-Friction Anomaly" (abnormally slow process), and "Safe Bet" (100% legitimate, ideal for fast-track). These personas enable strategic triage and focused expert attention.
AI Co-Pilot protects capital at pre-approval stage
AI Co-Pilot · Real-time fraud detection
Catch fraud before it costs you
Detect fraudulent loan applications at pre-approval and pre-funding stages. Our AI identifies early reversals, legal actions, repos, UCC failures, and other high-severity fraud indicators.
Early Fraud Indicators
Detect early payment reversals, legal actions, repos, UCC failures, known forgeries, and first-payment defaults. Our rules-based engine translates real-world outcomes into definitive FRAUD labels, ensuring the model predicts actual business impact.
Risk indicators: EARLY REVERSAL (HIGH), LEGAL ACTION (MEDIUM), UCC FAILURE (HIGH), FIRST-PAYMENT DEFAULT (HIGH)
Applicant Persona Analysis
Identify three distinct personas: "Digital Ghost" (70% fraud, lacks verifiable data), "High-Friction Anomaly" (abnormally slow with long pauses), and "Safe Bet" (100% legitimate). These behavioral patterns enable strategic triage and fast-track approvals for low-risk applicants.
Persona: DIGITAL GHOST detected, IDV CHECKS: 100% below average, BEHAVIORAL ANOMALY (HIGH)
Real-time Risk Scoring
Get instant fraud probability scores (0.0-1.0) with GenAI-powered PDF explanations. Reports answer: What is the risk? Why is it risky? Are there mitigating factors? Transforms complex SHAP data into plain-English actionable intelligence.
Risk Score: 0.85 (HIGH), Top Factors: High email digit ratio, Long application pauses, Low IDV checks
Enterprise-grade AI infrastructure
Secure data ingestion from OLL and TLOS systems with encrypted PII handling. Transforms approximately 100 raw data points into 650+ predictive features, capturing behavioral anomalies (deltaH timing features), contact information patterns, profile stability factors, and identity verification signals.
The "Task Force" ensemble combines two detection philosophies: XGBoost "Detective" (supervised learning expert on known fraud patterns) and Isolation Forest "Watchdog" (unsupervised anomaly detector). The 50/50 ensemble score dramatically improves detection rates, achieving 50% fraud detection on test sets.
Headless API deployment on AWS Lambda/SageMaker with secure API Gateway. Listens for new LoanApplication records, executes feature engineering pipeline, and writes FraudScore (0.0-1.0) and FraudFlag (binary) back to TLOS. Simultaneously generates GenAI-powered explanation reports via Amazon Bedrock.
Automated feedback loop captures loan outcomes (defaults, reversals, early legal actions) to create ground-truth labels. Automated retraining pipelines detect data drift, retrain models in SageMaker, and deploy only if new model beats previous accuracy metrics. Includes CloudWatch/QuickSight dashboards for technical and business metrics.
The AI Co-Pilot has transformed how we review applications. Getting plain-English explanations for every risk score helps our team make faster, more confident decisions.
Trusted by leading financial teams
