DecisionEngine™ - Automated Underwriting Intelligence

End-to-end automated underwriting with intelligent routing of complex cases to human underwriters.

The Challenge

Manual underwriting is slow, expensive, inconsistent, and doesn't scale. Yet it's hard to automate because of complexity and compliance requirements.

What It Does

End-to-end automated underwriting for straightforward applications, with intelligent routing of complex cases to human underwriters with AI-generated recommendations.

Model Metadata

Model Architecture: Hybrid rules engine + XGBoost classifier with explainable decision trees
Training Data Size: 5M+ underwritten applications with outcomes
Features: 250+ application, credit, income, and policy features
Update Frequency: Monthly model refresh, weekly policy updates
Inference Speed: <200ms for full underwriting decision
Auto-Decision Rate: 70-85% of applications
Override Rate: <2% of automated decisions

Business Outcomes

78% of applications auto-decisioned without human touch
Processing time reduced from 3 days to 15 minutes
92% underwriter productivity improvement (focus on complex cases)
$4M+ annual operational savings
Consistent, unbiased decisioning
Faster time-to-close improving customer satisfaction

Training Approach

Hybrid Rules + MLHard regulatory and policy requirements enforced via rule engine (debt-to-income limits, loan-to-value caps). ML model handles nuanced risk assessment within policy guardrails.

Learning from UnderwritersModel trained on historical underwriter decisions, learning their judgment patterns for edge cases.

Counterfactual LearningAnalyzes outcomes of borderline approved vs. denied applications to improve decision boundary.

Confidence-Based RoutingApplications where model is uncertain (confidence <80%) automatically referred to human underwriters.

Data Sources

Application Data

Loan amount, purpose, term requested
Self-reported income and employment
Assets, liabilities, housing costs
Down payment source and reserves

Credit Data

Full tri-merge credit reports
Credit scores from all three bureaus
Recent inquiries and new accounts
Payment history and derogatory items

Income Verification

Argyle, Truework (automated employment verification)
Plaid, Finicity (bank statement analysis)
IRS Form 4506-C (tax transcript verification)
Pay stub and W-2 OCR and analysis

Asset Verification

Bank account verification (Plaid, MX)
Investment account verification
Gift letter and sourcing documentation
Large deposit explanations

Property Data (for mortgages/HELOCs)

AVM (automated valuation models) - CoreLogic, HouseCanary
Appraisal reports (OCR and extraction)
Title search and lien verification
Property tax and insurance verification

Compliance Data

OFAC sanctions screening
HMDA data collection and validation
Fair lending statistical analysis
Required disclosure tracking

Human-in-the-Loop

Complex cases referred with AI-generated recommendations, risk factors highlighted, supporting documentation pre-analyzed. Underwriters make final decisions on edge cases while AI handles routine approvals.