Autonomous Mortgage

The Autonomous Loan Processing taking Mortgage as a case in point example showcases how AI, Automation, and Agents collapse a traditional 15–20-day process into a near real-time journey. From instant income, debt, property and credit verification to proactive compliance, reducing “time to yes” as customers move from intent (“I need a home loan”) to offer with minimal effort.

Autonomous Mortgage leverages core AWS services to ensure reliability, scalability, and performance:

• Amazon Bedrock (Claude Sonnet, Titan, Guardrails) • AWS Step Functions • Amazon Textract • Amazon OpenSearch Serverless • Amazon S3 • AWS KMS • Amazon Macie • Amazon Cognito • Amazon CloudWatch • AWS X-Ray • Amazon API Gateway • Amazon EventBridge • AWS CodePipeline • AWS CodeBuild • Amazon ECR • AWS PrivateLink • AWS Control Tower • AWS IAM • AWS Config • AWS CloudTrail • AWS WAF • Amazon CloudFront

Banks have invested heavily in automation and digitization - this has delivered speed and efficiency at the edges of the mortgage journey, but the last mile of document variability remains untouched creating systemic drag on time-to-underwriting and costs an issue that repeats across multiple banking journeys.

• Document intake and reconciliation remain human-mediated requiring re-keying and reconciliation

• Variability beats automation. Non-standard formats, screenshots, redactions, multi-income sources, self-employed filings: conventional automation tools break down. Tools powered by OCR, ICR, ML supported have provided minimal gains as these tools works on defined boundary or context for extraction and does not extract related information together

• Underwriters wait, not decide. Skilled staff spend days assembling data instead of assessing credit risk

Similar tasks, different teams, affordability, eligibility based on customer income is a task undertaken by bank operation team for every loan product

Autonomous Mortgage is live in production and delivers measurable improvements by automating the most manual phase of origination (document intake, validation, reconciliation and affordability computation) while keeping final underwriting accountability with bankers/underwriters.

• Cycle time reduction: document processing time reduced from 15–20 days to near real-time preparation of the underwriting package (with banker/underwriter final approval).

• Quality uplift: 95%+ extraction and reconciliation accuracy, materially reducing manual interpretation errors and downstream rework.

• Capacity gain: enables ~5× throughput increase for underwriting preparation without proportional headcount growth (peak-volume resilience).

• One-click customer consent enables instant aggregation from Open Banking, payroll and tax sources to pre-fill eligibility and affordability.

• AI-powered document and text extraction from varied formats reduces manual effort by ~70%.

• Transaction categorization and income/expense classification requires minimal human intervention (typically <10% of entries); feedback loops continuously improve accuracy.

• Composable agent architecture provides flexibility to pick and choose agents and integrate into existing mortgage operating models.

• Reusable capability across consumer loan products (mortgages, personal loans, credit card eligibility flows), reducing duplicate build effort.