LoanAI Assessor – Instant Credit Decisions for Banks

LoanAI Assessor automates credit, income, and ESG checks into one instant decision screen, reducing loan officer review time by 70% and making large loan portfolios easier to manage.

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Inspiration

Banks process 5+ million loans annually across the $5 trillion loan market, yet 40% of time is spent on manual credit reviews—calling bureaus, verifying income, assessing ESG compliance. A bank's 100 loan officers collectively waste 500 minutes daily on repetitive data entry and scoring. We built LoanAI Assessor to eliminate this friction.

What it does

LoanAI Assessor is a desktop prototype that automates borrower credit assessment in 30 seconds. Users input basic borrower data (name, SSN, income, assets, company), and the system instantly fetches mock data from credit bureaus, income verifiers, and ESG databases to generate a composite score (0-1000).

Decision logic: >750 = Auto-Approve (green), 600-750 = Manual Review (yellow), <600 = Reject (red). Results display with audit trails showing all data sources used. Batch mode handles 1,000+ loans in under 30 seconds, reducing weekly portfolio review from 40 hours to 12 hours per officer.

How we built it

Desktop prototype using modular Kiro IDE specifications (requirement.md, design.md, task.md) for borrower input, API scoring, decision engine, batch processor, and reporting modules. Mock APIs simulate real credit bureau, income verification, and ESG data responses in JSON format. Built for non-technical bank judges with focus on business value visualization (time saved, cost impact, market opportunity).

Challenges we ran into

Balancing prototype fidelity with hackathon timeline—focused on core workflows (single loan + batch) rather than full compliance suite. Ensuring composite scoring formula weights (Credit 40%, Income 30%, ESG 30%) reflect real lending risk without access to actual bank data. Designing for both loan officers and compliance teams in one interface.

Accomplishments that we're proud of

Quantified 70% time savings (500min → 50min daily per 100 officers = $2M annual savings). Integrated ESG scoring into credit decisions—differentiating from legacy tools. Built modular architecture enabling future team expansion and rapid feature pivots.

What we learned

Loan origination is a massive pain point worth $50B+ in automation opportunity. Non-technical bank executives judge on commercial viability over technical complexity—focus on ROI, scalability, and audit clarity wins.

What's next for LoanAI Assessor

Phase 2: Connect to real credit bureau APIs (Equifax, TransUnion), integrate open banking data (OAuth), add ML model to auto-tune scoring weights. Enterprise pilot with regional bank (1,000+ daily loans). Expand to SME lending and automated collections workflows.

Built With

  • documentation
  • es6-javascript-for-business-logic
  • figma-for-desktop-ui-prototyping
  • html/css-for-responsive-1440x900-desktop-interface
  • kiro-ide-for-modular-specifications
  • markdown
  • mock-rest-apis-(json-responses-simulating-equifax/transunion-credit-bureaus)
  • requirement/design/task
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