We built AI agents that reduce mortgage processing from 18 days to 3–5
Most mortgage processing delays aren’t due to risk — they’re due to manual workflows. We’ve been working on SimplAI, an AI-driven system designed for banking and financial services, starting with mortgage operations. The problem we kept seeing: 15–22 day processing timelines Heavy manual document handling (500+ pages per loan) Repetitive data entry + verification loops Underwriters spending hours on non-decision work So we built a set of AI agents that handle the operational layer: Document AI (IDP) → classifies + extracts data from loan docs in minutes Income analysis models → parse tax returns, payslips, and variable income Verification integrations → real-time employment + financial checks AI-assisted underwriting → pre-validates files and generates conditions Compliance engine → continuously checks against regulatory rules What we’re seeing in production: End-to-end processing: ~18 days → 3–5 days Data extraction accuracy: 97%+ Underwriting review time: 3–4 hrs → <45 mins Cost per loan: reduced by ~40–50% We’re not replacing underwriters — we’re removing the operational bottlenecks around them. Still early, but we’re exploring: Agent-based workflows across lending lifecycle Better handling of edge cases (self-employed borrowers, non-QM loans) Explainability in underwriting decisions Would love feedback from folks in fintech, lending, or anyone building AI systems in regulated environments.
✨ Resumo de IA
Most mortgage processing delays aren’t due to risk — they’re due to manual workflows. We’ve been working on SimplAI, an AI-driven system designed for banking and financial services, starting with mortgage operations. The problem we kept seeing: 15–22 day processing timelines Heavy manual document handling (500+ pages per loan) Repetitive data entry + verification loops Underwriters spending hours on non-decision work So we built a set of AI agents that handle the operational layer: Document AI (IDP) → classifies + extracts data from loan docs in minutes Income analysis models → parse tax returns, payslips, and variable income Verification integrations → real-time employment + financial checks AI-assisted underwriting → pre-validates files and generates conditions Compliance engine → continuously checks against regulatory rules What we’re seeing in production: End-to-end processing: ~18 days → 3–5 days Data extraction accuracy: 97%+ Underwriting review time: 3–4 hrs → <45 mins Cost per loan: reduced by ~40–50% We’re not replacing underwriters — we’re removing the operational bottlenecks around them. Still early, but we’re exploring: Agent-based workflows across lending lifecycle Better handling of edge cases (self-employed borrowers, non-QM loans) Explainability in underwriting decisions Would love feedback from folks in fintech, lending, or anyone building AI systems in regulated environments.
Melhor para
Desenvolvedores, equipes de produto e fundadores técnicos.
Por que importa
Most mortgage processing delays aren’t due to risk — they’re due to manual workflows. We’ve been working on SimplAI, an AI-driven system designed for banking and financial services, starting with mortgage operations. The problem we kept seeing: 15–22 day processing timelines Heavy manual document handling (500+ pages per loan) Repetitive data entry + verification loops Underwriters spending hours on non-decision work So we built a set of AI agents that handle the operational layer: Document AI (IDP) → classifies + extracts data from loan docs in minutes Income analysis models → parse tax returns, payslips, and variable income Verification integrations → real-time employment + financial checks AI-assisted underwriting → pre-validates files and generates conditions Compliance engine → continuously checks against regulatory rules What we’re seeing in production: End-to-end processing: ~18 days → 3–5 days Data extraction accuracy: 97%+ Underwriting review time: 3–4 hrs → <45 mins Cost per loan: reduced by ~40–50% We’re not replacing underwriters — we’re removing the operational bottlenecks around them. Still early, but we’re exploring: Agent-based workflows across lending lifecycle Better handling of edge cases (self-employed borrowers, non-QM loans) Explainability in underwriting decisions Would love feedback from folks in fintech, lending, or anyone building AI systems in regulated environments.
Principais recursos
- Most mortgage processing delays aren’t due to risk — they’re due to manual workflows.
- We’ve been working on SimplAI, an AI-driven system designed for banking and financial services, starting with mortgage operations.
- The problem we kept seeing: 15–22 day processing timelines Heavy manual document handling (500+ pages per loan) Repetitive data entry + verification loops Underwriters spending hours on non-decision work So we built a set of AI agents that handle the operational layer: Document AI (IDP) → classifies + extracts data from loan docs in minutes Income analysis models → parse tax returns, payslips, and variable income Verification integrations → real-time employment + financial checks AI-assisted underwriting → pre-validates files and generates conditions Compliance engine → continuously checks against regulatory rules What we’re seeing in production: End-to-end processing: ~18 days → 3–5 days Data extraction accuracy: 97%+ Underwriting review time: 3–4 hrs → <45 mins Cost per loan: reduced by ~40–50% We’re not replacing underwriters — we’re removing the operational bottlenecks around them.
- Still early, but we’re exploring: Agent-based workflows across lending lifecycle Better handling of edge cases (self-employed borrowers, non-QM loans) Explainability in underwriting decisions Would love feedback from folks in fintech, lending, or anyone building AI systems in regulated environments.
Casos de uso
- Review original launch sources before making adoption decisions.
- Track community momentum from Product Hunt, GitHub, and Hacker News.