AI Systems Implementation Plan
AI-powered underwriting assistance and document intelligence for internal operations.
Overview
This document outlines the initial two phases of an AI integration initiative for Geneva Financial. The goal is to layer intelligent automation on top of the existing Encompass LOS and nCino infrastructure , reducing manual effort in the underwriting and document review workflows while keeping loan officers in control of every final decision.
Phase 1 focuses on building an AI-powered underwriting assistant that pulls borrower data from Encompass, analyzes eligibility across loan programs, and surfaces a clear recommendation with reasoning. Phase 2 extends this with a document intelligence pipeline that automatically parses, extracts, and validates borrower-submitted documents before a human touches them.
Phase 1
Intelligent loan eligibility analysis powered by Encompass data
The system connects to Encompass via API, pulls the full structured borrower profile , income, credit score, DTI ratio, employment history, loan type requested , and passes it through an AI reasoning layer. The output is a plain-English recommendation that tells the loan officer whether the borrower qualifies, for which program (Conventional, FHA, VA, USDA), and under what conditions. Everything stays inside their existing workflow.
Total estimated delivery: 14–20 weeks with 1 developer, or 7–10 weeks with 2 developers working in parallel.
Phase 2
Automated parsing, extraction, and validation of borrower documents
Borrowers upload income docs, bank statements, tax returns, and pay stubs through the nCino app. Right now, someone on the ops team manually reviews all of it. This phase builds an AI pipeline that reads every uploaded document, extracts the relevant data fields, cross-references them against what Encompass already has on file, and flags any discrepancies , before a human looks at anything. Based on prior experience, document processing time can be reduced by 40–60%.
Total estimated delivery: 16–22 weeks with 1 developer, or 9–13 weeks with 2 developers. Can start in parallel with Phase 1 after week 4.
Budget Overview
Combined estimate across both phases, including development and 12 months of operations.
What you'll need to buy
No labour costs. These are the actual tools, APIs, and infrastructure bills you'd pay monthly.
Encompass API and nCino API access are assumed to be included in Geneva's existing licenses. Confirm with IT before finalising.
Phases can overlap after week 4 of Phase 1, cutting overall calendar time without any added cost.
Next Steps
These need answers before final scoping and pricing can be confirmed.
Does the AI recommendation need to trigger any automated actions in Encompass, or is it advisory only? This significantly changes the architecture.
Is there existing historical loan data (approved, denied, conditioned) that can be used to calibrate the AI model's recommendations?
What is the average monthly loan volume across all branches? This directly determines AI API costs.
Which document types are highest priority , pay stubs, W2s, bank statements, tax returns? Parsing complexity varies significantly by type.
Are there specific compliance rules or internal underwriting guidelines already documented? These can be encoded directly into the AI prompts.
Who on the internal team will be the point of contact for Encompass API access and nCino credentials during development?
Is there a preference for cloud provider , AWS, Azure, or GCP , for hosting the AI pipeline and data processing infrastructure?