Simultaneous document processing
Entire loan package classified and extracted in parallel. FRS canonicalization maps all fields to a canonical schema regardless of format.
Use Cases
Loan Underwriting Automation
MightyBot executes loan underwriting end-to-end. Document classification, extraction, policy evaluation, credit memo generation. Days of manual work done in minutes.
Why MightyBot
MightyBot executes loan underwriting end-to-end — classifying documents, extracting data from complete loan packages, evaluating against lending policies, and generating credit memos with evidence trails. Days compressed to minutes. Not assisted. Finished.
Automate Loan Underwriting End-to-End
A commercial loan package: financial statements, tax returns, credit reports, appraisals, entity documents, guarantor information. An underwriter must cross-reference all of it, apply policies, calculate ratios, and synthesize a credit memo. MightyBot does this in minutes with full evidence trails.
The Problem
Manual underwriting creates three compounding failures.
Slow — complex commercial loans take days of data extraction,
spreadsheet building, and memo writing.
Inconsistent — two underwriters weight factors differently,
apply policies with different interpretations, miss different data points.
Unscalable — volume increases force a choice between headcount,
turnaround, or analysis depth. Financial statements arrive in different formats.
An LLM wrapper hallucinates on the numbers that matter most.
Format variability
Financial statements from Big Four, regional CPAs, internally prepared — all different
Multi-document cross-referencing
Tax returns, credit reports, appraisals, entity docs must reconcile
Policy application
DSCR, LTV, concentration limits vary by loan type and borrower
Ratio calculations
Financial ratios from scattered data across multiple documents
Credit memo assembly
Hours of manual synthesis into an auditable format
How MightyBot Executes
Deterministic policy evaluation
Your lending criteria in plain English. Evaluated identically every time. Underwriter inconsistency eliminated.
Credit memo generation
Structured memos with every data point linked to source via evidence pointers. Ratios shown alongside source line items. Ready for credit review.
Exception routing
Loans requiring judgment routed with full context. Underwriters focus on credit decisions. Edge cases handled.
Production Metrics
95% Reduction in underwriting processing time
99%+ Accuracy on document extraction and data validation
10× Throughput increase per underwriter
80% Fewer manual interactions per loan
100% Deterministic policy application across every loan
Before vs After
Loan underwriting automated end-to-end. Days become minutes.
Request a demoFAQ
Frequently Asked Questions
How does MightyBot handle different financial statement formats?
The Data Engine and FRS canonicalization process statements from Big Four firms, regional CPAs, internally prepared financials, and tax-basis compilations. Different formats, same structured output.
Can MightyBot enforce our specific underwriting policies?
Yes. Your criteria are authored in your credit team's language and evaluated deterministically. MightyBot ships with standard lending policies and layers your institution-specific rules on top.
What happens when a loan requires a policy exception?
The file is routed to the appropriate reviewer with policy triggers, extracted data, evidence pointers, and any conflicting information already assembled.
Does MightyBot support SBA and government-guaranteed loans?
Yes. SBA SOPs, USDA requirements, and other government program criteria can be encoded as policies with the same deterministic enforcement and evidence trails.
How long does deployment take?
Production deployments typically start within weeks. Integration, policy configuration, and document training can happen in parallel with your existing LOS in place.
What audit trail does MightyBot provide for examiners?
Every decision includes a why-trail linking directly to policies and source data. Examiners can move from any memo value to the original source page and extracted evidence.