Automating the Credit Memo: A Standardized Borrower Summary for Faster Decisions
I designed and built a working prototype of “MemoMind” to demonstrate how AI can compress a full-day credit-memo workflow into a focused hour. In plain terms, a credit memo is the concise lending decision brief that distills a borrower’s story, risks, and recommendation. This client was seeking ways to implement more effective tools within their organization. This was just one in a series of prototypes to showcase how AI can be a multiplier for their team.
Challenge
Sarah Chen, a Senior Credit Analyst, had three memos due by EOD with data split across spreadsheets, PDFs, and past memos. Manual extraction, formatting, and risk reviews made speed and consistency tough to achieve.
Solution
The prototype ingested financial statements, bank statements, credit reports, and prior memos, auto-extracting key ratios and selecting an industry template to generate a standardized first draft. Sarah added meeting notes, reviewed flagged risks and peer comparisons, and finalized the memo—validating that the tool augmented judgment rather than replacing it.
AI-First
Using NLP, template learning, automated narrative generation, and inconsistency detection, the prototype standardized risk frameworks while surfacing anomalies with peer benchmarks.
Outcome: Sarah completed her first memo in just over an hour and finished all three before 3 PM—reducing manual data entry and errors while improving consistency and confidence in the analysis.