AIBCU Newsletter
Subject: Finding cross-sell opportunities with AI
October 5, 2026
In this issue
Use case
Using AI to find cross-sell opportunities
Industry news
- →The revised interagency model risk guidance
- →How large banks are measuring AI returns
- →Credit unions recognized for AI in member service
- →New survey data on AI adoption at banks and credit unions
Use case of the month
Lending & Credit
CRM Upsell Analysis
This prompt reviews a CRM export of existing borrowers against the products you want to promote. For each borrower with an opportunity, it recommends the next product to offer, when to reach out and through which touchpoint, and names the account fields behind the recommendation.
- →Input: a CRM export and your product list with eligibility rules
- →Output: a prioritized outreach list, talking points and a timing calendar
Industry news
Regulation
New model risk guidance leaves generative AI out of scope
The OCC, Federal Reserve and FDIC replaced their 2011 model risk management guidance in April. The revision explicitly excludes generative and agentic AI, so for now those tools are supervised through existing safety-and-soundness, third-party risk and consumer compliance expectations. The agencies have said a request for information on AI is to follow.
Read more at Sullivan & CromwellReturns
Banks start counting AI returns, not hours saved
Bank of America's CEO said the bank's 130 to 140 AI projects cost about $400 million and return about $800 million in benefits, and that the bank plans to double its AI budget next year.
Read more at PYMNTSCredit unions
Credit unions recognized for AI in member service
Heartland Credit Union and Alliant Credit Union were among four institutions recognized in Glia's 2026 Catalyst Awards. Glia reports Heartland saves more than 6,000 staff hours a year, and Alliant saw call volume fall nearly 20% year over year. These figures are vendor-reported.
Read more at Business WireResearch
Banks report higher back-office expectations for AI than credit unions
In CSI's 2026 Banking Priorities survey, banks were nearly twice as likely as credit unions to see AI's potential for back-office efficiency (38% against 21%). The same survey ranked AI-enhanced social engineering as the leading cybersecurity threat.
Read more at Business Wire