AI for Bank Relationship Managers Quiz

Answers and explanations appear as you take the quiz.

1. In an RM assistant built on retrieval-augmented generation, when should access-control filtering happen?
   • After the model writes its answer, by redacting sensitive words
   • Before retrieved text reaches the model
   • Only when the banker exports the briefing
   • Once a month during an audit
2. Why does the guide recommend computing credit memo figures deterministically and inserting them as fixed values?
   • Credit committees refuse to read AI-generated narrative
   • It prevents the language model from inventing or miscalculating financial figures
   • Deterministic numbers are required by suitability rules
   • It lets the model skip reading financial statements
3. What does a well-designed next-best-action system do?
   • Automatically sells products to clients without the banker
   • Replaces the banker's quarterly client reviews
   • Presents options with reasons, leaving the banker to decide whether they fit
   • Ranks bankers by how many products they sell
4. Which constraint specifically prevents material non-public information from flowing between teams in an RM tool?
   • Information barriers
   • Contact frequency limits
   • Model drift monitoring
   • Data retention schedules
5. What public example does the guide give of an AI assistant for advisors?
   • A chatbot that approves mortgages for retail customers
   • Morgan Stanley's GPT-4-based assistant that answers from internal research and procedures
   • A central bank tool for supervising relationship managers
   • A trading algorithm that executes client orders
6. Why is a credit memo described as a control document?
   • It controls the bank's marketing budget
   • It sets the client's account permissions
   • Credit committees rely on it to decide loans, so errors can lead to poor lending decisions
   • It is automatically filed with regulators
7. Besides propensity models, what do next-best-action systems typically combine to produce suggestions?
   • Business rules such as eligibility, suitability and contact frequency limits
   • Random selection of products to avoid bias
   • Only the banker's sales targets
   • Social media sentiment about the bank
8. Why should next-best-action systems log each suggestion, its features and whether the banker acted?
   • To calculate banker bonuses automatically
   • To support model monitoring and conduct review
   • To send the log to clients each month
   • To train the model to ignore banker decisions