Quest 14 of 15
Vendor selection and third-party AI risk
Selecting an AI vendor requires more than a product demo: banks must test data handling, resilience, model limits, contracts, and exit options.
Start here
This module builds on earlier parts, but every important idea is explained in context. Selecting an AI vendor requires more than a product demo: banks must test data handling, resilience, model limits, contracts, and exit options. As you read, connect each concept to the worked example and ask what a person must still decide.
Big idea
Selecting an AI vendor requires more than a product demo: banks must test data handling, resilience, model limits, contracts, and exit options.
Learn one idea at a time
Read, explore, then mark each idea when you can explain it.
Idea 1 of 8
Define the specific bank use case, data requirements, and risk tier before beginning vendor comparisons.
Choose a deep dive
Open the topics you want to explore. The detail stays folded until you need it.
Deep dive 1Evidence over demonstrations
Ask vendors to show tested controls, not only claimed accuracy. Banks need to know where data is processed, whether prompts train models, and how incidents are managed.
Deep dive 2Avoiding lock-in
A viable exit plan includes data portability, documentation, replacement timelines, and a safe fallback if the provider fails or changes terms.
Deep dive 3Worked example: Vendor selection and third-party AI risk
A chatbot vendor offers a low price but will not disclose its subprocessors or whether prompts are retained. A responsible response is: Require the missing evidence and risk review before any approval or pilot with real data. Correct: unresolved data handling risk blocks responsible adoption. Use this case to separate what the technology contributes from what people contribute. The team should compare the intended outcome with a baseline where applicable, record important assumptions, and keep a clear route to correct or stop the process.
Deep dive 4Local check for Vendor selection and third-party AI risk
Ask whether the examples, data, and assumptions fit your school, company, or community. Generic demos often miss local names, laws, connectivity, and languages.
Deep dive 5Vendor diligence before signatures
Ask where data is processed, how logs work, and how you exit the contract.
One-minute challenge
Connect this lesson to real life
Name one situation where this idea could help, and one thing a person should still check.
Explore a real-world example
Use the arrows to connect the idea to a visible situation.
Photo example
Third-party AI due diligence
Risk owners assess use, security, privacy, resilience, and contracts before a controlled pilot begins.
Key terms
Tap a term to flip and read the definition.
Optional further learningFree textbooks and trusted online resources
These sources informed the course structure. Use them to revisit a concept or study it in more depth.
Ready check
Tick each idea only when you could explain it without looking back.
Ready for practice? Write one question about whether customer data is retained or used for model training.
Extra context (audience, logistics, curriculum notes)
Built for: Banking and finance practitioners — no coding required.
Formats: Learn scroll · Practice interactions · Quiz · Optional chat lab
Module 14 — Vendor selection and third-party AI risk
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