AI in a Singapore bank's contact centre
New to this industry?Start with its one-minute summary: Retail and commercial banking
| Use case | Agent hours affected a year | Share of time saved (%) | Feasibility (1 low to 5 high) |
|---|---|---|---|
| After-call summaries written by AI | 160,000 | 50 | 5 |
| Answer suggestions during calls | 320,000 | 15 | 3 |
| Chatbot that handles simple requests | 128,000 | 40 | 2 |
The prompt
A Singapore bank has 400 contact-centre agents. Each costs SGD 60,000 a year fully loaded and works about 1,600 productive hours a year. The team has listed three AI use cases (see the exhibit). Assume 80 percent of agents will use whichever tool is launched. Which should the bank start with, and what is it worth?
Interviewer-led: the interviewer shows the exhibit and asks the questions in order.
Practice with a partner
1. Send the interviewer link to a friend. They read the case aloud and hold the answers.
2. You open the candidate view: you see only the prompt, a timer and a notes box.
3. Speak the case out loud. Your partner shares data when you ask, then scores you with the rubric.
Interviewer view
For the person running the case
Candidate view
For the person answering the case
The exhibit
| Use case | Agent hours affected a year | Share of time saved (%) | Feasibility (1 low to 5 high) |
|---|---|---|---|
| After-call summaries written by AI | 160,000 | 50 | 5 |
| Answer suggestions during calls | 320,000 | 15 | 3 |
| Chatbot that handles simple requests | 128,000 | 40 | 2 |
My notes on this case
0 of 5,000 characters. Saves automatically.