COURSE · PHASE 2
Data, AI and Decision Accountability
This practical, scenario-led workshop is built for Banking organisations and focuses on accountable decisions supported by data and AI. Participants work with a fictional bank team handling customer-case prioritisation to scrutinise evidence, document decision rationale, retain human decision authority, and strengthen oversight. The course develops repeatable decision practices around evidence quality, bias, accountability, and human judgment. It does not cover technical AI implementation or tool selection.
FROM THE CURRENT BROCHURE
Know what the experience covers before you download.
These highlights are drawn from the current approved course brochure and are designed to support an informed first conversation.
COURSE HIGHLIGHTS
The capabilities and outcomes in focus.
- 01
Understand how data and AI can support decisions while leaving responsibility for human judgment, context, values, and accountability with decision-makers.
- 02
Identify where decision inputs need additional scrutiny and where accountability risks remain when data or AI informs the decision.
- 03
Document decision rationale so evidence, limitations, authority, reasoning, and review support trust, auditability, learning, and responsible action.
- 04
Judge whether human judgment in an AI-augmented decision process is real and identify the practical changes that restore it.
WHAT YOU'LL EXPLORE
A clear route through the key topics.
- 011.1 Role and Limits of Data and AI
- 022.1 Evidence Quality, Bias, and Accountability
- 033.1 Traceable Decision Rationale
- 044.1 Human Oversight in Practice
- 05INTEGRATION, OUTCOME CHECK, AND CLOSE