2 of 13

Project Overview

Goal of the Project

Explore how AI can support internal training in a bank
Simplify complex workflows
Improve clarity in policies and compliance requirements
Create early prototypes for micro-learning

Focus Areas

Teller operations
Back-office processing
Compliance tasks
Policy interpretation

3 of 13

AI Tools Used

•-ChatGPT

•-Canva AI

•-Microsoft Copilot

•-Perplexity AI

4 of 13

ChatGPT Support

How ChatGPT Supported Training Design

Broke down operational workflows into simple steps
Explained internal procedures in plain language
Compared similar processes and highlighted conflicts
Suggested examples of reporting and escalation
Drafted early training elements (practice cases, Q&A, explanations)

Value

Faster early drafting
Clearer instructional content

• Easy adaptation into micro-learning

5 of 13

Role of Canva AI

Simulated internal system interface variations
Provided layout ideas for visual-heavy training content
Helped simplify complex workflow descriptions
Suggested diagrams and visual structures

Impact

Faster layout planning

• More user-friendly training visuals

6 of 13

��Microsoft Copilot

Uses in Internal Document Processing
Summarized internal policies
Highlighted essential procedural steps
Compared updated versions of internal documents
Improved clarity for training teams handling long policy files
Purpose
Support internal policy training, not replace compliance review

7 of 13

Perplexity AI

How Perplexity AI Helps
Organized fragmented compliance information
Highlighted relevant sections when policies overlap
Helped locate which internal rule applies to a specific task
Important Note
Supports navigation of internal information
Does NOT interpret laws or generate new regulatory guidance

8 of 13

��

(Insert the Exploratory + Charting Workflow Image)
Why This Matters
Matches how AI was used throughout this project
Seed → Explore → Structure → Refine → Integrate → Validate
Ensures clarity, consistency, and compliance during design

AI Workflow Framework

9 of 13

�Four-Part Training Structure

1 Internal Operational Procedures

2 Risk-Control Requirements

3 Internal Policy Requirements

4 Local Regulatory Requirements

10 of 13

Internal Operational Procedures

Documentation checks

Data entry

System steps

Approval workflows

Risk-Control Requirements

KYC, AML, Sanctions screening, Red flags

Identity verification

Detect inconsistencies

Mandatory compliance checks

Internal Policy Requirements

Standardized procedures

Reporting obligations

Policy interpretation

Applying internal rules while following local laws

Local Regulatory Requirements

Legal procedures

Customer protection standards

Reporting timelines

Requirements overriding internal policy when necessary

11 of 13

AI-Supported Training Module Concept

AI can support internal training teams by:

Explaining rules in simple terms
Shortening long policy documents into readable summaries
Providing examples of correct vs. incorrect actions
Identifying steps that cause frequent mistakes

• Suggesting escalation points

12 of 13

��

1. Short Explanation Cards

“3 checks before approving a transfer”
“When to escalate a KYC inconsistency”

2. Quick Scenario Questions

Mismatched IDs – next step?
Head office asks for unnecessary documents – what to do?

3. Step-by-Step Guides

Customer data entry
Risk review sequence

4. Simple Practice Quiz Items

Identify incorrect steps
True/false compliance checks

Micro-Learning Prototypes

13 of 13

Reflection on Learning

AI supports breaking down complex banking tasks
Speeds up early-stage training design
Helps produce clearer and more consistent explanations
Useful for micro-learning and daily operational support
Training must evolve because front-line banking challenges change constantly

• AI can assist—but not replace—human judgment in compliance and operations