Fintech/Virtual Assets

Fintech - Part 7

Overview

This eCourse comprises two modules on AI Applications in Credit Risk.

Financial institutions are increasingly leveraging AI to transform both retail and corporate credit processes. For retail lending, AI accelerates credit decisions, personalizes offers, and improves risk prediction through advanced machine learning (ML) models that analyze vast datasets. Generative AI and large language models (LLMs) further enhance underwriting, automate document review, and craft tailored loan terms.
In corporate credit, AI moves beyond static spreadsheets to deliver real-time insights from complex financial data. Traditional statistical models are now complemented by modern ML/AI tools that detect early warning signals, uncover hidden correlations, refine risk ratings, draft credit memos, and strengthen portfolio monitoring..

Module 1 describes how AI is being leveraged throughout the entire retail credit lifecycle, from rapid approvals to dynamic portfolio monitoring and more.

Module 2 describes how AI is helping to transform corporate credit risk assessment, covering traditional ML techniques as well as more recent developments such as generative AI and LLMs.

Objective

On completion of this course, you will be able to:
- Recognize the role of AI in enhancing retail credit risk assessment
- Identify how AI, including both machine learning (ML) and generative AI/large language models (LLMs), is used for credit origination and underwriting
- Recognize other areas where AI can add value for lenders and improve the efficiency and effectiveness of their retail credit business
- List the key benefits and limitations/challenges associated with using AI for retail credit risk assessment
- Recognize the role of AI in enhancing corporate credit risk assessment
- Identify the traditional machine learning (ML) techniques that lenders use to assess credit risk
- Identify how more modern AI tools, notably generative AI and large language models (LLMs), are being used to supplement traditional ML approaches
- List the key benefits and limitations/challenges associated with using AI for corporate credit risk assessment

Content Highlight

Module 1 - AI Applications – Retail Credit Risk
Topic 1: AI & ML Techniques in Retail Credit Risk
Topic 2: Credit Origination & Underwriting
Topic 3: Other AI Applications for Retail Credit
Topic 4: Benefits & Drawbacks of AI Tools

Module 2 - AI Applications – Corporate Credit Risk
Topic 1: AI & ML Techniques in Corporate Credit Risk
Topic 2: Traditional Machine Learning (ML) Techniques
Topic 3: Modern AI Tools
Topic 4: Benefits & Drawbacks of AI

Administrative Details

Code
TEPFT25003901
Venue
ePlatform
Relevant Subject
Type 1 - Dealing in securities
Type 2 - Dealing in futures contracts
Type 3 - Leveraged foreign exchange trading
Type 4 - Advising on securities
Type 5 - Advising on futures contracts
...More
Language
English
Hours
SFC:2.00, PWMA:2.00
Fees
All Member: HK$640
Chinese Securities Association of Hong Kong (HKCSA): HK$670
Non-Member: HK$960
Staff of Corporate Member: HK$640