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Overview

This one-day programme focuses on the application of machine learning in credit scoring and risk management within the financial domain (banks and financial institutions).
Participants will gain insights into credit scoring and risk assessment methodologies, explore data preprocessing and feature engineering techniques, and understand the application of various machine learning algorithms. The programme also covers model interpretability and explainability, presents real-world case studies in credit risk, addresses ethical considerations and fair lending practices, and concludes with a hands-on activity guiding participants in building a credit scoring model.
Programme Outline
Learning Objectives
By the end of the programme, participants will be able to:

  • Understand credit scoring and risk assessment principles in finance
  • Apply data preprocessing and feature engineering techniques for credit data
  • Implement machine learning algorithms for credit scoring
  • Interpret and explain machine learning models for credit risk
  • Analyse real-world case studies to gain practical insights
  • Navigate ethical considerations and promote fair lending practices
  • Gain hands-on experience in building a credit-scoring model

Programme Outline

  • Credit Scoring and Risk Assessment in Finance
  • Data Preprocessing and Feature Engineering
  • Machine Learning Algorithms for Credit Scoring
  • Model Interpretability and Explainability
  • Real-world Case Studies in Credit Risk
  • Ethical Considerations and Fair Lending
  • Hands-on Activity: Building a Credit Scoring Model
  • Q&A and Discussion
METHODOLOGY
Interactive group discussions, lectures, exercises, case studies and sharing of real-world experiences
Participant profile
Senior managers, managers, and executives from financial institutions
Trainer
Peter Kua
Co-founder & CEO of GradientX
Jeyshalini Tevosha
Data & AI Consultant at GradientX
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Peter Kua
Co-founder & CEO of GradientX
Peter Kua is the co-founder and CEO of GradientX. His responsibilities include finding ways data can be used as a competitive advantage as well as identifying new business opportunities with data. He also heads the Data Science team in REV Media Group (formerly known as Media Prima Digital) and was instrumental in driving the National Big Data Analytics Initiative under MDEC in the areas of thought leadership and industry development. He played a key role in developing the first National BDA Framework that delivered strategic recommendations and action plans to achieve the National BDA vision.

Peter has conducted training in areas that include public masterclasses in Big Data Strategy for NTT Data, PAS Selangor, CIIF, Pos Aviation Hitachi, FGV, Perodua Maxis, SIRIM, and Principal Asset Management CIMB. In addition, he also trained several in-house Big Data Strategy workshops for organisations such as OCBC, Keysight, TNB, TM One, and Johnson and Johnson. During the MCO period, Peter conducted several Big Data Strategy virtual classes for Citibank, Alliance Bank, Bank Islam, Intel, Osram, Dell, Sarawak Energy, Optics Balzers Penang Port, and Maxis Broadband. Peter’s core professional strengths include data science and big data strategies, web development and project management. His industry experience includes the media, internet, manufacturing, FMCG, e-learning and agriculture.
Jeyshalini Tevosha
Data & AI Consultant at GradientX
Jeyshalini Tevosha is a Data & AI Consultant at GradientX, where her expertise plays a pivotal role in strategically harnessing data and Artificial Intelligence to drive superior business outcomes. Currently pursuing her master’s in Applied Computing at UM, Jeyshalini is set to graduate in November, 2024. She holds a BSc in Artificial Intelligence from UTeM, Malaysia, awarded in 2022, complemented by a foundational education in Science from the Penang Matriculation College. She is also a HRD Corp Certified Trainer. Jeyshalini's previous roles include being a Software Development Engineer at Curlec by Razorpay and a Digital & Innovation Executive at Hong Leong Bank Berhad.
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Asian Banking School
Machine Learning for Credit Scoring and Risk Management
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