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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 of Growth.Pro Data Science Training Academy | Data & AI Strategist Trainer
Jeyshalini Tevosha
AI Trainer | Empowering Businesses with Ethical & Impactful AI Solutions | Deepfakes | Generative AI | Prompt Engineering
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Peter Kua
Co-Founder of Growth.Pro Data Science Training Academy | Data & AI Strategist Trainer
Peter Kua is the cofounder and Chief Data Officer of Growth.Pro Data Science Consulting & Training. His responsibilities include finding ways data can be used as a competitive advantage as well as identifying new business opportunities with data. He also headed 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 face-to-face training which includes public masterclasses in Big Data Strategy for NTT Data, PAS Selangor, CIIF, PosAviation, Hitachi, FGV, Perodua, Maxis, SIRIM, and Principal Asset Management CIMB. In addition, he also trained several in-house Big Data Strategy workshops for organizations such as OCBC, Keysight, TNB, TM One, and Johnson & Johnson. During the MCO period, Peter conducted several 2-day Big Data Strategy public virtual classes for Citibank, Alliance Bank, Bank Islam, Intel, Osram, Dell, Sarawak Energy, Optics Balzers, Penang Port, and Maxis Broadband. Most of his audience who had attended his in-house and public classes are senior managers and above.

Peter’s core professional strengths include data science & big data strategies and thought leadership. His industry experience includes the media, internet, manufacturing, FMCG, e- learning and agriculture.
Jeyshalini Tevosha
AI Trainer | Empowering Businesses with Ethical & Impactful AI Solutions | Deepfakes | Generative AI | Prompt Engineering
Jeyshalini Tevosha is a distinguished Data & AI Consultant at Growth.Pro Data Science Consulting & Training, with a profound expertise in strategically harnessing data and Artificial Intelligence to drive impactful business outcomes. Set to graduate in 2024 with a Master’s in Applied Computing from the University of Malaya (UM), Jeyshalini has already built a strong academic and professional foundation, holding a BSc in Artificial Intelligence from UTeM and a Science Matriculation from Penang Matriculation College.

Her passion for education and training is evident through her certification as an HRDF Certified Trainer, a role she has excelled in since 2023. Jeyshalini’s training philosophy integrates academic rigor with practical industry insights, drawing from her diverse experiences as a Software Development Engineer at Curlec by Razorpay and as a Digital & Innovation Executive at Hong Leong Bank Berhad.

At Growth.Pro, Jeyshalini is not just a consultant but a key driver of AI innovation, specializing in curating data, designing robust AI models, and implementing cutting-edge training frameworks. She is adept at translating complex AI concepts into actionable business strategies, ensuring that AI models are finely tuned to meet specific business needs. Her work extends beyond technical execution; she is deeply committed to the ethical development and transparency of AI solutions, ensuring that the technologies she helps build are both responsible and sustainable.

Through her work, Jeyshalini has become a trusted advisor to organizations looking to leverage AI for competitive advantage, particularly in finance, engineering, and decision-making roles. By championing these principles, she strives to harness the power
of AI for real-world impact, contributing to the industry's evolution towards ethical and sustainable AI solutions.
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Asian Banking School
Machine Learning for Credit Scoring and Risk Management
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