Live virtual course | Agenda timing is in HKT/SGT
Respective time in AEST:
09:00 – 10:00
Overview of alternative data (alt data)
- What is alt data?
- Classification of alt data
- Data source
- Comparing traditional data and alt data: the difference and advantages
- Current applications of alt data in financial organizations
- How alt data is changing the financial industry?
10:00 – 11:00
Alternative data and credit assessment
- Employing alt data in credit assessment: what are the benefits?
- Becoming the credit ‘visible’
- How alt data help to predict credit risk
- The application of artificial intelligence, machine learning and deep-learning
- Potential challenges of using alt data in credit assessment
Credit Risk Manager
New Development Bank
Sidharth Kamani is an FRM certified Risk professional. He currently manages Credit Risk at New Development Bank, a multilateral institution founded by the Governments of the BRICS countries. At NDB, he is responsible for credit appraisals and pricing of the bank's lending products in hard currencies and in local currencies. Prior to his current role, he worked with Goldman Sachs in the Market risk and Treasury functions, where he gained hand-on experience working on various risk regulations such as CCAR, LCR and NSFR. Sidharth's interests lie in the areas of international finance, sovereign risk analysis, infrastructure financing and the evolving landscape of digital finance.
11:00 – 11:15
11:15 – 12:15
Alternative credit scoring model
- What is alternative credit scoring?
- Alternative credit scoring vs. conventional credit scoring
- The framework of alternative credit scoring
- Alternative credit data sourcing
- Assessing the creditworthiness
- Case study
Raja Debnath is a Growth Hacker in MSME and Retail Banking and has advised over 40 financial institutions and Fintechs globally in the areas of Retail & SME Banking Digital Transformation, Data Analytics, Supply Chain Finance and Non-financial Services. He is the Managing Partner at Cogence Labs - a full-service technology enabled management consulting firm exclusively focused on advising FIs on Retail and MSME Banking. He is also the Co-Founder of two technology firms that provide enterprise applications in Lending, DW-BI, SCF to the BFSI sector.
Prior to this he was the Senior Global SCF and SME Banking Advisory Specialist for Asia at International Finance Corporation after having advised banks extensively across the Middle East, and Central Asia. Prior to that he was with EY, India as a Consumer and SME Banking Specialist. Earlier he had setup the Micro and Small Enterprise Unsecured Lending Business at Kotak Mahindra Bank in India.
He is an Advisor for the SME Finance & Alternative Data Certification program at London Institute of Banking and Finance. He holds an MBA from the Said Business School at Oxford University and an MBA from Jamnalal Bajaj Institute of Management Studies (JBIMS) at Mumbai University.
09:00 – 10:00
Managing alternative data set
- Data sourcing and due diligence
- Modelling and justifying the unstructured data set
- Accelerating data evaluation
- Maximizing the data value and avoiding potential missteps
- Privacy-enhancing technologies (PETs)
10:00 – 11:00
Machine Learning and alternative data
- Developing machine learning models
- Textual analysis and data processing
- Sentiment analysis
- Seasonality testing
- Assessing the pattern of behavior
Professor, Department of Mathematics and Information Technology
The Education University of Hong Kong
Philip Yu is a Professor at Department of Mathematics and Information Technology of The Education University of Hong Kong, and Honorary Professor, Department of Computer Science, The University of Hong Kong. Before joining the Education University of Hong Kong, he worked at the University of Hong Kong and was the Chairperson of the Asian Region Section of the International Association of Statistical Computing, the Vice President of the Hong Kong Statistical Society, and a member of the Technical Committee of Computational Finance and Economics, IEEE Computational Intelligence Society. He is an associate editor of Frontiers in Artificial Intelligence, Digital Finance, and Computational Statistics. The Hong Kong FinTech Index Project led by him is the first in the region to provide information in a timely manner to track the growth and development of the FinTech industry in Hong Kong. His research interests are broad; they include AI and big data analytics, non-parametric inference, ranking methods, time series analysis, financial data analysis, risk management and statistical trading. He has a substantial volume of work on most of these topics, including two co-authored books on nonparametric statistics and more than 120 publications in conference proceedings and professional journals.
11:00 – 11:15
11:15 – 12:15
Alternative data and ethical AI
- Application of AI in alternative data analysis
- What is Ethical AI
- How to establish governance for ethical AI
- Key Takeaways
09:00 – 10:00
Mitigating the data risks
- Strategic risk: Does alternative data lead to reliable business insight
- Privacy risk: How to comply with privacy regulations
- Regulatory risk: Copyright, intellectual property and other potential pitfalls
- Model risk: The struggle to ensure the validity of a unique alt data set
10:00 – 10:15
10:15 – 11:15
Looking ahead: the rise of alternative data in Covid-19 era and future
- How alt data help understanding the impact of Covid-19?
- The alt data ecosystem
- Alt data and future technology development
- Environmental, social and corporate governance (ESG) analysis
Karen is a Consulting Director in the advisory practice of PwC Hong Kong. She has over 11 years of professional experience in both banking and risk management consulting services to local, mainland and international banks. Karen has extensive hands-on experience in IFRS 9 implementation, credit risk model development and validation, Basel II planning / implementation, stress testing, rating and credit process, portfolio management and compliance assessment. Prior to joining PwC, she worked on a range of business analytics and sales management projects focusing on predictive modelling, customer experience, marketing campaign management and liquidity control. Her technical competencies include a deep knowledge of statistical and data mining techniques using SAS, R, Tableau, VBA and Python.
Karen holds a Master degree from the Chinese University of Hong Kong in Risk Management Science and a Bachelor degree from the Hong Kong University of Science and Technology in Finance and Information Systems. She is a Chartered Financial Analyst and Certified FRM.