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Artificial Intelligence & Data Science for Financial Services

Artificial Intelligence & Data Science for Financial Services

Advanced Machine Learning in Finance

The use of Data Analytics and Machine Learning (ML) / Artificial Intelligence (AI) in financial services is becoming increasingly popular. Their use has permeated the retail, commercial, corporate, and institutional banking sectors, as well as insurance and investment banks.

Across the various segments of the value chain of the financial services industry starting from loan / policy underwriting, product development, pricing, marketing, sales, distribution, claims, loan recovery, and customer service management, AI and ML techniques are being used to drive decision-making.

In this talk, we will begin with some of the use cases of the financial services industry where some of the popular fundamental techniques in the field of AI and ML are significantly utilised, discuss about the pros & cons and the technicalities involved in leveraging them. We will then shed some light on more advanced methods such as deep learning and graph neural networks and how even these are being used to unlock hidden value from data in the financial services industry.


Explainable and Responsible AI for Finance

Modern AI systems have successfully increased productivity and efficiency in organisational processes in banking and finance. While AI and ML usage is becoming more common in the financial services industry, the black-box nature of some AI systems has placed some roadblocks in the much more widespread adoption of AI, especially in the areas where regulatory supervision is essential. Furthermore, with the advent of tighter regulations in the use and movement of data in the financial services industry, it is becoming increasingly important to ensure that AI models that use data in making decisions that impact the customer follow the principles of fairness, ethics, accountability, privacy and security, and governance.

In the financial services industry, relevant members from loan and credit underwriting, account administration, policy management, claims administration, fraud detection, sales, marketing, and customer experience management teams frequently develop and/or use AI & ML models to make decisions, many a times focusing only on the higher precision and overlook the transparency of the solution. This talk is intended to increase the awareness of these members who use AI & ML to adopt responsible AI practices in their decision making. 

Join this seminar on 9 June 2022 for an engaging and mind-expanding discussion. See you there!

Audience

The seminar is suitable for participants working in banking/finance, regulatory sector and performing following roles: 

  • Data Analyst
  • Data Scientist
  • AI Expert
  • Regulators
  • Data Engineers
  • AI Product Managers
  • Data Science Product Managers
  • Underwriters
  • Pricing Actuaries
  • Head of Claims
  • Business Intelligence Analysts
  • Chief Data Officers / Chief Information Officers / Chief Information Security Officers
  • Data Protection Officers
  • Database Admins
  • Data Stewards
Date / Time / Venue
  • 9 June 2022, Thursday
  • 9:15 am - 12:15 pm (Registration starts from 9:00 am)
  • The seminar will be held in-person at: Institute of Systems Science, 25 Heng Mui Keng Terrace, Singapore 119615.
Free Admission Register Now  Registration ends
on Friday, 3 June 2022, 6pm 
Please email issmarketing@nus.edu.sg for enquiries.

 

Seminar Agenda


9am Registration 
9:15am Opening Remarks
By Dr Leong Mun Kew
Director, Graduate Programmes
NUS-ISS
9:30am DSAI Education Road Map to serve the Finance Industry
By Dr Rita Chakravarti
Chief, MTech Enterprise Business Analytics Programme
NUS-ISS 
9:45am Advanced Machine Learning in Finance
By Dr Stuart Wang
Senior Lecturer & Consultant, Data Science Practice
NUS-ISS
&
Dr Vishnu Nanduri, Adjunct Lecturer
NUS-ISS
 10:45am Tea Break (Light refreshments will be provided) 
 11:15am Explainable and Responsible AI for Finance
By Dr Tian Jing
Senior Lecturer & Consultant, Artificial Intelligence Practice
NUS-ISS
&
Dr Vishnu Nanduri, Adjunct Lecturer
NUS-ISS
 12:15pm  End of Event

Programme may be subjected to changes.



Speakers

 

Dr Leong Mun Kew

Director, Graduate Programmes, NUS-ISS
View Biography

Mun Kew is appointed as Director, Graduate Programmes of ISS. Prior to joining ISS, Mun Kew held multiple positions with the National Library Board, Singapore, as CTO, Deputy CIO & Director CIO Office, and Director, Digital & Knowledge Infrastructure Division. As Deputy CIO, he was responsible for governance and architecture and started ongoing efforts in master data management, enterprise architecture and corporate governance of IT. In particular, he designed a federated approach to EA that allows a gradual easing of operations oriented organisations into a business driven architecture, and started the Government EA Forum to promote practitioner sharing of EA pains and successes. 

 

Dr Rita Chakravarti

Chief, MTech Enterprise Business Analytics Programme, NUS-ISS
View Biography

Rita as a seasoned analytics professional has 25+ years of experience in Financial Services, Insurance and Market Research specialising in Scoring (operational & regulatory), Risk Management, Marketing Analytics, Analytics Strategy Development, Analytics Infrastructure, Analytics team management and training. Experience spans across Asia Pacific, Middle East, US & Canada.

 

Dr Stuart Wang

Senior Lecturer & Consultant, Data Science Practice, NUS-ISS
View Biography

Wang Cheng (Stuart) is a senior lecturer at the National University of Singapore's Institute of Systems Science (NUS-ISS). Prior to joining ISS, he held multiple positions (e.g. consultant, data scientist, head of data science and data & analytics lead) across health care, FMCG, gaming and fintech industries. He has global exposure from North America to Southeast Asia. He has published academic papers and is well versed in the commercial world. 

 

Dr Tian Jing

Senior Lecturer & Consultant, Artificial Intelligence Practice, NUS-ISS
View Biography

Tian Jing currently lectures in the Analytics and Intelligent Systems Practice in the areas of artificial intelligence, data analytics, and machine learning. He received his Ph.D. degree from School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.

 

Dr Vishnuteja Nanduri

Adjunct Lecturer, NUS-ISS
View Biography
Vishnu is a Data Science and AI leader with over 15 years of experience in Insurance and Financial Services, Climate change and Sustainability, and IT Operations Analytics. He has worked with clients across the US and APAC. He also worked as a professor at the University of Wisconsin-Milwaukee. He has designed and taught numerous courses for both University and the industry in Statistical Analysis, Operations Research, and Machine Learning.






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