Artificial Intelligence & Data Science for Financial Services

Artificial Intelligence & Data Science for Financial Services

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Institute of Systems Science

25 Heng Mui Keng Terrace

Singapore, 119615


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This seminar explores usage of Machine Learning and Artificial Intelligence in the financial services industry.

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Advance 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 utilized, 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.

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