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Leveraging PETs for Generative AI and Consortium Applications in Financial Services

June 5, 1:30 PM - 1:50 PM
Imperial Room A

As a part of the Canadian financial ecosystem, EY has been leading the application of Privacy Enhancing Technologies (PETs) for a) Generative AI applications for financial services and b) data consortium applications for financial services. We will discuss some use-case applications for Generative AI (such as contact center support for financial services, automated code generation, complaints handling, automated model documentation, etc.) and how EY has been leveraging PETs to ensure data privacy and security during its Gen AI applications in financial services. Technologies referenced will include Open AI, Microsoft Azure, Python, and other relevant tools. Further, we will discuss one of the first consortiums in Canada, finally moving to real-world applications in the field of anti money laundering. The technologies leveraged will include confidential computing (TEE), differential privacy, synthetic data generation, and end-to-end Gen AI evaluation (governance framework). Also included will be privacy testing framework and controls (PII sanitization, differentially private fine-tuning, privacy penetration testing), Hallucination (Retrieval relevance, response relevance, and faithfulness), performance testing (e.g. BERTscore, ROUGE), and content filtering. We will talk about practical challenges in these applications and our approach to solving them.

About the speaker

Vishal Gossain

Vishal Gossain

Partner, EY

Vishal Gossain has 20+ years of work experience gained by holding various modeling and risk strategy roles in the US, Canada, and Latin America. He currently leads the banking sector for risk consulting in EY Canada, where he acts as a "CRO" by designing risk solutions for his banking clients across credit risk, market risk, actuarial risk, financial crime risk, regulatory compliance, and conduct risk, process and controls risk, emerging risks, risk technology, ERP and risk architecture.

His most recent experiences included being Vice President of Global Risk Management at Scotiabank, where he was responsible for building lending models for all Canadian, Caribbean, and Central America retail (unsecured and secured) and small business lending portfolios for Scotiabank ($200+ b in receivables). He also oversaw retail regulatory models (IFRS9 and AIRB), and money laundering models globally across all asset classes (retail, commercial, capital markets, and wealth management) by leading a team of up to 125 members during his tenure. Some of his noteworthy earlier experiences include being head of credit risk for HSBC in Latin America, where he had overall second-line responsibility for life-cycle credit risk strategies across Mexican retail and small business secured and unsecured portfolios. He was also head of credit risk management at Capital One Canada, where he was accredited as a credit offer with credit lending authorities, and several risk management roles in the US at Capital One and HSBC, managing unsecured products up to $8 billion (US) in receivables from a credit risk perspective (co-branded and branded, omnichannel and full spectrum lending).

Vishal is also an avid champion of artificial intelligence and machine learning (AI/ML). He served on the board of the Machine Learning Applications of Systems That Learn Program at Massachusetts Institute of Technology (MIT)'s Computer Science and Artificial Intelligence Laboratory and as Scotiabank's representative for the Real-time Secure Explainable Systems (RISELab) at the University of California at Berkeley and at Vector.AI in Canada.