 A conversation with Quants, Thinkers and Innovators all challenged to innovate in turbulent times!
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Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.
Bias, Fairness, and Accountability with AI and ML Algorithms
With Harsh Singhal from Wells Fargo
The advent of AI and ML algorithms has led to opportunities as well as challenges. In this paper, we provide an overview of bias and fairness issues that arise with the use of ML algorithms. We describe the types and sources of data bias, and discuss the nature of algorithmic unfairness. This is followed by a review of fairness metrics in the literature, discussion of their limitations, and a description of de-biasing (or mitigation) techniques in the model life cycle.
Harsh Singhal is Head of Decision Science and Artificial Intelligence Validation within the Model Risk group. His team is responsible for validating and approving all retail Credit Decision, Commercial Credit Rating, Financial Crimes & Fair Lending including Fraud and BSA/AML, Operations Risk, Marketing, and other artificial intelligence/machine learning models.
Prior to his current position, Harsh was responsible for new model development for Wholesale Risk in Bank of America. Harsh also led the Retail IRB model qualification at Bank of America and contributed towards the development of first generation of deposit balance models for Asset-Liability management.
Prior to joining the financial industry, he worked on quantitative modeling for pharmaceutical and telecom industries. He is passionate about developing quantitative talent and fostering a culture of responsibility and intellectual curiosity. His technical expertise includes machine-learning, multivariate analysis, commercial and consumer credit.
He has a Master’s degree in Electrical Engineering and a Ph.D. in Statistics.
Sri Krishnamurthy, CFA is the Founder and CEO of QuantUniversity. Sri is the creator of QuSandbox, a platform for experimenting analytical and machine learning solutions for enterprises prior to adoption.
Sri earned an MS in Computer Systems Engineering and another MS in Computer Science, both from Northeastern University and an MBA from Babson College.
The QuantUniversity Summer School 2021
 Join QuantUniversity for a complimentary summer speaker series where you will hear from Quants, innovators, startups and Fintech experts on various topics in Quant Investing, Machine Learning, Optimization, Fintech, AI etc.
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QuantUniversity is a quantitative analytics advisory focusing on the intersection of Data science, Machine learning and Quantitative Finance. We take a practitioner’s approach to working with pragmatic applications of frontier topics to real-world financial and energy problems. QuantUniversity advises various companies in Quant Finance application development, validation and in algorithmic auditing. We also run data science and machine learning workshops in the United States and online in its Explore-Experience-Excel series through QuAcademy. QuantUniversity is pioneering the next generation platform for Algorithmic auditing that supports anonymization, model escrow and tracking, synthetic data generation and experimentation through the QuSandbox.
