Swapnil Awasthi
BARCLAYS BANK, Citigroup, University of South Florida, Aberdeen Asset Management
About
I completed my Bachelor’s in Computer Science & Engineering in 2008 and began my professional career as an application developer with IBM in October 2008. After spending nearly eight years in corporate roles, I felt the need to return to academics to pursue my growing interest in data science. I took a break from industry and earned my Master’s degree in Business Analytics and Information Systems from the University of South Florida in 2016. I also got an opportunity to work as a student assistant in statistics helping undergrad students with statistical problems and concepts.
Over the past decade, I have worked extensively in fraud strategy, risk analytics, and governance frameworks at leading financial institutions and technology companies like Aberdeen Asset Management, Citibank and Barclays. I managed acquisition underwriting for ~2B portfolio, and ECM programs like proactive line increase (~500mn annually) and customer initiated line increase for around ~1.3mn customer base.
I also developed and managed fraud strategies across the products and portfolios totaling over $40bn of dollar exposure and > 5mn customer base.
These experiences sharpened my expertise in AI/ML driven data extraction, modeling, visualization, and predictive analytics, while highlighting the transformative potential of advanced research to detect fraud, optimize credit risk, and improve decision-making.
Employment
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BARCLAYS BANK Assistant Vice President2023 - Present
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Citigroup Vice President2021 - 2023
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Aberdeen Asset Management Data Scientist2019 - 2021
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DataRobot Data Scientist2018 - 2019
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University of South Florida Student Assistant2017 - 2017
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CenturyLink (India) Senior Software Engineer2011 - 2016
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IBM (India) Application Developer2008 - 2011
Education
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University of South Florida MS - Business Analytics and Information Systems2016 - 2017
Projects & Funding
Projects & funding information is unavailable.
Publications (3)
- Synthetic Identity Fraud in U.S. Payments: Economic Costs, Risk Classification, and the ROI of Graph-Based Detection Save
- Synthetic Identity Fraud in U.S. Payments: Economic Costs, Risk Classification, and the ROI of Graph-Based Detection Save
- Adverse-Action-Ready Explainable AI for Credit Underwriting: Predictive Lift vs. Regulatory Specificity Save