Bhavik Shah
About Bhavik Shah
Bhavik Shah is the Director of CCAR Stress Testing and Interest Rate Risk at UBS, where he has worked since 2019. He has extensive experience in financial analysis and risk management, having held positions at Citi, GE Capital, and Bloomberg.
Work at UBS
Bhavik Shah has been serving as the Director of CCAR Stress Testing and Interest Rate Risk at UBS since 2019. In this role, he has focused on enhancing the efficiency of the CCAR submission process, successfully decreasing the submission time by five days through various automation projects. Prior to his current position, he worked as an Associate Director at UBS from 2016 to 2019, where he contributed to the organization’s risk management strategies.
Previous Experience at Citi
Before joining UBS, Bhavik Shah held the position of Vice President of Forecasting and CCAR at Citi for 11 months in 2015-2016. In this role, he was involved in forecasting and risk assessment, contributing to the bank's compliance with regulatory requirements.
Career at GE Capital and Bloomberg
Bhavik Shah worked at GE Capital as a Senior Treasury Analyst from 2014 to 2015, where he focused on treasury operations. He also spent several years at Bloomberg, first as an Equity Fundamental Analyst for seven months in 2009-2010, and then as a Research Analyst from 2010 to 2014. His experience at Bloomberg involved analyzing equity markets and providing research support.
Education and Expertise
Bhavik Shah earned his Master of Business Administration with a focus on Corporate Finance from Pace University Lubin School of Business, completing his studies from 2007 to 2009. He also holds a Bachelor's degree in Computer Engineering from Dharamsinh Desai University, where he studied from 2001 to 2006. His educational background supports his expertise in finance and risk management.
Achievements in Risk Management
Bhavik Shah has made significant contributions to risk management practices, including the creation of a 1000-step CCAR Checklist to ensure successful submissions to the Federal Reserve. He established a complex data feed/load process in QRM, integrating multiple front office feeds, and introduced improved mortgage rate equations for forecasting. Additionally, he implemented a framework for sensitivity scenarios in QRM to provide comprehensive results on net interest income and other comprehensive income impacts.