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approach-debt-bgs

Practical approach to Machine Learning based debt collection strategy in production

Date: Jul 10, 2019
Time: 11 AM – 12 PM EDT America/New_York
LOCATION: Webinar

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About The Webinar


According to recent reports from the Federal Reserve Bank of New York credit card, household debt and auto-loans delinquency rates have been slowly rising, hitting a 7 year high recently. It’s no wonder then that banks and lending organizations are looking to AI to make debt collection smarter and easier. Citizens Bank, based out of US, have been leveraging AI in their recovery processes to improve their collections and reduce delinquency rates.

In this webinar, Nate Spiegel – Vice President of Process Improvement and Change Execution at Citizens bank and Ashish Khandelwal – Director of Product Management at EdgeVerve share their insights on

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Speakers

Nate Spiegel

VP, Process Improvement & Change Execution, Citizens Bank

Nate Spiegel leads improvement and strategy focused initiatives for Citizens Bank’s Consumer Loan and Specialty Operations. Bringing over 12 years of engineering, program management, and change execution experience in the financial services and manufacturing industries, Nate ensures that Citizens is constantly evaluating and integrating cutting-edge FinTech and industry best practices into its operational model for optimal efficiency, effectiveness, and competitiveness in today’s market.

Most recently, Nate has led a collaborative initiative with EdgeVerve aimed at leveraging machine learning to optimize the performance of Citizens’ collection strategies.

Ashish Khandelwal

Director - Product Management, EdgeVerve

Ashish Leads Product Management and Research effort, at Edgeverve, for Business Applications in Lending Domain. Ashish brings in over 18 years of experience with focus on building product and application for Lending Industry. He has been with Infosys Ltd. for over a decade in various capacities, working closely with the Product Team to build the products from scratch as well as with the clients across the world, customizing and implementing those products to the client’s specific needs

Currently, he is responsible for incubating new products, with an intense focus on solving traditionally challenging problems in lending with the application of advanced techniques in Machine Learning and Natural Language Processing.