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Big Data Panel Session to be Held at ELFA Convention

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Date: Oct 09, 2015 @ 07:00 AM

On the opening day of the ELFA Convention, panelists from The Alta Group, Genpact and Equipment Data Associates will invite attendees to join them in mapping the customer journey through leasing, and in sharing ideas about how it can be re-energized using the latest analytical techniques, processes and “big data.”  Participants will examine the customer journey across the lending life cycle and how the science of big data and analytics can be deployed to transform key customer touch points defined as “moments of truth.”  The session will explore how the “big data” can be used to re-engineer business processes, provide valuable insights, stimulate business, and improve the customer experience.
 
Panelists will lead an interactive discussion offering fresh approaches and introducing new tools and methods for obtaining useful metrics, analyzing data, better understanding the needs of customers, and improving performance and effectiveness of processes. This presentation is designed to help companies re-energize their customers while also reducing the cost of acquiring and keeping them. 
 
The 11 a.m. Monday Oct. 26 session in San Antonio, Texas, titled "Re-Energizing the Customer Journey Using Big Data," features Paul Bent of Alta serving as moderator, and panelists Diwakar Singhal of Genpact and Mark McClanahan of Equipment Data Associates.
 
Bent is a senior managing director at The Alta Group whose background in computer science, law, and equipment leasing gives him unique insight into details of the important processes along the customer journey. Singhal is a senior vice president of Genpact with extensive experience in applying big data analytics and methods to corporate lending and finance. McClanahan is EDA’s manager of sales in financial services, whose focus is primarily in utilizing data analytics in financial sales and originations.
 
This program is especially timely in today’s marketplace, when formerly tried and true methods of analyzing customer needs and assessing the effectiveness of systems are rapidly giving way to predictive and analytical methods, tools, and techniques, particularly the application of big data methodologies, to drive greater margins, volumes, and customer satisfaction.



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