Session 10-G

How to leverage insights engine for personalized and actionable recommendation in financial domain?

← Back to Agenda

Customers today receive personalized recommendations across several domains including e-commerce, entertainment, and travel. This degree of customization, however, is still nascent in the financial industry with the current standard being heavily reliant on user surveys. With the power of Insights Engine, financial industry can harness the treasure of transaction data to create highly personalized, conversion focused customer engagement. Insights Engine leverage transactions enhanced by algorithms based on lookalike modeling, BNP techniques and temporal clustering to generate customized insights. The Insights Engine generates comprehensive, temporally evolving, and granular trends based entirely on the transactions in the account. Sample attributes for trends can include financial behavioral preferences in spending habits, lending, and cash flow predictions that enable personalized and actionable recommendations for Financial Service Providers (FSP) and account holders. IE can drive data-driven personalization needed for consumers to find and access tools in for their financial wellness. In this talk, we will explore how the Insights Engine provides timely recommendations, reduces costs to democratize access to financial products for all users. We will also dive into the comprehensive tech stack that powers IE, leveraging over than a dozen deep learning algorithms to process 80 million+ transactions daily, generate real-time insights, and make them easily consumable for clients to be utilized into apps, banking portals or existing customer engagement tools.



Chief Analytics Officer, Vice-President Data Sciences and Analytics, Envestnet Yodlee