News

Fiserv announces availability of Predictive Scores modeling solution based on big data

FiservFiserv announced on Thursday the availability of Predictive Scores, a new predictive modeling solution for customer behavior that uses multiple data sets.

The solution uses customer data to provide a complete view of a relationship based on account-level data, debit card and electronic bill pay usage and online and mobile banking activity.

“The unique combination of data science and big data is what sets our solution apart,” Danny Baker, the vice president of financial and risk management solutions at Fiserv, said. “It provides financial institutions with extremely valuable insights that can lower their direct marketing production costs – by almost 50 percent for some clients. The knowledge gained from Predictive Scores provides more accurate, detailed support for building and managing customer-centric growth strategies, particularly for acquiring new customers and expanding existing relationships.”

Fiserv is able to provide clients with direct marketing strategy and customer insight to help drive growth.

“Predictive Scores can be aimed at many different customer segments and offerings,” Baker said. “Adding the intelligence gained from Predictive Scores to existing customer data and then enabling financial institutions to use this data to increase customer adoption of our leading online, mobile, card, person-to-person payment and electronic bill pay offerings for the financial institution really encapsulate the holistic Fiserv approach that we know our clients are asking for.”

Additionally, the solution can be used to boost response rates and return on investment of direct marketing campaigns, encourage the adoption of digital banking tools to expand product sales and to identify prospective customers.

Predictive Scores works as an in-house solution and through software-as-a-service accessed through Fiserv’s Intelligent Workplace, which supports the Prologue Financial Accounting Services suite, Credit Risk Modeler, Trend Modeler and Prepayment Modeler.

Comments are closed.