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Predicting Servicing Issues Before they Happen

On Wednesday, Black Knight launched its Actionable Intelligence Platform (AIP). The platform, with its extensive data assets and decision-quality analytics, will help the mortgage industry grow its revenue, improve efficiency, and reduce risk, according to Black Knight.

The new platform is a unified delivery system which integrates Black Knight’s data, analytics, and technology solutions to provide actionable intelligence for mortgage lenders and servicers.

"Through the AIP we can deliver Black Knight's data and analytics across the entire loan cycle and at every level of the organization. From pre-origination, and origination to servicing and default servicing we have a 360-degree view of the customer lifecycle through this platform," Tyler Sherman, President, Enterprise Business Intelligence Division at Black Knight, told DS News.

Speaking about how the platform helped servicers with default servicing, Sherman said that the AIP helped clients in three categories—generate and protect revenue,  improve operational efficiencies, and supporting compliance efforts. Giving an example of how the AIP worked to predict loan analytics, Sherman said, "Through the AIP lenders can monitor loans that have a high exposure to natural disasters or are in a flood zone but currently do not have a flood insurance. From a high level, the executives would look at the entire portfolio while employees would use the AIP to look at a loan by loan exception as well as the portfolio to monitor the flood zones across the country and any changes that could lead to issues in the future."

Giving the difference between AIP and a production system, Sherman said that the AIP platform tracked, monitored, and suggested the right action and the right task to do at the right time, but doesn't do the task."

Speaking of the platform's predictive analytics, Sherman said that on the servicing side, the AIP had the ability to predict a customer's propensity to transact. "We know within 30-90 days the likelihood of a new consumer obtaining a new mortgage or refinancing their existing mortgage based on our algorithms and models within the AIP," said Sherman. "We can predict almost a year out the likelihood that someone will transact on a new home. This helps the servicer get ahead of the game and start to contact the homeowner through their customer service department or origination arm to retain the client."

The costs of servicing would also reduce through AIP, according to Sherman. "We're eliminating bottlenecks and predicting problems before they occur, which reduce the cost of origination and servicing."

About Author: Radhika Ojha

Radhika Ojha is an independent writer and copy-editor, and a reporter for DS News. She is a graduate of the University of Pune, India, where she received her B.A. in Commerce with a concentration in Accounting and Marketing and an M.A. in Mass Communication. Upon completion of her masters degree, Ojha worked at a national English daily publication in India (The Indian Express) where she was a staff writer in the cultural and arts features section. Ojha, also worked as Principal Correspondent at HT Media Ltd and at Honeywell as an executive in corporate communications. She and her husband currently reside in Houston, Texas.

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