Global software provider Katabat has released Katabat Engage.
The system which data-driven debt collections powered by machine learning to consumer lenders
Katabat Engage helps lenders collect more dollars through a platform of personalized, digital communications tailored to customer preferences.
Powered by a proprietary machine learning platform that has performed well in Google Kaggle competitions, Engage enables lenders to deploy customized e-mail and SMS text collection messages and continuously tune customer outreach and response strategies, a release stated.
“We are very excited to present Engage to our clients and the broader marketplace,” said Katabat CEO Ray Peloso, who recently did an interview with Thrive Global about machine learning. “Our data science team has built a mature and reliable data pipeline for machine learning and continues to demonstrate the power of the platform through its success in several Google Kaggle machine-learning competitions.”
Katabat expects that clients who use Engage will increase recoveries while providing a positive customer experience. They also expect the new machine learning product to be used beyond debt collections to include both marketing and servicing, helping to increase contact rates, reduce operating costs and compliance risk, and service customers more efficiently, the release stated.
“We’ve already seen early interest from several lenders that are deploying the product to support their collections efforts,” said Katabat Head of Product Strategy Kelly Dickerson. “Our Engage clients will benefit from the platform’s ability to learn from each customer interaction and quickly update and optimize strategies. Clients want a product that meets stringent regulatory and compliance standards while saving them the cost and time of developing and testing software like this on their own.”
For more information on Katabat Engage, click here.
Katabat is a global, SaaS-based Customer Experience Management (CXM) software provider headquartered in Wilmington, with offices in the United Kingdom and Australia.
