Katabat Releases Data-Driven Debt Collections Platform Powered by Machine Learning

1 min read

We are proud to announce the release of Katabat Engage, a new machine learning-powered product that delivers automated digital collections to our clients and the broader marketplace.

Katabat Engage helps lenders collect more through a platform of personalized, digital communications tailored to customer preferences. Powered by a proprietary machine learning platform, Engage enables lenders to deploy customized e-mail and SMS text collection messages and continuously tune customer outreach and response strategies.

Our CEO, Ray Peloso, recently did an interview with Thrive Global about how machine learning can improve the customer journey. Our data science team cut their teeth in Google Kaggle competitions and continue to demonstrate the power of the platform. The real excitement now is in discovering how powerfully our clients can leverage it.

We expect clients who use Engage will increase recoveries while offering a better customer experience and we look forward to publishing those results in the near future. In addition to collections, we look forward to Engage being used in both marketing and servicing, helping to:

  • Improve and increase contact rates.
  • Lower operating costs and compliance risk.
  • Service customers more efficiently.

We’ve already seen a great deal of early interest in Engage from several large lenders that are deploying the machine-learning software to support their debt-collection efforts.

We anticipate that they will benefit from the platform’s ability to learn from each customer interaction and quickly update and optimize strategies. Like most lenders, they 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, go here or send us a note at info@katabat.com.

Kelly Dickerson is Head of Product Strategy for Katabat.

Leave a Reply

avatar
  Subscribe  
Notify of
Share
Tweet
Share