logo
  • Home
  • Blog-Navigation
  • Art
  • About
  • Contact

Machine Learning for Debt Collection and Recovery Scorecards for Banks

· Roopam Upadhyay 7 Comments

Covid-19 pandemic has ignited an unprecedented risk for the economy. Banks and financial institutions across the globe are expected to register unusually high default rates on loans once the moratorium and forbearance imposed by the governments and the regulators are lifted. 

Scientific tools such as collection and recovery scorecards offer a mechanism to predict defaults on the loan portfolio and also suggest appropriate actions to alleviate debt collection and recovery risk. In this webinar video, learn how you can use machine learning to develop collection scorecards to improve debt collection efficiency. Also, learn how to implement collection scorecards to reduce bad debts on your portfolio.

 

  • Share
  • Twitter
  • Facebook
  • Email
  • LinkedIn

Related

Posted in Risk Analytics, Video Discussion |
« How data science will shape post-COVID banking? – Video Discussion

7 thoughts on “Machine Learning for Debt Collection and Recovery Scorecards for Banks”

  1. Christine says:
    February 1, 2021 at 11:52 am

    Machine Learning is not only used to reduce loan defaults but it can also be used to increase debt collections and recoveries.

    Reply
    • Roopam Upadhyay says:
      June 9, 2021 at 11:00 am

      That’s correct, Christine.

      Reply
  2. Kyle says:
    February 5, 2021 at 9:12 am

    AI isn’t simply used to decrease credit defaults however it can likewise be utilized to build delinquent payment assortments and recuperations.

    Reply
  3. Rhishikesh (Rishi) Nepal says:
    March 1, 2021 at 12:57 pm

    Hello Rupam ji,
    Amazing webinar. Thank you.

    I have a question here. If you are intending to build a collection score card for a lets say digital lending product such as buy now pay later model of digital lending, but the product has not gone live and there is no data collection, then can we build a collection score card in the form of a reference model using credit card and non-collateralized personal loans?
    Appreciate you response.

    Best Regards,
    Rishi

    Reply
    • Roopam Upadhyay says:
      March 1, 2021 at 1:53 pm

      Hi. In case it is a new product then using scorecards for similar products as a proxy is a reasonable approximation. In this case, it is recommended to monitor the collection performance closely and modify the scorecard based on new evidence/data.

      Reply
  4. Rahul Rathore says:
    March 26, 2021 at 11:11 am

    First of all, I loved your video ,found your video very useful. I am trying to build ML powered scorecard for short term(15-30 days tenure) loan app . Is there any github repo where i can look for code for your above video ?
    Thank you

    Reply
  5. Roopam Upadhyay says:
    June 9, 2021 at 10:58 am

    Hi Rahul, there is no GitHub code repository for this webinar however I suggest this risk scoring case studies which you will find useful

    http://ucanalytics.com/blogs/category/risk-analytics/banking-risk-case-study-example/

    http://ucanalytics.com/blogs/category/risk-analytics/credit-risk-analytics-series/

    Cheers

    Reply

Leave a comment Cancel reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Subscribe to Blog

Provide your email address to receive notifications of new posts

Must Read

Career in Data Science - Interview Preparation - Best Practices

Free Books - Machine Learning - Data Science - Artificial Intelligence

Case-Studies

- Marketing Campaign Management - Revenue Estimation & Optimization

Customer Segmentation - Cluster Analysis - Segment wise Business Strategy

- Risk Management - Credit Scorecards

- Sales Forecasting - Time Series Models

Credit

I must thank my wife, Swati Patankar, for being the editor of this blog.

Pages

  • Blog-Navigation
  • Art
  • About
  • Contact
© Roopam Upadhyay
  • Blog-Navigation
  • Art
  • About
  • Contact
loading Cancel
Post was not sent - check your email addresses!
Email check failed, please try again
Sorry, your blog cannot share posts by email.