Effective debt collection in changing times with Pega

Most nations are struggling to deal with the Covid-19 pandemic. Due to lockdown and various restrictions, what’s certain is the harsh economic reality facing businesses as government support is reduced in various aspects such as debt collection. The collection departments of most financial institutions are bearing the brunt of the situation as many of the borrowers are unable to meet their financial commitments. With our experience in redefining collection processes for many of our clients, we are well aware of the best practices in collections and the data to be identified to streamline the entire cycle of collections during this time.

Data capturing and finding the vital information

 Financial service providers have always been concerned about pre-delinquencies. But a deep level of scanning is required to capture the vital information that would separate the economic victims from others. The data from calls, collections, or communication systems need to be assessed to create segregation and to understand the degree of risk associated with each customer. With the following data, we may arrive at a certain level of understanding that may reduce the risk associated with collections:

  • Data that reveals how reliant the customer is on credit. For example, data on card-utilization.
  • Data that gives you a clear picture of the financial morality of your customer such as the number of credit cards, interest-free offers availed, early settlements, etc.
  • Changes in card transactions and spending patterns.
  • Information about their industry, occupation, income, job stability, etc.

Without much of the above information, most of the credit borrowers will end up in the category of low-risk customers. The predictive analysis to assess the probability of an existing customer ending up in the high-risk category of collections is the need of the hour.

Assessing the affordability factor

While the credit bureau information and other behavioral data may help assess the risk to a certain degree, forward-looking analytics to measure the effect of incremental debt may give a clear picture. What we need to understand is that there isn’t any generally accepted measure of indebtedness and affordability risk and hence a combination of factors should be applied to know whether a person is indebted or has the likelihood of being indebted in the near future. With the pandemic, many of the customers who were previously in the low-risk category too have defaulted on payments which indicate the need to upgrade the mechanism of data capturing and analysis. The additional data that may have to be collected will include:

  • The reasons for the financial burden. For example, unemployment, reduction in income, medical reasons, quarantine, etc.
  • Type of relief offered by the financial institution
  • Industry the customer is associated with and other behavioral data

The data collected with respect to the pandemic situation shouldn’t be static and must include several other factors. Not to mention, communication is the key to receive updates on the current situation of the customer.

Revolutionizing collections with Pega

Pega offers a unique combination of personalized and data-driven automated processes that enables real-time decisioning to optimize collections and reduce the number of customer contacts required to resolve collection challenges. With the implementation of advanced solutions, collection representatives can personalize customer interactions and recommend optimal repayment plans while being compliant with the risk policies of the financial institution. This would result in consistent, compliant interactions across multiple channels and accounts that would allow financial institutions to remain customer-centric while increasing collection rates and improving operational efficiency. 

To know more about the Pega solutions we offer to our financial clients visit our case studies section: Instellars | Case Study.

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