Intelligent Debt Collection – A Fresh Perspective To Recovery
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What is the relevance of Intelligent Debt collection?
Banks and/or Financial Institutions (FIs) invariably face issues pertaining to loan collection or debt collection. The investments made for customer acquisition, branding, etc. gets affected during the recovery process.
This raises a question, is there a way to implement an Intelligent Debt Collection Process which can help facilitate the recovery along with enhancing customer loyalty ?
Artificial Intelligence and Machine Learning (AI & ML) technology is used widely for adding intelligence to the debt collection operations. It is interestingly seen that they are achieving better results in terms of collections as well as customer loyalty and retention.
Debt Collection Efforts May Result in Losing Customer Loyalty
In many cases, while the customers face difficulty in repaying the Debt, the lender or debt collection agency will be struggling with follow up activities, more aggressively. The follow-up calls, irreverence in conversations, quality of information shared with the customer, etc. – will only exacerbate the problem leaving the customer(s) perturbed.
Debt Collection Stats
In the US, FDCPA Act (Fair Debt Collection Practices Act) was passed in 1977. The FTC (Federal Trade Commission) enforces the Fair Debt Collection Practices Act (FDCPA), which makes it illegal for debt collectors to use abusive, unfair, or deceptive practices when they collect debts.
Debt.com, a financial solution provider company comes out yearly with statistical report on ‘Complaints on debt collection’.
- 13% of the complaints received, threatens to take legal action.
- 10% of the complaints claimed are false i.e., quotes erroneous amount.
- 40% of complaints claiming debt not owed.
- 23% claims that they already paid off the debt.
The situation in several countries is more or less similar.
What Is the Impact of This?
Losing customer loyalty is the prime result and it adversely affects the brand reputation. Out of all the delinquent cases identified, many will have justified reasons to support.
If analyzed accurately with highly relevant data points, there may be several ways to mitigate the delinquency. Customer profiling plays a significant role in determining the current situation in which the customer is, the debt management plan of customer and other trigger points i.e., earnings, credit score, workplace, etc. – can deliver deep customer insights.
Many customers need financial advisory services to manage their debts and finances, in the best possible manner.
McKinsey & Company Study Report on Collection Operations
In this report McKinsey claims that, “the collection managers across the world are facing rising delinquencies and the cost to manage the collections is on the rise”. They also highlight that “lenders need to invest in smarter and more effective collection operations”.
Adding Intelligence to Collection Process Using Customer Segmentation
Segmenting your customers based on their profiles i.e., static and dynamic factor is essential to improve customer correspondence and compliance to credit policy. In current scenario, the FIs are sitting on heap of customer related data and structuring it with the advent of digitization.
Analyzing the data using AI & ML tools will give you lot of insights about the profile of the customers. Segmenting your customers based on the data points and device collection strategy is one major intervention step.
This circumvents “one size fits all” kind of approach and helps bring in a more informed perspective which can ease the decision-making approach on every collection case that comes in.
Deloitte in “A fresh perspective collection strategies for the digital age” explains in detail about segmentation strategy in implementing an intelligent Debt collection system.
Segmentation helps you to identify the best i.e., comms medium for every customer segment, alternative to manage debt, time and ways to approach, etc. Analytical insights are available so that you can do a continual improvement and up your strategy to achieve better results every time.
Adding Intelligence to Collection Process Using Prediction of Delinquency
Prediction of delinquency of loans is one another solution in adding intelligence to the loan collection. ML capabilities to forecast the delinquency of a customer is widely used in order to make the Debt collection process more productive. Knowing who is likely to default is a good tool in the hands of the lender.
Using this information, right strategy can be formulated by the lender who can prevent the customer from such situation. Deloitte stresses that “banks or financial institutions have greater incentives to maintain brand loyalty so that when the customer is in better financial health, they will consider returning to that lender”.
Introducing Intelligent Debt Collection Solution by Speridian Technologies
Speridian Technologies is the leading Global IT solution provider in Financial segment with specialized solutions on collections and recovery.
BEACON Delinquency Management Solution comprises of various tools and techniques capable of providing an intelligent debt collection solution for your organization.
The implementation of this solution has led to huge success for many Banks, NBFCs across multiple geos. It helps customers not only improve their collection but also keeps the customer loyalty and retention factor.
Schedule a Demo today, to get detailed insights on the host of features and functionalities that best fits your business ecosystem.
Creating collection scorecards, Risk segmentation are few other tools to enhance your recovery practices. I’ll be back with more details on this subject. Visit this space to stay tuned with more updates on Intelligent Debt Collections & Recovery.
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