Segmenting debtors based on risk and payment behavior is essential for effective debt collection management. By categorizing debtors into different segments, you can tailor your collection strategies to maximize recovery and minimize costs. Here are the most effective strategies for segmentation:
Analyzing Credit Scores
Credit Score Segmentation
Use credit scores to segment debtors into categories such as low-risk, medium-risk, and high-risk. Credit scores provide a quick and reliable way to gauge a debtor’s overall financial health and payment reliability.
You can use the credit score that you obtained at customer’s acquisition stage and modify it based on your own experience or by obtain authorisation from the customer to perform a new search. You might be able to obtain a new updated credit score during the relationship with the customer, when a customer requests to make a new and important purchase, or if your customer is experiencing financial difficulties and is requesting an arrangement. It is not unreasonable at these moments to request the authorisation to perform a new credit search and update the score you hold.
We shall not over complicate this process. It is recommended to create up to five tranches of credit score, so you can develop up to five strategies or prioritisation. You can use for this effect the Focus Matrix described in chapter 11 – Collection management tools and methods.
Risk Buckets
Debtors can be grouped into risk buckets based on their scores, with each bucket representing a different level of risk and corresponding to specific collection strategies. You can then build Focus matrix combining Risk and Total Due or Risk and Aging.
Payment History Analysis
On-Time vs. Late Payers
Segregate debtors based on their payment history, identifying those who consistently pay on time, those who occasionally miss payments, and chronic late payers. This will allow you to provide a distinct and more appropriate reaction to a late payment:
- If an on-time customer is late. This should light a red flag that we may have done something wrong. Customer care or account managers need to intervene immediately to understand the root-cause of the late payment (like a problem in the product or service delivered and fix it immediately).
- On the opposite, a chronic late payer should trigger a more effort intensive collection strategy adapted to the customer’s (bad) payments habits.
Read more about this in Chapter 10 – The Collection process – Debt collection in arrears, phase 2: treatment of reasons for non-payment.
Delinquency Patterns
Look for patterns in delinquency, such as the frequency and severity of missed payments, and categorize debtors accordingly.
Channel Preference
Identify the preferred communication channels of debtors (e.g., email, phone, SMS) and segment them accordingly to improve engagement and response rates.
Financial Capacity and Employment Status
Income and Employment
For debtors where this information is available, segment them based on their income levels and employment status. This can help in customizing repayment plans that are more likely to be honored.
Debt-to-Income Ratio
Use this ratio to assess a debtor’s ability to pay and segment them accordingly.
Income and expenditure statement
Whether your customer is a small business or a private consumer, you might be able to obtain an income and expenditure statement (or profit and loss for a business) when a customer is requesting delays.
Of course, the information provided by the customer could be biased. But it describes to you the situation the customer wants you to understand, and it is the basis of the negotiation with the customer for a settlement. It is often a trigger to obtain the permission from the customer to allow you to obtain a new credit report.
Demographic Segmentation
Age and Life Stage
Segment debtors by demographic factors like age and life stage, as these can influence payment behavior. For example, younger debtors might be more responsive to digital communication, while older ones might prefer traditional methods.
Geographic Location
Location-based segmentation can help tailor communication styles and payment options, considering local regulations and cultural nuances.
Psychographic Segmentation
Behavioral Insights
Use psychographic data, such as attitudes toward debt and financial stress, to create more personalized and empathetic collection strategies.
Motivations and Barriers
Understand what motivates debtors to pay and what barriers they face, segmenting them based on these factors to design effective interventions.
Historical Data and Predictive Analytics
Predictive Models
Utilize predictive analytics to forecast the likelihood of payment based on historical data. Debtors can be segmented based on predicted payment behavior, allowing for proactive and targeted collection strategies.
Machine Learning Algorithms
Implement machine learning models that continuously learn from historical payment behavior to refine segmentation over time.
Engagement History
Track how debtors have responded to past collection attempts and segment them based on their engagement level. Those who have been responsive might require less intensive follow-up compared to those who have been unresponsive.