Debt collection is all about contacting customers, and that only works with correct contact details. Contact data quality in debt collection is a common challenge, and we are often asked how best to address it.
1. Get contact data before you need it
It is much easier to obtain valid contact details from your customers than from a third party. And updating contact data when you need to contact a customer as part of a collections process is usually much more difficult than in setups or account management. Therefore, managing contact data should be a business task.
Data entry during customer acquisition should not be limited to the data necessary to complete the assembly process. Specifically, mobile phone number and email addresses should be captured in addition to the physical address whenever possible, as they facilitate digital engagement and transfer to self-service processes.
2. Test the quality of your data
Whenever contact data is acquired, it should be checked for syntactical plausibility – two-digit phone numbers and email addresses without @ or without a valid top-level domain won’t be of much use anymore late. And ideally, contact data should be tested. Initially, these tests can be called a customer satisfaction survey, which is a sensible thing to do anyway. Switch channels if you can – for example, if email is used to update your client on the progress of the creative process, use phone or text for a follow-up survey.
3. Evaluate your communication results
It is common bad practice not to process the physical communication results of automated bulk communications. Typically, these shortfalls are due to implementation budget restrictions, but tend to be costly in the long run. If a customer cannot be contacted on a phone number because the number is invalid, this will not change on subsequent attempts.
For each outbound customer contact, the physical outcome must be assessed; failures must be recorded and must trigger a respective rectification process. Negative results include undeliverable emails and text messages, invalid phone numbers, and returned physical mail. Fixing the issue when it first occurs increases the likelihood that customers can still be reached on another channel.
4. Periodically confirm contact data
Over time, customers will change their contact details, and especially for low interaction, long-term products like mortgages or credit cards, it is important to periodically validate contact data with the customer. This can be achieved through pop-ups on the customer portal or mobile app or as part of the call script when contacting customer service. For a reasonable customer experience, the date of the last validation should be stored and the next confirmation should be triggered based on that date.
5. Process contact changes
It seems too obvious to say, but when customers provide updated contact data, that data needs to be processed. In too many organizations, this remains a challenge. There are usually two main factors for this: the first is the insufficient integration of satellite systems or product-specific platforms, which leads to address changes not being replicated throughout the ‘organization. The second concerns policies that make it unnecessarily difficult for customers to share their address.
While it may be appropriate to insist on written confirmation of changes to the primary legal address, contact changes provided by the customer should never be ignored simply because they do not meet certain formal requirements. . Instead, this contact data should be captured and flagged as unconfirmed. If necessary, confirmation can be obtained via pop-ups in customer portals or via pre-filled forms that are sent to the customer.
6. Define a contactless strategy in debt collection
Even with valid contact information, you may not be able to contact some of your customers. For example, you may repeatedly attempt to contact customers at a time when they cannot answer your call.
In highly automated pickup environments, it’s even more important to keep track of customers you haven’t been able to contact. These customers should be removed from standard processing and assigned to a dedicated contactless policy, where the reason for failed attempts is assessed and addressed.
7. Professionalize data research
Even if you follow the recommendations above, you might end up without valid contact data. Then comes the time of researching data.
The value of valid contact data may vary from customer to customer, depending on customer value, outstanding balance, and customer lifecycle stage. Therefore, a segmented approach should be taken when choosing the contact data recovery method and effort.
Leaving the search for contact data to the individual collector is probably the most expensive approach. Research should be a specialized task, performed by dedicated resources. This is the only way to get an idea of which methods work best and to understand the costs and benefits of alternative approaches. In small organizations that do not have a dedicated team, contact data research should always be done by specialized resources, even if it is not their sole responsibility.
8. Automate and scale
Even though accounts missing contact data should be the exception, they usually lead to high volume processes. For this reason, automating data recovery is essential.
Where possible, initial attempts to retrieve data should be undertaken en masse, for example by contacting the customer on an alternate channel and requesting updated contact details. In many geographies, address lookup services provide up-to-date contact information and only charge based on success. When there are multiple vendors, you can pit vendors against each other in champion/challenger tests or alternate unsuccessful attempts from one vendor to another. Implementing processes in your decision engine can provide the structure and agility needed to dramatically accelerate testing and learning.
For customers without valid contact data, larger institutions have in-house mini-tracing teams and outsource Gone Away Skilled Tracing and Collection to specialist agencies. Small organizations can go straight to Trace and Collect. Importantly, Gone Away accounts are not immediately considered much higher risk if they are easily tracked down and contacted. A Gone Away tag or label should not preclude the need to validate the customer’s financial vulnerability.
Manual research activities are generally much more expensive and may include a review of previous client correspondence and original files. Depending on customer value and lifecycle stage, field visits and third-party manual searches may be your last resort.
9. Measure what you’re doing to improve your data quality
Regardless of your approach to contact data retrieval, activities should follow a structured process, should be logged, and should be monitored for effectiveness and efficiency. It’s the only way to improve your processes and data quality over time, understand what works for what type of customer, and get the most out of your research efforts.
How the FICO Platform Can Advance Your Debt Collections