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Increase Telecom Recoveries with Robust Scoring Models

  • Written by Sam Edens

edens samWhen handling telecom accounts, agencies need to have a distinct approach to be successful in their recovery attempts. Customer delinquency is on the rise in the telecom market. Higher subscriber prices, providers combining services, the competitive nature of the players in the market, and third-party involvement is to blame for the growing number of delinquent subscribers and rising write-off amounts. News like this should be welcoming to agencies servicing telecom accounts, but with it comes increased pressure on the agencies to recover.

It is a mistake to think of telecom accounts just like every other account. It is an even greater mistake to treat telecom consumers as you would treat bank card, student loan, or medical consumers who have delinquent accounts. Take a minute and think about yourself as a consumer in the telecom market. This should be easy as you likely have some combination of telephone, cable, satellite, or streaming service accounts in your name. As a consumer in the market, do you understand what you signed up for, how much you owe, and in what respect the money is applied when you make a payment? Generally, consumers in the telecom market cannot answer these questions and furthermore, cannot explain the contract they signed or if they even signed a contract. We see this phenomenon in the telecom industry because it has been commoditized to the extent where it is too easy for consumers to switch suppliers. When a consumer switches, he/ she usually either does not know or does not care he/she owes money. The point is the industry is different so how an agency utilizes systems and technology to collect needs to be different.

Closer management is essential. Creating and implementing finely segmented profiles using strong scoring models is one way to manage telecom accounts in your collection software. First and foremost, identify the data elements that should factor into generating your recovery score and how each may positively or negatively impact the score. The list below includes some data elements and considerations when generating a recovery score for your telecom accounts.

Credit Score

In most cases this is undoubtedly the top data element to include when generating a custom recovery score. It should weigh heavily in determining the collectability of an account. The workflows or queue logic in your software should stage consumers with the higher credit scores to receive the most attention. Likewise, you may set up your workflow to all but close out accounts with a credit score in the 300 or 400 range.

Quantity and Quality of Data

It is important to know how much data you have per account and the quality of the data. Generating a custom recovery score with not enough and or unqualified data may hurt your recovery attempt more than helps it. Ideally, you already have the data captured in your software. If not, most data should be included in the placement file from the service provider or can be obtained by interfacing with data scrub service providers like LexisNexis, MicroBilt, or any of the major credit bureaus. At a minimum, make sure you are receiving and storing data points like full name, social security number, full and verified address, and verified phone.

Number of Delinquent Accounts

Any consumer with multiple delinquent accounts in your system should receive a lower score. It is an indication the consumer is hopping suppliers when better deals or introductory offers are available.

Geographic Location

Some may question the significance of this data element but in remote or lesspopulated areas of the country, consumers do not have many options for telecom service. They may even be limited to a single supplier for Internet, cable, and/or telephone service. In these cases, a higher recovery score is reasonable as the consumer must satisfy the debt in order to resume service or to receive new services from the supplier.

Type of Residence

You may consider increasing the recovery score if the consumer owns versus rents or shares a residence. In just about all cases, the telecom accounts for a homeowner are in his/her name. When working with consumers in an apartment, condo, or other renting situation, the telecom services and responsibilities may be split among many of the residents, making it somewhat easier to neglect their portion of the service.

After identifying and detailing the data elements important for generating your custom recovery score, they must be built into your software for automatic and fluent management. Some recovery software platforms include modules to set up custom scoring but none I have encountered are very impressive. More flexibility and options are likely available outside of the software. In most cases, custom scripting will be required to consume the data and make systematic scoring decisions. If you have strong programmers on staff, their skills will certainly be required to configure your scoring model. This can be handled strictly with scripting a solution that will integrate with your recovery software or externally in a data warehouse or “black box.” The terms data warehouse and black box are interchangeable on this topic. It is a place external to the recovery software where data from your recovery software, accounting software, web portal, CRM, or any of other in-house system is captured.

Custom scripting can be applied here as well and may be a better option than against the recovery software database because you may have more data elements to work with in the data warehouse. Regardless of the database(s) utilized, it is imperative to apply the recovery score logic uniformly and against all consumers in the system. One mistake agencies make when implementing new logic is only applying it on a go-forward basis. Circle back on all the existing telecom consumers in your system and run them through your new custom scoring logic as well. Allow the system to make decisions and commit to allowing your scoring to drive collection efforts.

Sam Edens has been with Emprise Technologies since 2006 and is currently serving as Vice President. Prior to his time with Emprise, Sam designed and developed performance and flow management software for UPS.