Millennials have the highest delinquency rates on telco trades. According to TransUnion consumer credit data, with some millennial customers, telcos lose a dollar for every dollar they make ... but not with all. The key is being able to recognize those who carry less risk. In a recent TransUnion analysis on trends in telco utilization and payments, we uncovered insights to help telcos identify the least and most risky consumers in any generation.
Using this analysis, here are four key findings about telco customers and their payment behaviour.
TransUnion enhanced a traditional generation-based analysis of telco customers with additional data sets. Each step of our analysis revealed implications for onboarding customers.
Key finding: Millennials make up the majority of the subprime population
The subprime population—customers with a credit score under 640—is the largest user of telco trades. It also has the highest share of telco balances across all provinces. And who makes up the majority of this population? Millennials (consumers born between 1980 and 1994).
Millennials have higher delinquency rates on telco trades than other generations. The rate of late payments (90+ days past due) for Millennials is two times higher than for Baby Boomers (1946 to 1964) and half as high as the rate for Generation X (1965 to 1979).
Implication: Millennials may not pay their telco bills and are therefore a higher risk.
Question: Were younger consumers not paying at all, or was there more to the story?
Key finding: Not all subprime payers are equal - Some are struggling: some are sloppy
When we looked at the performance of the entire subprime group, using payment behaviour data from their telco and other accounts, we found two types of payers:
Implication: Not all Millennials exhibit the same payment behaviour when it comes to their telco accounts; therefore, not all Millennials are necessarily higher-risk potential customers.
Question: Were they paying late, rather than not paying at all? Let’s dig a bit deeper into the data.
Key finding: Gen X and Millennials have about the same proportion of sloppy and struggling payers
The table below tells the story:
Implication: Millennials and Gen X customers appear to have the same proportion of consumers taking longer to pay off their debt, and therefore present equal risk to the telco. It’s not just Millennials who have higher-risk customers in their group.
Question: Who, then, should telcos be onboarding?
Key finding: Struggling Millennials are the least likely to pay, but not all Millennials are strugglers
In both generations, we found strugglers were the least likely to pay. And within the strugglers group, it was the Millennials who were most likely not to make payments at all.
On average, for every telco trade written off, Millennials have $125 more in charge-off balances than Gen X. In fact, telcos lose a dollar for every dollar they make on struggling Millennials. But, as we’ve seen, not all Millennials fall into the strugglers category.
Implication: Clearly, there is a difference in payment behaviour among generations. But not everyone aged between 23 and 37 is a potentially higher-risk customer—which could have been our conclusion if we’d stopped our analysis at step 1.
Conclusion: By adding additional data to their demographic segmentation, telcos can identify the subsets of struggling and sloppy payers within each age group, and make more informed decisions when onboarding customers.
Deeper analysis is key to successful segmentation. It is standard practice to use demographic data to profile your customers, but if that is where your segmentation ends you could be missing valuable opportunities.
This analysis enables you to weed out higher-risk customers and also reveal opportunities to expand your customer universe.
Additionally, it is not a one-time analysis, either. As the lifestyles of your customers change so does their credit risk. By staying on top of trends, you will be in a better position to segment and manage your customer base across generations and throughout the credit lifecycle, ultimately making more informed decisions.
For information on TransUnion’s analytic capabilities, please visit transunion.ca/solution/analytics