3 Ways to Assess Credit Risk with Utility Payment Data
The acceptance and appeal of using alternative credit data to assess credit risk has rapidly grown across the financial services space. Not only has it displayed powerful predictive accuracy, but it’s also shown the potential to extend credit to millions of consumers left out of the current system. By layering in alternative data sources like rent and utility payment data to a traditional risk score, Experian saw a 60 percent lift in approvals of near-prime consumers.
However, when it comes down to actually putting alternative data sources to use, the process gets murky. How can a lender take the complicated history of a consumer’s utility bill payments and zero in on a clear picture of their credit risk? Below, we’ll break down the three ways a lender can assess credit risk from a consumer’s utility payment history.
First, utility payment data is a good indicator of delinquency. There’s a strong correlation between utility payment behavior and credit risk: if a consumer is frequently behind on a day-to-day essential like their utility bills, they’re likely to fall behind on their loan payments, too. From 12 months of utility bill payments, a lender can calculate:
- Number of delinquent occurrences: the number of months during which payments failed to reach the balance due
- Most recent multi-month delinquency: how long it’s been since the last time the consumer didn’t pay their bills for several consecutive months
- Longest delinquency: the longest stretch of time over which monthly payments failed to clear the balance due
Observe Payment Behavior
Utility payment data also offers a rich source of history on payments made on time, supporting and improving a consumer’s credit risk profile. For example, lenders can accurately assess credit risk from these data points:
- Average advanced payment date: how far in advance of when the bill is due that a complete payment is made*
- Average monthly utility payment: amount of money spent on utilities on a monthly basis
- On-time utility payments: how many bills in the last year were paid in full, on or before the due date
*When the payment date consistently coincides with the date when the bill is issued, it’s likely that the consumer has auto-pay set up for their utilities, a good sign of their confidence in their own ability to pay.
Analyze Accumulated Balances
Finally, the data sets that perhaps most closely resemble a traditional credit risk model are the credit balances built up in a consumer’s utility payment history. When consumers overpay or underpay on their utility bills, these balances will show up on their bill month after month:
- Unpaid balances: partial payments that result in accumulated balances on the bill
- Mega-payments: large lump sums intended to cover several months of payments – a very good sign that the consumer is confident in their ability to pay
Most consumers have to pay their utility bills every month. If they don’t, they end up with delinquencies and balances running that are clearly visible within utility payment data. For lenders, this accumulates into a rich data source to draw from as they assess credit risk of near-prime consumers. Now, the question becomes: what’s the best way for lenders to start channeling utility payment data?
How to Access Utility Payment Data to Assess Credit Risk
There are a number of options out there for lenders looking to access utility payment data. Several of the big three credit bureaus are piloting experimental risk models that incorporate alternative data, and NCTUE houses a member database of consumer utility data. But the best way to access utility payment data is from the consumers themselves, with a user-permissioned platform.
The Urjanet platform provides a simple, seamless access point for consumers to share their utility payment data with lenders for the specific, transparent purpose of assessing credit risk. Through Urjanet, lenders can get on-demand access to the most recent 12 months of utility payment history and gain deeper visibility into near-prime consumers.
To learn more about how it works, request a demo today.
You might also be interested in:
- Getting Started with Urjanet Utility Data for Credit Risk Decisioning
- Phone Payment Data Grows in Value & Availability
- Say “Yes” to the Consumer
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About Amy Hou
Amy Hou is a Marketing Associate at Urjanet, writing about emerging topics in sustainability, energy management, and data innovation.