Receivables and Expected Credit Losses |
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| Receivables and Expected Credit Losses | Note 3 – Receivables and Expected Credit Losses We maintain an allowance for expected credit losses that assesses the lifetime credit losses that we expect to incur related to our receivable portfolio segments. Each period, management assesses the appropriateness of the level of allowance for credit losses by considering credit risk inherent within each portfolio segment as of period end. We consider a receivable past due when a customer has not paid us by the contractually specified payment due date. Account balances are written off against the allowance for credit losses if collection efforts are unsuccessful and the receivable balance is deemed uncollectible, based on factors such as customer credit ratings as well as the length of time the amounts are past due. Our portfolio of receivables is comprised of two portfolio segments: accounts receivable and EIP receivables. Accounts Receivable Portfolio Segment Our accounts receivable segment primarily consists of amounts currently due from customers, including service and leased device receivables, device insurance administrators, wholesale partners, third-party retail channels and other carriers. We estimate expected credit losses associated with our accounts receivable portfolio using an aging schedule methodology that utilizes historical information and current conditions to develop expected credit losses by aging bucket, including for receivables that are not past due. To determine the appropriate credit loss percentages by aging bucket, we consider a number of factors, including our overall historical credit losses, net of recoveries and timely payment experience as well as current collection trends such as write-off frequency and severity, credit quality of the customer base, and other qualitative factors such as macro-economic conditions, including the expected economic impacts of the COVID-19 pandemic (the “Pandemic”). We consider the need to adjust our estimate of expected credit losses for reasonable and supportable forecasts of future economic conditions. To do so, we monitor professional forecasts of changes in real U.S. gross domestic product and forecasts of consumer credit behavior for comparable credit exposures. We also periodically evaluate other economic indicators such as unemployment rates to assess their level of correlation with our historical credit loss statistics. EIP Receivables Portfolio Segment Based upon customer credit profiles at the time of customer origination, we classify the EIP receivables segment into two customer classes of “Prime” and “Subprime.” Prime customer receivables are those with lower credit risk and Subprime customer receivables are those with higher credit risk. Customers may be required to make a down payment on their equipment purchases. In addition, certain customers within the Subprime category may be required to pay a deposit. To determine a customer’s credit profile, we use a proprietary credit scoring model that measures the credit quality of a customer using several factors, such as credit bureau information, consumer credit risk scores and service and device plan characteristics. Installment loans acquired in the Merger are included in EIP receivables. We applied our proprietary credit scoring model to the customers acquired in the Merger with an outstanding EIP receivable balance. Based on tenure, consumer credit risk score and credit profile, these acquired customers were classified into our customer classes of Prime or Subprime. The following table summarizes the EIP receivables, including imputed discounts and related allowance for credit losses:
We manage our EIP receivables portfolio using delinquency and customer credit class as key credit quality indicators. The following table presents the amortized cost of our EIP receivables by delinquency status, customer credit class and year of origination as of June 30, 2021:
We estimate expected credit losses on our EIP receivables by using historical data adjusted for current conditions to calculate default probabilities for our outstanding EIP loans. We consider various risk characteristics when calculating default probabilities, such as how long such loans have been outstanding, customer credit ratings, customer tenure, delinquency status and other correlated variables identified through statistical analyses. We multiply these estimated default probabilities by our estimated loss given default, which considers recoveries. As we do for our accounts receivable portfolio segment, we consider the need to adjust our estimate of expected losses on EIP receivables for reasonable and supportable forecasts of economic conditions through monitoring external professional forecasts and periodic internal statistical analyses, including the expected economic impacts of the Pandemic. For EIP receivables acquired in the Merger, the difference between the fair value and unpaid principal balance of the loan at the acquisition date is accreted to interest income over the contractual life of the loan using the effective interest method. EIP receivables had a combined weighted average effective interest rate of 6.3% and 6.7% as of June 30, 2021 and December 31, 2020, respectively. Activity for the six months ended June 30, 2021 and 2020, in the allowance for credit losses and unamortized imputed discount balances for the accounts receivable and EIP receivables segments were as follows:
Off-Balance-Sheet Credit Exposures We do not have material, unmitigated off-balance-sheet credit exposures as of June 30, 2021. In connection with the sales of certain service and EIP accounts receivable pursuant to the sale arrangements, we have deferred purchase price assets included in our Condensed Consolidated Balance Sheets measured at fair value that are based on a discounted cash flow model using Level 3 inputs, including customer default rates and credit worthiness, dilutions and recoveries. See Note 4 – Sales of Certain Receivables for further information.
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