Student lender SLM posts Q3 net loss; annual EPS outlook lowered

By Reuters News


Overview

  • US private student lender's Q3 Private Education Loan originations grew 15% yr/yr, marking a record quarter

  • Company posted GAAP net loss per share of $0.19, mainly due to higher provisions and expenses

  • Company repurchased 5.1 mln shares for $132.2 mln during Q3


Outlook

  • Company lowers 2026 diluted EPS guidance to $1.95-$2.05 from $3.10-$3.20

  • Company maintains 2026 Private Education Loan originations growth forecast at 12%-14%

  • Company raises 2026 net charge-off guidance to $400-$420 mln from $365-$385 mln


Result Drivers

  • ORIGINATIONS GROWTH - Co said record Private Education Loan originations, especially graduate loans after PLUS reform, drove higher activity

  • HIGHER PROVISIONS AND EXPENSES - Net loss attributed to increased provisions and expenses tied to elevated loan origination volumes

  • CHARGE-OFFS INCREASE - Higher net charge-offs driven by issues with third-party debt resolution practices and changes to recovery strategies


Company press release: Full Story


Key Details

Metric

Beat/Miss

Actual

Consensus Estimate

Q3 Loss Per Share

$0.19

Q3 Net Interest Income

$339 mln


Analyst Coverage

  • The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 7 "strong buy" or "buy", 3 "hold" and 1 "sell" or "strong sell"

  • The average consensus recommendation for the consumer lending peer group is "buy"

  • Wall Street's median 12-month price target for SLM Corp is $29.00, about 27% above its October 21 closing price of $22.83

  • The stock recently traded at 7 times the next 12-month earnings vs. a P/E of 8 three months ago


Reuters Recommended Reads

  • Oct 20 - Synchrony Financial's Q3 net earnings fall 17%

  • Oct 22 - Enova Q3 adjusted EPS beats estimates on healthy loan demand, stable credit

  • Oct 21 - Pressure on lower-income US households raises delinquency risks, Morningstar DBRS says


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(This story was created using Reuters automation and AI based on LSEG and company data. It was checked and edited by a Reuters journalist prior to publication.)

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