FinWise Bancorp Q1 profit falls on elevated charge-offs

Finwise Bancorp

30/04/2026 21:35

Overview

U.S. fintech-focused bank's Q1 loan originations rose 38% yr/yr to $1.7 bln

Net income and diluted EPS declined yr/yr amid elevated charge-offs and higher expenses

Nonperforming loan balances increased, mainly due to higher SBA 7(a) loan nonaccruals

Outlook

Company expects SBA charge-offs to remain elevated over the next few quarters

FinWise expects efficiency ratio to improve with increased revenues from credit enhanced loan balances

Company says partner pipeline continues to strengthen and platform is scaling

Result Drivers

INTEREST INCOME ALLOCATION - Net interest income rose, driven by a change in estimate on allocation of interest received on credit enhanced loans and growth in average balances

ELEVATED CHARGE-OFFS - Net income was affected by higher net charge-offs, particularly in the credit enhanced portfolio and legacy SBA credits

HIGHER NON-INTEREST EXPENSES - Non-interest expenses increased mainly due to higher credit enhancement guarantee and servicing costs tied to portfolio growth and interest income allocation changes

Company press release: ID:nGNX5Dqq9h

Key Details

Metric
Beat/Miss
Actual
Consensus Estimate
Q1 EPS
$0.20
Q1 Net Income
$2.70 mln
Q1 Net Interest Income
$28.10 mln
Q1 Loan Loss Provision
-$10.60 mln
Q1 Net Interest Margin
12.90%


Analyst Coverage

The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 3 "strong buy" or "buy", no "hold" and no "sell" or "strong sell"

The average consensus recommendation for the banks peer group is "buy"

Wall Street's median 12-month price target for Finwise Bancorp is $21.00, about 31.9% above its April 29 closing price of $15.93

The stock recently traded at 9 times the next 12-month earnings vs. a P/E of 10 three months ago

For questions concerning the data in this report, contact Estimates.Support@lseg.com. For any other questions or feedback, contact reuters.support@thomsonreuters.com.

(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.)