Princeton Bancorp's Q3 net income falls on higher credit loss provision

By Reuters News


Overview

  • US community bank's Q3 net income fell sharply due to higher provision for credit losses

  • Net interest margin declined to 3.75%

  • Company raised quarterly dividend by 14.2%, citing confidence in sustained earnings


Outlook

  • Company did not provide specific guidance for the current quarter or full year in the press release


Result Drivers

  • CREDIT LOSS PROVISION - Q3 results were primarily impacted by an $8.0 mln increase in provision for credit losses, mainly due to charge-offs of two commercial real estate loans

  • ASSET WRITE-DOWN - Asset write-down related to future retail consolidation reduced reported net income

  • NON-RECURRING ITEMS - Core operations generated about $7.0 mln in net income, but reported results were lowered by non-recurring charges


Company press release:


Key Details

Metric

Beat/Miss

Actual

Consensus Estimate

Q3 EPS

$0.15

Q3 Net Income

$1 mln

Q3 Net Interest Income

$20 mln

Q3 Net Interest Margin (%)

3.75%


Analyst Coverage

  • The current average analyst rating on the shares is "hold" and the breakdown of recommendations is 1 "strong buy" or "buy", 2 "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 Princeton Bancorp Inc is $43.00, about 4.1% below its October 27 closing price of $44.83

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


Reuters Recommended Reads

  • Oct 27 - FFB Bancorp Q3 profit falls on higher provision for credit losses

  • Oct 27 - National Bank Holdings posts Q3 loss on credit provisions

  • Oct 28 - California Bancorp Q3 profit declines on higher provision for credit losses


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.)

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