NSTS Bancorp, Inc. (NSTS) Operating Expenses (2020 - 2026)
NSTS Bancorp (NSTS) reported Operating Expenses of $3.44 million for Q2 2026, up 25.4% from $2.74 million a year earlier.
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Analysis
NSTS Bancorp, Inc. (NSTS) Operating Expenses (2020 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, NSTS Bancorp's Operating Expenses came in at $11.23 million, up 9.6% year-over-year; for FY2025, it was $10.31 million, up 6.1% from FY2024.
- Operating Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 10.4% (FY2020 to FY2025).
- By year, Operating Expenses came in at $9.72 million in FY2024 (+23.8%), $7.85 million in FY2023 (+14.2%), $6.88 million in FY2022 (+22.8%) and $5.6 million in FY2021 (-10.8%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q3 2020.
- Year over year, Operating Expenses gained in six of the last seven quarters, with growth averaging 11.2%.
- The high point for year-over-year Operating Expenses in five years was Q4 2023 (growth of 42.0%); the low point was Q4 2021 (a decline of 19.4%).
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Peer Comparison
Historic Data
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Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.44 Mn |
| Dec 31, 2025 | 2.54 Mn |
| Sep 30, 2025 | 2.50 Mn |
| Jun 30, 2025 | 2.74 Mn |
| Mar 31, 2025 | 2.53 Mn |
| Dec 31, 2024 | 2.56 Mn |
| Sep 30, 2024 | 2.40 Mn |
| Jun 30, 2024 | 2.49 Mn |
| Mar 31, 2024 | 2.26 Mn |
| Dec 31, 2023 | 2.44 Mn |
| Sep 30, 2023 | 1.95 Mn |
| Jun 30, 2023 | 1.79 Mn |
| Mar 31, 2023 | 1.67 Mn |
| Dec 31, 2022 | 1.72 Mn |
| Sep 30, 2022 | 1.68 Mn |
| Jun 30, 2022 | 1.83 Mn |
| Mar 31, 2022 | 1.65 Mn |
| Dec 31, 2021 | 1.33 Mn |
| Sep 30, 2021 | 1.36 Mn |
| Jun 30, 2021 | 1.40 Mn |
API Access
NSTS Bancorp, Inc. Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=NSTS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NSTS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=NSTS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();