Nerdy (NRDY) Non Operating Interest Expenses (2020 - 2026)
Nerdy's Non Operating Interest Expenses came in at $672,000 for Q2 2026, up 1.8% from the prior quarter.
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Analysis
Nerdy (NRDY) Non Operating Interest Expenses (2020 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Nerdy reported Non Operating Interest Expenses of $1.33 million, up 3.3% year-over-year; for FY2021, it came in at $3.79 million, down 22.7% from FY2020.
- Going back by year, Non Operating Interest Expenses was $4.9 million in FY2020 (+133.4%) and $2.1 million in FY2019.
- The Q2 2026 figure represents the highest quarterly Non Operating Interest Expenses since Q3 2021.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | - |
| 2 | Veeva Systems | 46.20 Bn | 18.45 Bn | 695.95 Mn | - |
| 3 | Samsara | 22.32 Bn | 19.09 Bn | 392.58 Mn | - |
| 4 | Toast | 16.73 Bn | 9.40 Bn | 516.00 Mn | - |
| 5 | Ptc | 15.53 Bn | 14.35 Bn | 490.47 Mn | 15.80 Mn |
| 6 | Duolingo | 13.32 Bn | 8.49 Bn | 216.74 Mn | - |
| 7 | Trimble | 13.32 Bn | 12.38 Bn | 674.90 Mn | 20.90 Mn |
| 8 | Manhattan Associates | 11.58 Bn | 10.58 Bn | 168.33 Mn | - |
| 9 | Costar | 11.10 Bn | 5.07 Bn | 728.00 Mn | - |
| 10 | Nerdy | 103.21 Mn | -51.85 Mn | 27.98 Mn | 672,000.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 672,000.00 |
| Mar 31, 2026 | 660,000.00 |
| Sep 30, 2021 | 1.29 Mn |
| Dec 31, 2020 | 1.27 Mn |
| Sep 30, 2020 | 1.27 Mn |
API Access
Nerdy Non Operating Interest 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=non-operating-interest-expenses&ticker=NRDY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-interest-expenses", "ticker": "NRDY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=non-operating-interest-expenses&ticker=NRDY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();