Moodys (MCO) Asset Writedowns and Impairment (2012 - 2023)
Moodys (MCO) reported Asset Writedowns and Impairment of $32 million for FY2024, down 8.6% from $35 million in FY2023.
Analysis
Moodys (MCO) Asset Writedowns and Impairment (2012 - 2023) Analysis & Trends
Dating back to FY2012, Moodys' Asset Writedowns and Impairment record includes 6 years.
- Asset Writedowns and Impairment has a five-year compound annual growth rate of 5.1% (FY2019 to FY2024).
- Five-year annual Asset Writedowns and Impairment spans a low of $29 million in FY2022 and a high of $36 million in FY2020.
- According to Business Quant data, Asset Writedowns and Impairment came in at $35 million in FY2023 (+20.7%), $29 million in FY2022 and $36 million in FY2020 (+44.0%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | S&P Global | 113.90 Bn | 109.50 Bn | 2.98 Bn |
| 2 | Moodys | 76.48 Bn | 68.91 Bn | 1.67 Bn |
| 3 | Msci | 38.99 Bn | 37.33 Bn | 717.10 Mn |
| 4 | Verisk Analytics | 21.33 Bn | 15.96 Bn | 572.90 Mn |
| 5 | Equifax | 16.47 Bn | 15.87 Bn | 926.40 Mn |
| 6 | TransUnion | 12.16 Bn | 9.14 Bn | - |
| 7 | Factset Research Systems | 9.52 Bn | 8.28 Bn | 310.73 Mn |
| 8 | Morningstar | 6.89 Bn | 4.79 Bn | 423.90 Mn |
| 9 | Mastercard | 480.84 Bn | 440.75 Bn | - |
| 10 | Cme | 94.54 Bn | 94.54 Bn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2023 | 23.00 Mn |
| Dec 31, 2022 | 29.00 Mn |
| Sep 30, 2020 | 11.00 Mn |
| Dec 31, 2019 | 14.30 Mn |
| Sep 30, 2019 | 2.00 Mn |
| Jun 30, 2019 | 25.00 Mn |
| Dec 31, 2012 | 11.20 Mn |
| Sep 30, 2012 | 1.00 Mn |
API Access
Moodys Asset Writedowns and Impairment 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=asset-writedowns-and-impairment&ticker=MCO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "asset-writedowns-and-impairment", "ticker": "MCO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=asset-writedowns-and-impairment&ticker=MCO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();