What is Risk Data?
Risk data refers to information that helps identify, assess, and manage various types of risks. It encompasses a wide range of data points and indicators collected from multiple sources, providing insights into potential hazards and uncertainties.
Examples of Risk Data include historical market data, credit ratings, financial statements, insurance claims data, and cybersecurity threat intelligence. Risk Data is used for assessing and managing potential risks, making informed decisions, and developing risk mitigation strategies. In this page, you’ll find the best data sources for various types of risk data.
Best Risk Databases & Datasets
Here is our curated selection of top Risk Data sources. We focus on key factors such as data reliability, accuracy, and flexibility to meet diverse use-case requirements. These datasets are provided by trusted providers known for delivering high-quality, up-to-date information.
Biodiversity Proximity Risk Data | Climate Risk Data | 14k+ companies | IBAT Partnership
Trade Credit Risk Data | Web Data | Global Risk Data | 235K+ Sources / 3M+ Articles Daily | Risk Management
Political Risk Data Append API, USA, CCPA Compliant, Political Interest Data
News Data | Company Funding Data | Crime Risk Data | Entity Resolution & Disambiguation
Global Cyber Risk Data | Company Cybersecurity Risk Indicators, 100K+ Events
Environmental Risk Data| USA | Make More Informed Business Decisions | Business Location Data | Places Data
Risk Modeling Data | 3,300 Global Issuers | Dataset for Portfolio Risk Modelling | Market-implied Credit Risk Modelling | Data for Inhouse Risk Models
Global Cyber Risk Data | Email Address Validation
Daily Footfall Data | Location Data | Risk Analysis Data for Investors | UK-wide | 2.7K+ Retail Centres | 600+ Customers
CustomWeather | Flood Risk Data | 5-Day Ahead Flood Outlook PDFs | Map Data| Severe Weather Data | Weather Forecasts | Storm Data
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Popular Use Cases for Risk Data
Risk Data is essential for a wide range of business applications, offering valuable insights and driving opportunities across industries. Below, we have highlighted the most significant use cases for Risk Data.
Main Attributes of Risk Data
Below, we outline the most popular attributes associated with this type of data—features that data buyers are actively seeking to meet their needs.
| Attribute | Type | Description | Action |
|---|---|---|---|
| Integer | An unique identifier (ID) of a company. | View 3 datasets | |
| String | The name of a company or business, might be the legal or brand name. | View 3 datasets | |
| String | The approx. number of employees working for a company. | View 2 datasets | |
| String | The address of a company. | View 1 datasets | |
| String | The domain name of a company website. Potential ID to match company records. | View 1 datasets | |
| String | The email address of a company or contact. | View 1 datasets |
Frequently Asked Questions
How is Risk Data collected?
Risk data is collected from various sources such as government agencies, research institutions, industry reports, specialized data providers, and open data initiatives. These sources gather and analyze data related to financial, operational, environmental, cybersecurity, and other risk factors.
What is Risk Data used for?
Risk data is used to make informed decisions, develop risk management strategies, and mitigate potential hazards. It aids in assessing financial risks, evaluating market volatility, predicting natural disasters, analyzing cybersecurity vulnerabilities, ensuring regulatory compliance, and maintaining a positive reputation.
What’s a quality checklist for Risk Data?
A quality checklist for risk data may include factors such as data accuracy, relevance, completeness, timeliness, consistency, and reliability. It involves verifying the data sources, evaluating the data collection methodologies, assessing data quality controls, and ensuring data integrity throughout its lifecycle.
How is Risk Data priced?
The pricing of risk data varies depending on several factors, including the data provider, the type and depth of data, the level of analysis and insights provided, and the target audience. Pricing models can range from subscription-based services, customized data packages, or pay-per-use arrangements, considering the value and market demand for the risk data.
- Overview
- Datasets
- Use Cases
- Attributes
- FAQ