The more the financial landscape changes, the more essential accurate risk modeling becomes. Financial institutions are looking to newer, updated, and more relevant data points for data augmentation to better assess their business risk. Even the most sophisticated machine learning models are insufficient without the most relevant risk data signals, pulled from a wide variety of data sources.
Some examples of alternative data for lending are:
- Data on financial activity such as income, borrowing, payment history, assets, and liabilities.
- Company data that includes years in operation, company type, and search trends.
- Web presence data, such as domain creation date, domain expiry date, number of related links, and website global traffic rank.
- Internet and social media data such as online reviews and online ratings.
- Company credit history.