According to Harvard Business Review, low-quality data costs U.S. businesses $3.1 TRILLION each year.
Especially for insurance carrier and MGA underwriters, it’s essential to have high-quality data. Injecting low-quality data into an underwriting workflow can create a host of downstream problems:
- Misclassifying risks
- Adverse selection
- Compliance risks
- Inefficient workflows
Read this whitepaper if you’re looking to automate your underwriting process and capture more small commercial business. You’ll get more info about how to recognize low-quality underwriting data, as well as the top 6 things to look for in a quality data and analytics partner.