Accelerate decision making and fine-tune pricing with optimal data quality
A wealth of data is available to the insurance industry today. Recognizing the untapped value, carriers are investing millions of dollars into sophisticated analytics, cloud computing, artificial intelligence (AI) and machine learning (ML) to turn that data into insights that will inform decisions at every level of the business.
However, despite being the very foundation of successful AI and ML developments, the quality of the data itself is often an afterthought. The result? Poor data quality can have a direct impact on the customer experience and lasting consequences for underwriting and pricing.This white paper offers insights into:
- The main factors that affect data quality, including source, accuracy, completeness and coverage.
- Why carriers might be seeing the quality of their data declining despite all the new datasets available.
- How optimal data quality helps carriers at every stage of the policy lifecycle.
You don’t have to settle for making long-term decisions based on poor quality data. In fact, if you’re willing to make an investment in your data, there are several actions you can take to improve the quality of the data you use starting today. Read our recommendations and join leading carriers that use optimal data quality—to differentiate themselves from competitors, develop more positive interactions with customers, build more accurate pricing and make better decisions.