Data Quality is a challenge. We hear this statement for many insurers that we speak to. The concern about data quality is a barrier to implement AI systems, as stated by many insurers and surveys. The availability of good provider data and health insurance, or third party data and property casualty insurance, is a challenge.
But did you know that AI software can be used for identity resolution and help you build a provider registry, or a third party registry, or other really useful metadata that can help you implement complex systems like AI? Data quality can be addressed by your AI Software as a Service vendors and shouldn't be a barrier to move forward.
Given the current environment, where we expect fraud to rise significantly, delays and acting could cost you a lot and put you at a competitive disadvantage to those companies that are already keeping pace and implementing this technology today. So, if you're planning to implement AI in the coming years, you should probably get started implementing those systems now. Do pilots, have proof of concepts, and address those data quality issues with your AI SaaS vendors. If you start now, you can begin to stop fraud in its tracks.