December 12, 2017
Enhancing Claims Experience With AI
Insurance is now ready for an AI-based analytics platform that can help minimize claim costs and improve customers’ claims experience.
Insurtech and artificial intelligence (AI) have become the new buzz words and mantra in the insurance industry. Creativity and innovation are thriving in Silicon Valley with more than 1,600 technology companies in the insurtech space for underwriting and claims. If you remember, back in the 1990s, experts predicted that if your company was not an internet company, you would not be around for long. That prediction came true, but what about the current prediction that artificial intelligence for claims will change the insurance industry? I believe that it will, and now is the time to
stake your claim for the future.
For the last few decades, insurance companies have yielded massive amounts of data. We know that a robust AI system for insurance claims needs a lot of data to thrive and perform. Because you have the data, how can you start to leverage it and improve your business performance and outcomes? Insurance is now ready for an analytics platform such as Infinilytics’ smartCTM that can help minimize claim costs, and improve customers’ claims experience.
One of the most contemporary AI solutions for claims is fraud and litigation prediction. Imagine the capability of predicting with a 90% accuracy rate if a claim is going to fall into litigation. Your claims team would be able to take immediate steps to mitigate the litigation, customer service would be greatly enhanced and your
claims costs would be reduced.
Insurance companies need to embed A.I. solutions along with their human intelligence so there’s an effective feedback mechanism. Such AI-based claims SaaS solutions aim to:
- Lower loss-adjustment expenses
- Reduce the time to settle a claim
- Identify suspected fraudulent claims with AI pattern matching
- Use sentiment and emotion analysis for litigation predictions
AI solutions using machine learning require careful deployment and breathing time to achieve the return on investment. Machine learning can cause data biases and hide the context of predictions, which makes it unusable by claims organization. Claims organization need to become super users of such AI solutions and understand the context of these predictions and continue to contribute through continuous feedback. Most successful companies have combined human intelligence with AI to change labor-intensive, pattern-driven processes such as claims.
Insurance companies have a vast amount of data. We need to leverage the data and transform the claims process into an efficient and cost-effective business model by quickly bringing artificial intelligence into the claims process.