RiSIC does not bring only the technology for detecting WAF in claims, but also the experience on how to apply this into existing complex environments. The methodology we developed leverages our experience in this domain and maximizes the benefits of the innovative technology.
Basic hypothesis of the methodology is that fighting WAF is a continuous process. Insurance companies themselves are not able to address the motivations because of which people do WAF. Therefore, WAF will continue to exist taking different forms: blocking WAF one way without removing the original incentive will lead to individuals looking for other ways to get the same benefits.
When kicking off new implementation, the assessment is a critical step in establishing the base line. Once completed, we immediately identify the population behavior. We can distinguish outliers but we also detect and adjust positive and negative behavior. The second step is to automate patterns that the system accurately detects. In the case of claims processing, we identify immediate wins of claims whose decision can be automated.
We were able to identify a set of claim items for denial, with accuracy higher than 90%. Once identified, we managed to successfully deny 60% of them. The 3rd phase, we call it augment, looks at new patterns which are not trivial and not easily detectable in the data.