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These are examples of solutions Claim Insights can bring to its clients.
SolutionsData Strategy:
Before embarking on accumulating lots of technology and software solutions, a company must define what their data strategy will be, how they will use the data to create a competitive advantage and how the solutions will add to top line revenue, operational improvements, and add to customer value creation. For those companies that are just embarking on using data to improve their businesses or refining their current data strategy, Claim Insights will work with you to think through and design a Data Strategy and the solutions best suited for your current state of readiness.
Fraud:
Supervised models are available that identify/flag claims that exhibit fraud or abuse characteristics or known patterns in the data. In addition, unsupervised models effectively identify new patterns of fraud. These can be either clustering or anomaly detection models where the specific result is unknown. The actual model chosen is updated with new data making the models more accurate in their detection of potential fraud.Recovery Models:
Predictive models can be built that identify those claims that should be referred for recovery. This is applicable in the lines of business of workers compensation, automobile, and disability insurance.
Outcome Models:
Models may be built using supervised models to flag those cases that are likely to deteriorate into more serious or complex cases. Other examples may include models designed to identify characteristics of claims that drive the outcome so that remedial steps can be taken to mitigate the potential adverse outcomes.
Segementation Strategy:
Models can be built to identify claim characteristics that allow them to be diverted to the right person with the right expertise at the right time. For example, claims meeting certain characteristics such as a minor impact claim, with no third party involvement and minor injuries to the insured driver, may be sent automatically to a fast track unit for processing. Other times, claims or components of the claim, may be auto-adjudicated if it meets certain specifications and does not require human centric decision making.
Cost Containment:
Business Intelligence studies of the data may be done to identify the real cost drivers of claims at both a macro and micro level. Once these cost drivers are known purposeful strategies may be built to address and control the costs. These costs cover the range of indemnity, medical, and loss adjustment expenses.
Vendor Management:
With data at your fingertips, it is now easier to manage outsourced functions and create the opportunity to work with your vendors as partners.
Data Quality Audits:
As we integrate multiple data sources from both inside and outside the organization we will be identifying areas where data quality needs to be improved. In addition, Claim Insights will work with you to identify new data elements that should be captured and perhaps eliminate data elements that are unnecessary for achievement of the Data Strategy.
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Predictive Modeling:
Predictive modeling explores cost and business drivers, creates special studies, and identifies target variables. We help companies advance from claims processors to powerful claims management organizations.
Data Aggregation