Insurance, Insurance Companies
Claim Analytics, Predictive Modeling, Predictive, Model, predictive model, Insurance, Benchmarking, Scoring, Claims, Data Mining, Patter Detection, Acturial, Actuary, Long Term Disability, disability, claims data model sample, fraud detection, probablility
Claim Analytics has now developed a model to predict the likelihood that a newly reported LTD claims will be approved. The model was built by quantifying patterns in historical approval decisions and applying this logic to score newly reported claims on the likelihood that they would be approved based on an insurance companies existing practices. The model was field test tested and shown to be an accurate predictor of approval.
On a weekly basis, newly reported claim data is transmitted to Claim Analytics with required data fields and Claim Analytics will score these claims on the likelihood that the claim will be approved.
Claims will be scored from 1 to 3 as follows:
- A score of 1 will indicate that an eligibility check and then can approve the claim,
- A score of 2 will indicate that eligibility and compliance to the duration guidelines need to be checked and then the claim can be approved.
- A score of 3 will indicate that the claim must be manually adjudicate the claim before approving it.
Claim Analytics has seen more that 30% of claims falling into the scores ‘1’ and ‘2’ offering our customers a significant operational cost saving over a fully manual adjudication process.
, Insurance Companies