Advanced Analytics
To forecast the claims fraud risk: Classical Time Series Models, Regressions, Autoregression, Neural Networks , GAM models
To cluster the points/meters in groups with similar behavior, hierarchical clustering algorithms
APP is provided with a library of pre-configured business rules to detect the fraud risk
To select the most effective model in library, back testing simulation logic
Key Differentiators
The APP allows to reduce cost reducing the total time of detecting frauds since the whole detecting process is completely industrialized and automated
The user will be able to focus on the most risky clients first increasing the effectiveness of the detecting process
The process does not require any extra data flow like email or paste and copy increasing the speediness of the process and reducing the operational risk
The algorithm will suggest how risky can be a new client reducing the risk to acquire a new client