Wipro Ltd - Subrogation

Subrogation solution helps the motor vehicle insurance industry and its agents to analyze and predict if any insurance claim will be entitled for Subrogation or not.

パートナーに問い合わせる

Subrogation

About Subrogation

The term Subrogation in the Insurance industry is the right for an insurer to pursue a third party that caused an insurance loss to the insured. This is done as a means of recovering the amount of the claim paid to the insured for the loss.

Subrogation Solution

Wipro’s Subrogation solution is created with the goal to help the motor vehicle insurance industry to analyze and predict if any insurance claim will be entitled for Subrogation or not. The insurance agent will be able view data insights and take informed decisions. Revolution Analytics is used for carrying out statistical analysis.

Profiling of the claims data and other data analysis like missed opportunity and prediction can be done using this solution.

High Level Architecture of the solution:

SQL Server dimensional model is the source for reporting. Output of the “R” processes is stored in SQL Server database and it is used as source for exploratory analysis reports. Power BI reports are created using Power BI desktop import option and reports are hosted on Power BI Service.

Functional Overview of the solution:

The solution would empower the organizations to identify leakage in the recovery process, translate missed opportunities and savings and improve the recovery accuracy and case referral.

It has following dashboards and reports.

Policy Distribution analysis:

This report provides holistic view of policy distribution based on time, Policy tenure, Policy Brand, Provider Brand, Claim Age and Gender etc.

Revenue:

This tab displays the KPI associated with the revenue. It gives insight about the revenue earned by the organization and helps in taking useful business decisions to increase the revenue.

Claim Analysis:

Helps to understand the behavior of the triggers and the impact of a claim liability will be visualized

Vehicle Analysis: This report give us useful insights about the vehicle involved and also about the drivers and their driving behavior. These insights lead us to help the company to take important strategic decisions on targeting potential customer groups.

Model Output:

These reports are based “R” model output. This enables one to find out how accurate the predicted output as compared to the actual output is.

These reports are based “R” model output. This enables one to find out how accurate the predicted output as compared to the actual output is.

Gain Chart: They are visual aids for measuring model performance. The greater the area between the lift curve and the baseline, the better the model

Lift Curve: Lift is a measure of the effectiveness of a predictive model calculated as the ratio between the results obtained with and without the predictive model.


Power BI パートナーになりたいですか?

認定パートナーは、チームにとって重要な存在です。 新しいビジネス チャンスを見つけ、つながりを作り、御社の才能と経験を世界中の Power BI ユーザーと共有してください。

サインアップ

サインアップでお困りですか?
お問い合せください pbiptnr@microsoft.com

Request demo