Your Company: SBI General Insurance
Company background: SBI General Insurance founded in 2009. is one of the largest general insurance organizations in India – with nearly 141 branches serving over 20.8 crore customers.
In 2022, recognized as the 'Best General Insurance Company of the Year' at the 'Third Emerging Asia Insurance Awards' organized by the 'Indian Chamber of Commerce'.
Your Name: Yashaswi Malot
Your Title: Dy- Vice President Analytics & CLM
Your Country: India
Customer Awards Category: Innovative Problem Solver
Tell us about the business problem you were trying to solve?
Insurance intermediaries, including agents and brokers, play a pivotal role in the industry by assisting customers in finding suitable insurance policies and connecting insurance companies with potential clients. On the other hand, underwriters are tasked with evaluating and analyzing the risks associated with insuring individuals and assets.
A critical decision confronts the business: whether to rely on individual intelligence or restrictive data in accepting the risks tied to its products. The Motor PVT4W loss ratio is high, and the absence of a tool to measure the impact of changes in underwriting guidelines on the loss ratio poses a challenge. Furthermore, there is a lack of a tool to guide the sales team on policy mix at the intermediary level, where the right policy mix can significantly impact profitability and loss ratio.
Our goal is to empower underwriters in the organization to make decisions regarding the number of policies to be sold by an intermediary based on their experience and the output of an advanced analytical model. This approach aims to achieve maximum profits by minimizing the loss ratio in the insurance business. We envision an interface that can swiftly calculate Gross Written Premium (GWP) and Loss Ratio (LR) under various permutations and combinations of risks, ultimately yielding the best results. Additionally, the interface should allow for the modification of the analytical model's results to transform them into achievable goals while providing flexibility to pass on benefits to intermediaries. The desired interface should display real-time outputs of an optimization model, showcasing the optimum number of policies based on the risk-reward dynamics for each intermediary.
How did you use SAS to solve that business problem? What products did you use and how did you use them?
The above problem was solved in two parts:
- The first part was to solve the business problem of maximizing benefits to organization was solved by using optimization algorithm to map optimum number of policies to be sold by each intermediary. The model was run on SAS Studio of SAS Viya and the results were accumulated in CASLIBs.
- The second part of the problem of providing the interface to underwriters to use this model and run various scenarios by changing the output of the model was achieved using Data Driven Content (DDC), Job Execution Service (JES) & SAS Visual Analytics (VA) Interface. Using DDC-JES an interface was created on SAS Visual Analytics that provides an editable table on VA dashboard. This table interns behave as an input to 2nd level logical scenario analysis by altering the output (Number of Policies) of optimization algorithm and re-calculating the loss ratio & gross written premium. In addition to the number of policies the model also factors in impact of rewarding the intermediary to increase the sale of policies.
The Tool once deployed also captures the finalized target number of intermediaries and saves the data for further tracking and monitoring. The 2nd part of Tool provides this monitoring functionality to consistently track if intermediaries have reached their goals.
The tool aims to highlight Intermediary wise historical business trends and actively suggest the optimal policy mix at Intermediary level which shall help to improve profitability as well as business growth.
What were the results or outcomes?
The above solution is being used by underwriters across the organization to better plan and approach maximizing the profits and minimizing risk. It has heavily reduced the time of monitoring the GWP and LR at an intermediary level as well as organization level. As a result of the continuous efforts by all teams, the Motor PVT4W loss ratio has improved by 9%.
Why is this approach innovative?
This prescriptive tool, which combines a predictive tool for estimating loss ratios with a prescriptive tool for optimal simplex linear programming, is unique in the insurance industry and will be a key competitive differentiator. The use of model output on SAS VA dashboard and the functionality it provides can no longer be called a simple dashboard. It itself has become an application that provides specific features to solve the above business problem. This is unmatched to any solution across the organization.
What advice would you give to new SAS users?
SAS has capabilities to solve most complex business problems and it enables quick development and deployment of such solutions. There are features / functionalities that you might not be aware of but with a little research those could easily be used.
