Business Insurance is continually one of the largest cost drivers for companies, but too often companies are not fully utilizing data and analytics to ensure they have the most cost-effective programs in place. Analyses such as future loss projections, collateral evaluations, EMR analysis and property modeling provide a data-driven basis for making business decisions.
Engaging a dedicated analytics team can help dig into different metrics to be sure the most cost-effective program is put in place. This team can help businesses:
- Identify cost drivers and trends
- Work toward lowering their experience mod
- Evaluate cost effectiveness of large deductibles and SIRs
- Evaluate collateral requirements
- Drill down from policy level to individual claims
- Benchmark program performance to industry averages
- Evaluate program design modifications
An analytics team can run projections to help better understand a company’s risk, allowing the business to choose a program that balances cost with their tolerance for risk. As the market changes, an alternative risk financing structure may be crucial. It’s important to get ahead of the marketplace and allow data to assist your decisions.
Here’s how our analytics team was able to help a retailer review their CAT modeling and determine if they needed to change their limits.
A large RV and camping retailer’s lenders were questioning the limits they carry for CAT perils on their property coverage. The retailer enlisted the support of their Marsh McLennan Agency (MMA) insurance broker who has a financial analytics team ready to help.
The financial analytics team quickly:
- Ran a CAT Modelling report
- Ran a property value stratification report
- Met with the retailer to go over the findings
It was determined the retailer’s limits were sufficient for their CAT modelled exposures. They were then able to meet with the C-Suite to communicate the coverage in place was adequate. This prevented the retailer from having to seek additional limits to satisfy the lenders, saving them a significant amount of potential premium.
The report’s findings also helped highlight where coverage was close to potential losses modelled. This helped the retailer prepare for the potential need to increase limits as they expand.
This is one of many examples of how our team deploys analytics to advocate for our clients, and to be sure we are providing them with best-in-class service. Contact a MMA advisor to utilize your data and analytics to make informed decisions on cost-effective programs.
