Data analytics are finding their way into just about every line of business, and now the insurance industry is getting in on this growing trend. Insurance companies are finding that raw data can be converted into an immediate understanding of needed coverage, personalized attention for policyholders, and an expedited claims process. Let’s take a look into how insurers are using algorithms to their advantage in various types of insurance coverage.
Homeowners Insurance
Data science allows for insurance companies to rely upon predictive models to get an understanding of the type of coverage that a homeowner may need. When using home insurance compare tools, insurance providers are able to gain a quicker assessment of the homeowner’s insurance policy that this prospective customer may be looking for. This can range from the personal belongings in their household to an idea of the premium or deductible they are seeking for protection in the event of an accident or peril.
Data analytics also help insurers to access, distribute, and update reference data in real-time. Advanced analytics can help potential policyholders understand what they may need for a renters insurance or home insurance policy in their location. With security options for the handling of datasets, homeowners can feel like their policy is the only policy being looked after with a personal touch. Insurance companies are able to utilize machine learning and analytics tools to get an assessment of the amount of coverage that a dwelling may need when disaster strikes. This not only provides peace of mind for the insured, but that reference data can expedite application systems for additional coverage or changes to existing home insurance coverage.
Auto Insurance
The use of data analytics not only helps for a policyholder with a new home but in getting protection for their car. With frameworks established through data visualization, insurance companies can help vehicle owners explore the coverage level that is best for them. While there are basic standard policies for replacement cost coverage, data analytics can promote extra coverage and assure customer satisfaction through a variety of insurance quotes by offering a personalized touch and understanding as it relates to a car insurance policy.
With real-time data processing, an insurance company can determine the risk on the road for a driver added to the coverage. This comes in handy when a younger family member is placed on a car insurance policy, as they may be deemed high-risk, impacting premiums for coverage. This also comes to the aid of the customer in the claims process, as data analytics are able to assess replacement value based on new information received. A data system can make life easier for a protected driver in the event of a claim, and boost their relationship with their current insurer.
Health Insurance
Data analytics can use not only real-time but historical data for the benefit of the insured and themselves. The healthcare field has found itself relying on analytics and electronic communication more than ever because of the COVID-19 pandemic. Real-time analytics have become part of a database formed in contact tracing, detecting coronavirus cases, and able to link them within 24 hours to a cluster of cases from one location. Statistical models were also constructed across the U.S. to monitor cases, hospitalizations, intubations, and, unfortunately, deaths as related to the pandemic.
The health insurance market has been able to maintain a standard of data quality. This allows insurance companies to collect personal information in a timely fashion regarding insurance claims while keeping a personal touch and quickly reach solutions whether the insured is a new customer or a longtime partner. This also allows health insurance providers to get an idea of medical bills and the financial impact on different customer segments.
