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5 Ways Insurance Companies are Driving ROI through Analytics

By June 27, 2019 No Comments
5 Ways Insurance Companies are Driving ROI through Analytics

Insurance providers are rich with data far beyond what they once had at their disposal for traditional historical analysis. The quantity, variety, and complexity of that data enhances the ability of insurers to gain greater insights into consumers, market trends, and strategies to improve their bottom line. But which projects offer you the best return on your investment? Here’s a glimpse at some of the most common insurance analytics project use cases that can transform the capabilities of your business.

Issuing More Policies

Use your historic data to predict when a customer is most likely to buy a new policy.

Both traditional insurance providers and digital newcomers are competing for the same customer base. As a result, acquiring new customers requires targeted outreach with the right message at the moment a buyer is ready to purchase a specific type of insurance.

Predictive analytics allows insurance companies to evaluate the demographics of the target audience, their buying signals, preferences, buying patterns, pricing sensitivity, and a variety of other data points that forecast buyer readiness. This real-time data empowers companies to reach policyholders with customized messaging that is more likely to convert.

Quoting Accurate Premiums

Provide instant access to quotes and speed-up the time to purchase.

Consumers want the best value when shopping for insurance coverage, but if their quote fails to match their premium, they’ll take their business elsewhere. Insurers hoping to acquire and retain policyholders need to ensure that their quotes are precise – no matter how complex the policy.

For example, one of our clients wanted to provide ride-share drivers with four-hour customized micro policies on-demand. Using real-time analytical functionality, we enabled them to underwrite policies on-the-spot that were both accurate and fast.

Improving Customer Experience

Better understand your customer’s preference and optimize future interactions. 

A positive customer experience means strong customer retention, a better brand reputation, and a reduced likelihood Predictive Analyticsthat a customer will leave you for the competition.  In an interview with CMS Wire, the CEO of John Hancock Insurance said that many customers see the whole process “cumbersome, invasive and long.” A key solution is reaching out to customers in a way that balances automation and human interaction.

For example, the right analytics platform can help your agents engage policyholders at a deeper level. It can combine the customer story and their preferences from across customer channels to provide them more personalized interactions that make them feel valued.

Detecting Fraud

Stop fraud before it happens.

You want to provide all of your customers with the most economical coverage, but unnecessary costs inflate your overall expenses. Enterprise analytics platforms allow claims analysis to evaluate petabytes of data to detect trends that indicate fraud, waste, and abuse.

See for yourself how a tool like Tableau can help you quickly spot suspicious behavior with visual fraud analysis.

Improving Operations and Financials

Access and analyze financial data in real time.

In a recent report, Deloitte indicated that ongoing economic growth, rising interest rates, and higher investment income have created ideal conditions for insurers. However, that’s only if a company is maximizing their operations and ledgers.

Now, high-powered analytics has the potential to provide insurers with a real-time understanding of their loss ratios, using a wide range of data points to evaluate which of your customers are underpaying or overpaying for their policies.

Are you interested in learning how a modern analytics platform like Tableau, PowerBI, Qlik or other BI technologies can help you drive ROI for your insurance organization?  Schedule a no-cost whiteboard strategy session to explore the full potential of your insurance data.

Insurance Data Strategy