How does data analytics boost customer loyalty in the insurance industry?

The world is still in recovery mode amid the evolving global health crisis. Interest rates are lower than ever to encourage loans and investments, however, this has also resulted in minimal returns for paid-in premiums. 

The insurance sector is seeing an unprecedented decline in product penetration growth—especially in mature markets. The latest statistics have revealed that the fee structure for financial advisors presents a conflict of interest that can harm consumers, especially in Europe, the US, and Australia. 

This has industry analysts and experts hunting for new solutions. The only viable solution seems to be adopting a more customer-centric approach to insurance.

The path to achieving that involves big data. Big data can provide the insurance industry with plentiful, unprocessed, raw information, and data analytics platforms can process it into the insightful data that is needed to incite change. 

Does having a loyal customer base solve the challenges facing the insurance industry? 

Data shows that customers who are loyal to their insurers cost less to serve, stay longer, buy more, and recommend their insurance provider to family and friends. The survey, however, also reveals that insurance companies find it hard to build customer loyalty. 

The same set of data processed through different filters allows us to understand that the main reason behind this is the lack of interaction between insurance providers and their customers. 

Enhance brand image and improve customer satisfaction

Data analytics provide insurance companies with the insights they need to build all-inclusive policies. This means that customers can get tailor-made policies that fit all their requirements instead of purchasing multiple plans from the same provider. 

Data analytics can also help insurance companies optimise their communication channels to have better interactions with their clients. 

Knowing the different demographics that form your customer base and noting their preferred mode of communication, whether it is through a website, in-person, phone call, or video chat can help build relatability. 

In short, interaction is the pillar of building customer loyalty and data analytics is its facilitator.   

Solve fraud issues and keep premiums low

Fraud is one of the biggest issues faced by the insurance industry. Statistics suggest that at least one in ten of every claim filed is fraudulent. Considering the number of policyholders these companies serve, this can reach a staggering number. 

The result of this is an increased premium for the rest of your client base. With data analytics, however, it is possible to find these cases, resolve them, and prosecute the culprits swiftly before it causes widespread effects.  

Big data solutions such as social network analysis and telemetrics can be used to achieve this. 

Leveraging these solutions pays off because keeping your premiums low is a guaranteed way to keep customers satisfied and loyal. 

Accelerate settlement cases and streamline customer payouts

Data analytics can also be used to speed up settlement cases. The main reason lawsuits and claims take a long time to settle is because of the large amount of analysis that needs to be done. 

Data analytics allow firms to check the claim, analyse it, and access the customer’s claim history instantaneously. This can increase the speed with which a firm can give customers their payouts.  

Innovations and solutions geared at improving customer interactions 

The rise of online aggregators or comparison sites, to use the more popular term, has led to an even greater decline in the interactions between customers and service providers.

Technology has, however, allowed many companies to redefine their image and service as insurance providers in order to build meaningful relationships with their clients and, in turn, develop loyalty. 

These changes and innovations would not have been possible without the insights gleaned from data analytics and the advances made in data modelling techniques. 

Advances that include:

• Insurance companies investing in wearable devices that can help improve worker safety. 
• Funding smart home technology to minimise flood damage.
• Gamifying safe driving to stimulate consumer engagement. 
• Stolen vehicle tracking and recovery services. 

Building insurance companies that are customer-centric with data analytics 

With the information gathered from social media, mobile data browsing history, and purchasing history, companies in the insurance industry can gain a more personal understanding of their clients. 

Equipped with this information, they can find swift solutions to process and service issues, providing the customer with an easier and more wholesome experience. 

When coupled with the ability to build insurance plans and policies tailor-made for individual customers, we can confidently say that big data and data analytics together can help increase customer satisfaction and build loyalty.