Insurtech Embracing The New: How Machine Learning Factors Into Big Changes

Typically, insurance companies only get to  process around 10-15% of data they have access to, according to Accenture. At least, that’s what it was like in 2018 when the report was generated. With massive amounts of data needing to be analyzed and collated, companies and industries are now  turning to machine learning to usher in a new era. So what big changes have leaders in insurtech embraced because of machine learning?

Consumer Engagement

Cerity.com explains that 24/7 availability is important in the insurance sector for establishing client trust. Machine learning has helped insurance companies with this by introducing the concept of chatbots. A chatbot applies machine learning algorithms to sift through data in order to be the first line of interaction for consumers. While there was some initial hesitation, now around 69% of consumers prefer engaging with a chatbot as it gives them an instantaneous response to queries, according to Cognizant. So the insurance industry is effectively changing the way they interact with their clients.

Fraud Detection

Around  81% of major insurance companies have experienced a data breach within the last two years, according to KPMG. Hackers and other criminals are trying to find new ways to defraud insurance companies, which is why insurtech needed to up its game. Machine learning introduced AI-based fraud detection protocols. It allows insurance firms to have a speedy analysis of claims in order to flag any fraudulent or suspicious ones. Machine learning also gave birth to stronger shields against cyberattacks.

Claims Processing

With the number of clients that an insurance company may have, there exists a massive amount of data to sift through. The old protocols were to have a manual review of claims that consume extensive time and manpower. This leads to prolonged processing times, which may be to the detriment of both the clients and the company itself. Machine processing allowed insurance companies to put parameters into algorithms that analyze large amounts of data in a short amount of time. The end result is that clients get a swift review of their policies and a clear answer. It also ensures that the effort placed by employees is streamlined, as they have a better handle of facts.

Personalized Marketing

No two clients are ever the same in the field of insurance. In order for insurance companies to survive, they need to be able to attract new clients and retain their existing client base. This requires understanding the particular needs of each client and tailoring their policy to best fit their needs. Insurtech now uses software and programs that draw insight from data about the client based on their provided information, and match them with a plan that fits. The algorithm used for this purpose continuously learns from new information being added. So as time goes on, the better it is able to match clients with the plans they need.
Insurance companies definitely have the right idea of embracing machine learning to improve what they offer. Ultimately, improving their processes will benefit their clients and their bottom line. Given that technology is on a continuous improvement trend, it will be interesting to see how else newer machine learning protocols will induce more changes in the field of insurance.
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