The tech-driven adaptation of underlying business models continues at pace to disrupt the insurance industry.
This is leading to ongoing changes in the distribution segment of the industry, but more excitingly, movements are happening in fundamental spaces like personalization, underwriting, and claims management.
The same data that allows the insurer to move toward an active insurance risk management model also powers a more personalized insurance model for the consumer. Currently, gross premium classes are based on age, gender, and location. Data science techniques have the potential to allow individually tailored, lower-cost premiums, while also managing the overall risk in the book.
By equipping agents and brokers with the right content for specific segments or individual customers, insurance providers can optimize the performance of their agent networks, who are equipped to provide customers with personalized and trusted advice and guidance.
Thanks to emerging technologies, using richer customer data to drive intelligent decision-making together with a growing investment in content to deliver rich experiences, provide all the ingredients for personalized journeys that satisfy consumers whilst strengthening business performance for insurance firms.
Underwriting and Distribution
As personalized data becomes more reliable and available , more of the underwriting process itself can be automated. This trend towards complete underwriting automation creates an opportunity for the elimination of the traditional distribution channels, which is already being exploited by startup carriers focused on niche markets.
Speeding up the process can also have a considerable impact on a consumer’s likelihood to purchase. In direct-to-consumer channels, agent commissions and other costs can be reduced and even sometimes, eliminated. Automating the underwriting process results in significant savings that increase year over year as the decision models continue to harness property data as well as data intelligence to further automate underwriting. This type of deep learning not only drives loss cost avoidance, but can also expose more accurate assessments and cost savings from labor and vendor management efficiencies.
Another area where there is a considerable amount of human effort in the insurance value chain is in claims processing. Here, the opportunity lies in putting that process in the hands of the consumer. Artificial intelligence has improved dramatically over the last few years and it is having a tangible impact on many industries. Advances in cognitive technology like voice and image recognition and language understanding allows for the creation of bots which takes the customer through the claims process. This can be used to automate much of the decision-making process. Taking steps towards automation and leveraging AI where you can, also frees up skilled adjusters to bring their experience to bear where it can add the most value.
Insurers prepared to make constant changes to their technology and business models will effectively capitalize on these progressing technology trends.
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