The evolution of underwriting in the insurance industry
The birth of data science, combined with the evolution of AI, remodelled traditional underwriting into a more effective and sophisticated process capable of increasing sales while lowering risk without compromising speed.
Many insurance companies mistakenly believe that automating manual processes are all that is required to improve underwriting efficiency. However, this only helps superficially, and the old obstacles are still inherited. In general, modernisation requires more than just improving aged systems, but instead, adjusting the mindset and looking for completely new ways of doing things.
AI-powered underwriting can change the perspective of how insurance companies are related to their clients, migrating from a transactional relationship to a customer-centric one. It is important to sell a product and understand how the customer feels throughout the whole journey. Instead of collecting intermittent feedback through costly research methods, AI-powered underwriting can gather and analyse enormous volumes of information coming from different sources and understand consumer behaviours along the different touchpoints.
Just "going digital" is no longer enough. Maximising conversion and improving sales funnels on digital channels becomes ever more important. Converting online visits into actual policy sales is a combination of art and science. McKinsey's research shows how digitally smart insurers convert digital customers at six times the rate of their peers. And it seems that the key lies in personalisation and continuous improvement of the customer experience.
Credolab’s embedded underwriting technology can uncover insights that further explain a user's digital behaviour. For example, our tech can detect behaviours similar to confirmed fraudulent and risky ones without compromising the user experience in any application process. Having this information in real-time could help insurers deliver a more delightful experience and increase conversion rates. Thus, this can also improve the agent/broker experience.
According to McKinsey, besides improving the underwriting process, data could also enable a more refined and granular risk categorisation. The company exemplifies that mortality outlook can be meaningfully informed by factors such as charitable giving, pet ownership, fitness protocols, and a range of other behavioural indicators. Different types of risk and premiums could be detected according to a set of patterns without the need to ask too many questions to clients. For instance, it is possible to predict the probability of a customer filing a claim without jeopardising the user experience, fully complying with privacy laws and in harmony with the existing underwriting processes.
One of the main benefits of AI-powered underwriting is that no manual processes are involved. Therefore, insurance companies can make more decisions simultaneously, at a lower cost, and reach new prospects in minutes. This improves customers' experience and loyalty since waiting times are reduced compared to traditional underwriting. At the same time, and most importantly, privacy laws are respected. Credolab uses smartphone and web behavioural metadata that do not contain any Personally Identifiable Information (PII) and are previously consented by clients.
In times where speed and data are crucial to succeed, AI-powered underwriting benefits are an unmistakable solution. However, the market demands profoundness in the path towards modernisation, which means a complete change in mindset and a transformation in how things should be done and how clients should be treated.