Underwriting is one of the most important parts of insurance. Improving this process will help an insurer better evaluate risk and offer better prices. The key to this is correctly leveraging the magnitude of data that now exists.
It cites a recent global survey, which identified the top three underwriting process challenges, as seen by insurance executives. These were: an increase in automation adoption to drive speed, efficiency, profitability and lower costs, utilising more data from more diverse data sources to build better risk models, and a rise in AI usage to make everything more cost-effective.
The traditional underwriting process makes use of a lot of data. Asking consumers about a customer’s behaviour, understanding bind and renewal patterns, understanding the likelihood of events, and more. However, with more data being created each day, an insurer’s competitive advantage comes from leveraging all of this new information and doing so quickly, Quantexa said.
When a firm is looking to implement an intelligent underwriting solution, they need to be sure it can access the data fast, analyse it and derive meaningful context.
Quantexa went on to explain several issues with the traditional underwriting model, including the increasing difficulty there is with effectively handling data. Another major problem is the time spent finding and connecting unstructured data with structure data.
It said, “It’s estimated that more than 80% of enterprise data is unstructured, but only 10% of it is used alongside structured data. On top of this, over 60% of data teams’ time is spent normalising and cleansing data from different formats. With the growing complexity of data formats and structures, it is crucial to move away from rigid data format tools to a more schema-less data fusion approach, leveraging tooling such as a dynamic entity resolution.”
The InsurTech company also outlined the issue of uncovering context about a customer. It stated that under 30% of organisations create a holistic customer view and those that do struggle to do it accurately and dynamically for different business uses. There is a rising need to quickly extract context from public and third-party data sources to give internal systems a more unified view of risk.
With all these issues in traditional underwriting, Quantexa believes the future is firmly with decision intelligence. It said, “With the continued explosion of data and the growing importance of profitability, speed and customer experience, insurers must act now. All insurers should be re-evaluating if they are really set up for intelligent underwriting and are well equipped to solve the above challenges.”
Decision intelligence will avoid historic fixed/predefined data models and will be able to ingest data from any source or format. The technology also allows for dynamic entity resolution and network generation, which fives single views of customers and can reveal any entity connections they have. Combined with contextual data exploration tools, they give underwriting teams, actuaries, and analysts with powerful data visualisation tools.
Finally, decision intelligence gives a unified and normalised process of the data decision estate throughout the enterprise, ensuring the right data is with the right person.
It concluded, “Insurers should be considering how they can bring data to the centre of their business, harnessing the power of new data-driven and connected decision ecosystems. This is contextual decision intelligence. And this is the journey on the quest for digital underwriting.”
Read the full blog post here.
Copyright © 2021 FinTech Global