In the first four parts of this series, we have considered how the underwriting ecosystem is evolving in terms of channels, products, data, analytics, services, tools, operations and management. What we haven’t covered is how the underwriting process is evolving.

In a simplified underwriting process, there are two steps: data gathering and triage. Data gathering is where we collect the information necessary to underwrite the risk. Today, the data gathering process is transforming in a number of ways. We now collect data directly from the customer and can integrate large amounts of external data into the process. This limits the information we need from the insured while providing more complete information for the underwriters. In the digital landscape, underwriters gather data through various channel portals or, if submitted through traditional submissions, can handle it offshore or through the use of robotics and automation.

Triage is when carriers evaluate submissions to see if they match their risk appetite and to route them to the correct underwriting path/underwriter. Underwriters perform triage by using complex rules algorithms, analytic rules engines or judgment. In the digital age, carriers look to onshore/offshore underwriting operations centers, or most recently to artificial intelligence or machine learning solutions.

The future of the underwriting process in the digital age

Once triaged, we handle submissions and renewals in one of three paths:

  1. Automated underwriting, in which rules, predictive models and more recently, machine learning/artificial intelligence evaluate, rate, and price the submissions, with or without the support of an underwriting/operations hub.
  1. Flow or low touch underwriting, which are hybrid processes in which a percentage of the submissions can be handled via automated underwriting, but where others are still too complex and need the attention of underwriters, either completely or in part. In these cases, we see the underwriter supported by rules, analytics, and potentially by machine learning and artificial intelligence.
  1. Full touch underwriting, where we have to handle rating, setting terms, pricing, quoting and negotiating the risk. In this flow, we see the analytics, rules engines and machine learning tools move from enacting prescribed decisions to supporting the underwriter in making the decision. It is in this space that some of the newer technologies such as comparative analytics, machine learning, and artificial intelligence hold the most promise.

This simplistic view of the underwriting process provides a way to consider the different underwriting process options, but it is not the whole story. The market drivers of speed, cost efficiency, transparency, and customer service are changing underwriting as they are changing every other area of insurance. In the end, the underwriting process needs to be designed to best meet the customers’ needs and expectations for a given product in a given channel. Every other aspect of the underwriting ecosystem bends itself to that core goal.

The high performers of tomorrow are going to be the ones that figure this out first. They will choose the customer segments, channels, and product offerings in which they want to compete. They will then adapt every other aspect of the underwriting ecosystem to deliver superior services and solutions that are profitably priced to the market.

So ask yourself two questions:

  1. Am I thinking about my underwriting process from the outside in?
  2. Have I considered or thought about all of the aspects of the evolving digital underwriter ecosystem?

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