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Underwriting – meet the new kid on the block

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Published on:13th August 2021
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For many underwriters, the data explosion provides both a challenge and an opportunity.

Solving complex risks problems is a highly sophisticated process that relies not only on deep and extensive first-hand experience but also on mining and interrogating multiple, disparate data sources. Evolved underwriters that can take advantage of emerging technologies (AI, machine learning, RPA etc) to leverage real-time data will become more valuable to their clients and companies.

It’s time to meet the new kid on the block. It is what Deloitte describes as the exponential underwriter: a multiskilled professional who will take the use of alternative data and advanced technology to a whole new level while enhancing their role and becoming more strategic.

So where does an exponential underwriter start?

Reinventing the role of underwriting to become insight-driven has never been more important, but where does a CUO start? A good first step is overcoming the nervousness that emerging technologies will replace the underwriter. While the underwriter of the future will look different to today, in commercial and specialty insurance there will always be a need for processing complex cases using deep professional judgment and gut instinct to make better risk decisions. The science will never replace the art.

Indeed, the game-changer is the combination of traditional skills with modern data-driven approaches. Openly embracing new technologies may well provide the answer to the challenge many face: how can they free up critical resource to focus on what they do best, assessing risk.

Opportunities abound to use data and technology solutions to automate and streamline the value chain. From intake to risk assessment, to pricing and binding there are many examples of how advanced technology can help an exponential underwriter:

  • robotic process automation that takes over mundane, repetitive tasks
  • artificial intelligence to rapidly and accurately extract data from submissions
  • machine learning for SOV and bordereaux to iteratively improve the model
  • deep learning that spots patterns in data that can assist with improving the rating
  • natural language processing that reads documents and contracts such as MRCs.
Becoming a technology trailblazer, and a data master

To be hyper-relevant in today’s market and grow in current and future markets, carriers must prioritise insight-driven underwriting. Those that take an enterprise underwriting approach and a strong technology strategy to constantly evolve data will be at the forefront. A modern CUO needs to be both a technology trailblazer, and a data master. Fortunately, they don’t need to do this alone.

Insurers no longer have to accept the current approach as inevitable or inflexible. Harnessing the power of modern technology, data and advanced analytics can help them regain control and underwrite smarter. They can be nimble, fast, future focused. They can be exponential underwriters.

Underwriters in the future can make informed decisions in minutes by leveraging gigabytes of data and complex models in the background – KPMG2


1 The future of insurance underwriting | Deloitte Insights

2 Enabling-the-future-of-underwriting | KPMG

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