With the abundance of data available to today’s underwriters, it would be easy to assume that decisions are made swiftly and based on comprehensive information, allowing Chief Underwriting Officers (CUOs) to easily assess the impact of each transaction on their overall portfolio. Ideally, this data would enable the industry to manage and grow portfolios sustainably and profitably.
This overarching view of insurance portfolio performance would continuously inform underwriters’ strategies, creating a seamless feedback loop—surely an underwriters’ nirvana?
However, this ‘nirvana’ state remains out of reach for most insurers. We have the data, it’s out there. Insurers are getting better at harnessing and assessing it using ever more innovative tools and technologies, but still, there is a disconnect. CUOs and actuaries only see very high-level data, for example, broad geographies or industry types, rather than the rich detail that makes up the fabric of their portfolio. They’re also getting this information on a delay, it can be months before CUOs see claims data for their portfolio, or can identify trends in transactions that might necessitate changes in their strategy.
What happens when good data happens to bad structures?
There is a significant disconnect between transactional and portfolio-level underwriting. We know many underwriters are getting this rich, risk-level data at submission. They’re getting granular trade, building, credit data, and more thanks to a sophisticated ecosystem of APIs that enrich submission data when it arrives. These underwriters make smart decisions based on this, binding what they believe to be the best risks. But that level of insight is getting lost somewhere between the transactional line underwriter, the senior underwriting managers, and the C-suite.
As an industry, I think we’re getting a lot better at capturing the right data, but it often sits in Excel spreadsheets, emails, or underwriters’ brains, it’s used artfully in the quote process, but then not captured in any structured way to be used at a portfolio level. Another hurdle is the traditional PAS systems used by many insurers. They weren’t developed to handle that level of data, and many embedded systems can’t evolve quickly enough to respond to the increasingly sophisticated data needs of their users.
The disconnect hampers underwriting effectiveness and business performance. Portfolio optimisation provides underwriters with a comprehensive view, allowing for swift adjustments in strategy and risk tolerance. Without this information, underwriters may either assume excessive risk or miss valuable opportunities due to insufficient insights.
Will we achieve nirvana?
Advances in underwriting technology, particularly at the pre-bind stage, have the potential to build a strong bridge between transactional and portfolio-level underwriting. Today’s underwriting workbenches can provide a home for all the rich data underwriters need, bringing it out of silos and into one place. The processes and swift transfer of information offered by these platforms can support that underwriting feedback loop and ensure CUOs and actuarial teams can see, in real-time, how portfolios are performing, and the granular data that will help them to strategise.
Beyond the technology, the industry needs to work on joining together all the relevant parties. The underwriters, data scientists, actuaries, CUOs, and operational leads all need to be working towards the same goal. They need to have an aligned view of strategy and be able to seamlessly communicate this between them.
Nirvana is within our grasp. The industry is reaching a point where the tools and talent for true portfolio optimisation are ready, but we need to find the right ways to stitch them together.
Find out more about Send’s Underwriting Workbench and its capabilities here.
Written by William Harnett, Head of Business Strategy & Customer Success. Get in touch with William on LinkedIn.