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Nov 2024

From barrier to benefit: Rethinking the future of underwriting

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Source: Asia Insurance Review | Oct 2024

Underwriting has been going through significant transformation over the last few years and continues to accelerate at an unprecedented pace. Traditionally seen as a barrier, there is now a growing opportunity to position underwriting as a strategic asset. To explore these changes and their implications, Pacific Life Re’s Mr Andrew Doran gives insights into the current state of underwriting and what to expect in future.
By Ahmad Zaki
 
 
Insurers have been talking about the use of data, AI and technology for a long time, yet it is only in recent years that there has been a significant acceleration in its material use within day-to-day underwriting.
 
“In my role with a view across many markets, I have witnessed firsthand the rapid evolution of the underwriting landscape,” said Pacific Life Re chief underwriting and claims officer Andrew Doran. “Following the introduction of underwriting automation well over a decade ago, which sparked a notable shift in underwriting practices, we have seen only a gradual evolution. Until recently.”
 
Today’s underwriting environment is marked by a growing shift towards digital solutions and AI integration, which contrasts sharply with the practices of the past.
 
Traditionally, underwriting involved a largely manual process. After completing an application form, a tree-based rules engine would process these answers to make an automated decision for around 50-80% of customers. For the remainder, underwriting evidence would be required, and a human underwriter would make the final decision.
 
“I would previously spend my time considering how we grind out 1-2% increases in automation, marginally increase non-medical limits, or tweak application questions based on anecdotal feedback or lower quality data analysis,” he said.
 
Today, modern data-driven underwriting is increasingly characterised by its reliance on digital tools, AI, and alternative data sources, driving a more dynamic and streamlined process. This shift results in faster and more accurate decisions, ultimately benefiting consumers.
 
“Judgement and expertise are important, but now, when I’m considering any changes in underwriting practice, my starting point is always ‘show me the data’, before working with clients to better understand the right changes that will have the biggest impact on the most meaningful measures of success.”
 
AI in underwriting
When it comes to the role of technology – especially AI – in underwriting, Mr Doran encounters two common questions:
  1. Can alternative technology and data sources be used to replace traditional underwriting approaches?
  2. Can (or will) AI or generative-AI replace underwriting?
“These are also questions I ask myself and my team regularly, and my perspective on this has evolved in the last few years. But the short answer continues to remain ‘yes, but…’,” he said. “While alternative data, technologies, and AI have the potential to enhance and further automate underwriting processes, and in some situations completely revolutionise the way underwriting is carried out, I continue to see human underwriters playing important roles in this future.”
 
However, in some situations, the concept of ’underwriting’ might not exist at all, as industries embrace the use of connected data to seamlessly assess new and existing customers frictionlessly. The industry is already seeing this to a limited extent today in many countries across Asia, with China, Korea, and India, leading the way on connected data and how this is used to assess underwriting risks.
 
Transforming the role of underwriters
Even with technological advancements, human underwriters will remain crucial for handling the most complex cases, providing their deep technical knowledge and insight that automation and AI cannot.
 
However, the future of underwriting will in many ways be shaped by changes in that workforce. With alternative data sources, machine learning, and AI technologies becoming more prevalent, underwriting roles will need to adapt.
 
“Underwriters of the future will need to be adept at interpreting complex data outputs and integrating them into the underwriting process and balancing technological advancements with human expertise. With the continued boom of InsurTech and HealthTech options, a particularly important skill will be in spotting the right opportunities to explore, and the right partners to connect with.
 
“Recent training sessions we have carried out are now more focused on developing these types of skills, and building confidence using data, to broaden underwriting skills, rather than deepen them technically / medically. This can be quite unsettling and frankly scary, but we’re in one of the most exciting times to be part of the underwriting and claims profession,” Mr Doran said.
 
“The things I envisioned, but thought impossible, many years ago are now happening, and this brings opportunities for us to not only understand underwriting risk better, but develop ourselves, expand the reach of insurance, and make underwriting the reason people chose to buy, rather than the barrier that many see us today.”
 
 
The future of underwriting
The future of underwriting is poised for radical evolution over the coming five to 10 years.
 
When it comes to augmentation of our current underwriting processes, there are three areas worth mentioning, according to Mr Doran:
  1. Data-driven predictive underwriting, where traditional and non-traditional data sources are inter-connected with underwriting to offer tailored experiences to accelerate the previously manual process and expand the reach of insurance. This may mean that for some customers the underwriting process might not feel like underwriting at all, whereby they are seamlessly offered insurance coverage without any ‘tangible’ underwriting friction.
  2. Augmented underwriting rules engines with machine learning models to improve existing automation rates beyond what is achievable with the current rule-based systems. I see a lot of focus in this area, with many organisations having reached the limit by which traditional means of increasing Straight Through Processing (STP) rates are effective, and therefore looking towards AI to supplement this goal without compromising their risk assessment.
  3. Technology integration which will increasingly supplement or replace traditional underwriting evidence requirements, such as video technology for medical exams, or facial scanning technology that continues to evolve. So far, this hasn’t quite taken off in the way that many expected it might, but it’s an area where we should continue to pay close attention.
At Pacific Life Re and UnderwriteMe is committed to investing heavily in this area and collaborating closely with partners to bring these advancements to fruition.
 
Caution ahead
The road ahead seems bright, but it is not without its dangers. Mr Doran pointed out three areas where caution is warranted:
“Regulatory clarity: 
AI regulation is still evolving, and ensuring explainability in AI-driven processes is crucial for justifying underwriting outcomes fairly. This is essential to ensuring we not only broaden the reach of insurance, but we do it fairly and transparently, without creating uninsured pockets by focusing only on the cleanest lives that are easiest to automate.
 
Risk management: 
As it becomes easier and cheaper for consumers to gain insight into their long-term health through innovative digital and medical technologies, this introduces risks of information imbalance and anti-selection. Robust monitoring processes are essential to manage these risks effectively.
 
Avoid overcomplication: 
I see this and have done this myself. Some of the opportunities that are becoming available to us are exciting and no doubt some will revolutionise insurance underwriting, but it’s important not to create solutions for problems that don’t exist. Focus on the key issues that need to be solved that add value for consumers and advisers. Think carefully about how you will measure success, and just because a technology solution can be implemented doesn’t mean it should be,” he said. A 
 
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