By Amrit Santhirasenan, CEO and co-founder of hyperexponential (hx)
Risk is everywhere in today’s world and is only set to increase. 2023 will be a year in which insurance companies will have to navigate turbulence and a precarious macroeconomic climate, while also trying to digitally transform. One area that much of the industry has turned its attention to is pricing. For example, a recent report shows that 68% of actuaries surveyed at leading actuarial conference GIRO 2022 cited pricing as a key priority for their digital transformation agenda.
With many insurers still trying to price 21st century risk with 20th century tools, the time to invest in new pricing models has arrived. However, this is easier said than done in an ever-changing market. Before insurers rush into overhauling their entire tech stack, it’s important to consider some of the potential scenarios that could play out in the market in 2023.
While businesses with the best pricing infrastructure and future-proofed technology are likely to succeed, first, they must meet the current hard market demands, secure tech platforms that drive insurance data and recycle legacy tech.
Insurers rush to meet ‘hard market’ demand
The insurance industry is experiencing high demand due to increasing interest rates, supply chain issues, geopolitical conflicts, Covid-19 consequences and natural catastrophes. Insurers and underwriters know that increasing risk has severe implications on global society, but the same risk also drives opportunities for their industry.
The current ‘hard market’, which is so favourable to insurers, will eventually reach a tipping point as supply meets demand, which technology could facilitate in many ways. Premium growth is indeed expected to remain elevated, even for the 2023-2024 period, but the uncertain future demands that the insurance sector maximises its data advantage now, not tomorrow.
Data-driven solutions & AI
The insurance sector is fundamental to how the commercial world deals with risk. Risk and opportunity go hand in hand, and data-driven insurers are best placed to make the most of those opportunities.
The sector has historically been slow to adopt new technology, but the rate of adoption is increasing. Take AI, for instance, which is finally being deployed to help insurers with tasks from claims classification to data ingestion. As AI’s notoriety grows with high-profile developments like ChatGPT, it will be embraced for a huge number of business use cases. The wider business world is already leveraging AI for tasks from image generation to marketing copy. In insurance, there is huge potential for AI to help insurers make better pricing decisions.
In the modern era, insurers can’t grow if they can’t react quickly. The amount of risk is constantly increasing with new assets such as cyber security and liabilities like global warming. At such a time, insurers must be able to respond to new and emerging risks and deliver fair prices to customers without leaving themselves overexposed.
Without the right technology to ingest and analyse big data at speed, and tools to price previously unseen risks, firms will leave themselves at risk of losing out to more agile competitors or widening loss ratios due to inaccurate pricing. Therefore, businesses that become data-driven sooner rather than later will have a significant advantage when the market turns.
Legacy tech recycled, not rejected
The conversation about AI and data-driven transformations is definitely an important one, but pricing for the future does not mean forgetting the past. While there is a huge amount of ambition brewing across the whole sector to address digital transformation, this is often understood as ‘moving away from legacy tech’.
There is often a preconception that legacy is unequivocally bad, but this isn’t always the case. Insurers should avoid the mindset that they must rip everything out and start again. Modern technology solutions should be able to integrate with and work alongside established datasets and technology platforms where it makes commercial sense.
The resulting combination can be more than the sum of its parts. And, although newer entrants without any legacy tech may be able to move faster, larger traditional insurers making their legacy technology useful could deliver a huge competitive advantage when the hard market changes.
Ultimately, failing to capitalise on the data in existing systems may be a big mistake, especially for larger institutions with huge amounts of historical data. To bring new life to decades-old data, firms must analyse it forensically with modern techniques – not rip and replace, but incorporate the old with the new.
