Until recently, the insurance space has not been at the forefront of digital transformation.
The very nature of the industry requires a cautious approach, bound by strict regulatory constraints and rigid data privacy that limits spurious infrastructure investment and aims to protect profitability through proven, established ways of working.
Yet almost overnight, the world has changed. First the pandemic, and now the ongoing conflict in Ukraine have contributed to global uncertainty and upheaval. Many countries are staring into the abyss of recession, with interest rates and the cost of living rapidly increasing. While high interest rates present opportunities for insurers to maximize returns and maintain shareholder value, new market entrants, committed to finding innovative ways to deliver customer-friendly insurance policies, are forcing a reappraisal of the industry.
The choice to revolutionize how an insurance company makes its decisions may feel like an expensive, resource-intensive minefield. Yet the transformative nature of using tools such as transparent AI and machine learning can empower actuaries and insurance organizations to deliver dynamic, competitive services and pricing, and maximize the power of leveraged data to make better business decisions and offer fairer, more varied and competitive services to their customers. Sophisticated pricing teams will empower insurers to quickly react and adapt to changes and make the most of them.
Early adopters of AI and big data technologies have already had a significant impact on the insurance industry. Big Tech (think Google, Facebook, Apple and Amazon) have been making data-led decisions for many years, and have turned their focus to the insurance space, with a ready-made, global customer base and a wealth of user data to inform their decision making.
In a study published in CapGemini’s World Insurance Report, 36% of customers say that they are willing to purchase insurance from Big Tech firms, vs. just 16% in 2016. This is putting tremendous pressure on historical insurance carriers. Meanwhile, insurtechs are creating entirely new ways of interacting with customers, raising policy holders’ standards and expectations.
According to Dan Schreiber, CEO of Lemonade, (a company which describes itself not only as an insurer, but as a next-generation AI company), his company collects around 100 times more data than a traditional insurer. This data is used to better target and serve customers, upending historical industry standards to deliver fast, seamless and personalized insurance products and services.
It feels like stating the obvious, but more data = better decisions.
While the whole world seemingly embraces data as a tool to transform how we do business, the reality is that unless that data is used correctly, it remains either worthless, or missing its full potential. Incumbent carriers need to accelerate deploying AI and machine learning to stay in the game. The insurance industry has been somewhat slow in unlocking the ways in which data can transform how business is done, and has lagged behind others when adopting AI at scale.
Yet, regardless of these challenges, leveraging AI and data is a land of opportunity for the insurance industry. In fact, 87% of insurance carriers are investing more than $5m in AI-related technologies per year, illustrating their willingness to accelerate this adoption. AI gives insurers the ability to make faster, more accurate decision making based on current situations, but to do this, the skills and knowledge of the actuary are fundamental to ensuring the right data points are used to make the right decisions. AI learns from its inputs, so building models that operate both fairly and transparently is crucial.
Analysis shows that AI leaders generate five times the amount of ROI than firms that are further behind on their AI journey, and 22 percent of firms state that at least five percent of their earnings in 2019 were attributable to AI. Organizations that adopt AI now will survive and thrive, while those that lag will fall behind.
This is where expert, best-in-class B2B SaaS providers come into play: they provide incumbents with cutting-edge technologies that can be used in production at the core of their processes. The speed of AI and new ways of processing data can also accelerate the way that data is managed and automate processes in line with regulatory restrictions, to rapidly keep pace with legislation.
In its first global pricing report; Akur8 Global Pricing Survey: Convergence between Actuarial and Data Science is coming,’ Akur8 noted from its findings: “For major insurance players, pricing is the most important competitive differentiator in the marketplace, with 81% of respondents ranking it as a very important criteria.” Yet the report also notes: “Established pricing processes and tools, though robust, continue to make use of legacy pricing approaches, having not yet activated the potential of pricing as a business lever.”
Pricing analytics has been one of the last bastions of powerful data use in the insurance industry. The early groundwork has taken place and we now have a world where transparent AI can ensure clear, fair and ethical decision making, which empowers insurers to make faster, smarter decisions and gives them the flexibility to ride the waves of a changing economic climate with ease.
Ultimately, no insurer would dispute the core importance of pricing within their strategy. Yet how pricing is determined and used is in a state of change and transformation, thanks to tools like machine learning and AI. This change is parallel to the slow nature of change with actuaries, whose precision and modeling remain of fundamental importance, but whose existing roles will evolve from manual rate plan building into validating, checking, confirming, and approving automated machine learning outputs.
In the current economic climate, insurers choosing to stick with what they know will find themselves at competitive risk, as other players who understand how to leverage data, will bring new and innovative offerings to the market.
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