“The essence of risk management lies in maximising the areas where we have some control over the outcome while minimising the areas where we have absolutely no control over the outcome.” – Peter L. Bernstein
With rising claims costs, customer dissatisfaction with increased premiums, and decimated global supply chains, risk management feels more important than ever before. Whether it’s through identifying, assessing, mitigating, transferring, or monitoring risk, insurers have many moving parts to ensure they remain profitable and can honour claims while avoiding excessive exposure to high-risk scenarios.
But as with everything in the world right now, customer demand and expectation are changing rapidly, with a move towards more proactive and personalised solutions increasingly higher among their priorities.
Adoption of the latest insurance technology almost certainly offers a viable solution for many of these challenges. For example, Avenga found that companies using AI for risk assessment report a 25% increase in the accuracy of their risk predictions and a 90% increase in the speed of the assessment process itself. Without wishing to sound hyperbolic, that is a huge difference-maker in allowing insurers to not only do more, faster, but more profitably as well.
Artificial Intelligence
Surprise, surprise. An insurance technology blog in 2024 that mentions AI. Sorry, I wouldn’t be doing my job if I didn’t at least start here. In fact, McKinsey believes AI could add up to £1.1 trillion in annual value for the global insurance industry. Whether it’s predictive analytics, automation of processes, or pattern recognition around claims, the message is clear: AI will allow us to dramatically improve both our operational efficiency and the accuracy of our decision-making.
I once suggested, to some eyebrow raises, that underwriters would be dead in the water within ten years as a result of the cumulative impact of big data coupled with AI. After all, this technology can process information around 100 times faster than the human brain. McKinsey goes one further and suggests that underwriting will cease to exist, at least as we know it, by as early as 2030. Research from Hyperexponential revealed that 69% of underwriters are concerned about being replaced by AI in the next five years. Instead, I’d prefer to think that the underwriter of the future will spend far less time on administration and far more on actual underwriting, with a process augmented by numerous predictive analytics tools designed to help them make decisions. At the very least, I’d expect every underwriter to have a digital twin that completes tasks for them at breakneck speeds.
Internet of Things (IoT)
‘The Internet of Things’ has never quite taken off as rapidly as the insurance industry might have liked. Adoption has been slow and has perhaps not been pushed as hard as it could have been by insurers already struggling to make sense of the vast amounts of data they receive. And that’s a shame because more real-time data from connected devices (telematics, smart homes, wearables) would certainly enable more proactive risk prevention and improve claims accuracy and loss reduction.
Telematics is a great example of something with disappointing adoption. Whilst about 33% of commercial fleets employ telematics, personal lines adoption accounts for a paltry 2–3% of the market, with the majority being young drivers desperately trying to get lower premiums.
Equally, when you consider that, according to GoCompare, 28% of all home claims are for escape of water, with insurers said to be paying out £1.8 million every day for escape of water damage, doesn’t it seem that smart leak detectors should be deployed in every single house?
Big Data and Advanced Analytics
The global big data analytics market in the insurance industry is projected to reach $3.6 billion by 2027, up from $1.8 billion in 2019, illustrating the growing reliance on data for risk assessment.
Given insurance is an industry literally built on actuarial science and the use of data points, the value of ‘more information’ cannot be overstated. Whether it’s the ability to undertake enhanced risk modelling with vast data sources accessed at unprecedented speed or creating personalised risk profiles for customers, the end result is clear—faster and more accurate decision-making for insurers.
Automation and Robotic Process Automation (RPA)
‘Swivel-chair RPA’ hasn’t quite proven the technological saviour that many heralded it as, but when we begin to incorporate AI into those processes for ‘intelligent process automation,’ things get far more interesting. With insurers heavily prioritising operational efficiency, the ability to streamline and automate vast amounts of admin becomes central to their success. Lower operational costs and the reduction of human error are one thing, but returning humans to high-value tasks is going to be paramount in meeting shifting customer needs and maintaining that personal service that so many still desire.
The Competitive Advantage for Insurers
The best way to remain profitable as an insurer is to stop the claims happening in the first place! We often look at the efficiency of handling claims, but there is no better way than…well…not having to handle them! Proactive risk management can dramatically reduce that, and the cumulative impact of the above insurance technology brings that very much to the fore.
At this point, insurers can begin to deliver value to customers beyond premiums, shifting from reactive to proactive risk management partners. In turn, that helps insurers to not only differentiate themselves on service but to begin to rebuild trust with wavering customer bases. We may even start to see an increase in customer loyalty from those who recognise their insurer going above and beyond the service provided by their peers.
The Customer Impact
This isn’t all just to the benefit of the insurers, though—customers also stand to gain greatly. Protection of their assets becomes a much more proactive process, with insurance technology helping to predict, communicate, and ultimately mitigate potential risks. Equally, hyper-personalisation ensures they are being offered the right policies and coverages for their very specific needs and circumstances, taking a wider view of the exposures they face.
They’ll also see much faster response times, the ability to self-service, and theoretical 24/7 access to advice and guidance. Underwriters and brokers will also become significantly more accessible to those who need their guidance when they need it.
The Future of Risk Management
We find ourselves on the cusp of a revolution, with insurance technology poised to redefine the very essence of risk management. By integrating advancements such as AI, IoT, big data analytics, and intelligent automation, insurers can transition from reactive responders to proactive partners, reshaping both operational models and customer relationships.
For insurers, adopting insurance technology isn’t just an opportunity—it’s a necessity. The ability to prevent claims, enhance operational efficiency, and provide personalised, proactive solutions offers a distinct competitive edge in an industry driven by trust, precision, and customer satisfaction. Faster and more accurate claims handling, coupled with reduced operational costs, means the shift from being a risk manager to a true risk mitigator is now a tangible reality.
Meanwhile, customers stand to gain immense value. From hyper-personalised policies to real-time risk mitigation tools, insurance technology empowers them to protect their assets proactively while enjoying faster, more accessible, and more comprehensive services. Insurers embracing this shift are not just future-proofing their businesses but also redefining customer expectations and possibilities within the insurance space.
Ultimately, the convergence of insurance technology and risk management will enable insurers and customers alike to navigate an increasingly unpredictable world with confidence and clarity. The tools are ready, the data is abundant, and the potential is enormous—the time to innovate is now.
