Risk management capabilities behind the curve

Despite their efforts, insurers are not properly prepared to address this situation for multiple reasons. First, they lack the consolidated data to be able to evaluate the risks. 72% of our insurance respondents say their risk management capabilities and processes have not kept pace with the rapidly changing landscape. At 30%, the use of cloud to derive value from data is low but this is likely due to the fact that insurers don’t have enough risk data in the cloud. The core data is not captured with risk characteristics locked away in PDFs and manuscript endorsements not readily accessible. 22% cite data quality as the top challenge they face when it comes to generating insights from data. 18% cite even more fundamental data availability.

Second, even when they have the data, they don’t have the right access or tools to assess it. 17% of the executives say they still do not get satisfactory results in eliminating data silos. Therefore despite the data existing, it is still not readily available for practical use, not to mind interpreting and gaining insights from it.

And third, they lack the skills and technology to make use of it. 22% cite lack of relevant skillsets as the top challenge while 17% cite legacy technology as the biggest hindrance.

Risk management leaders are emerging

There is hope for better risk management in the future to meet these needs. 28% of insurers are already starting to use generative AI to process and derive value from data which at this early stage is promising. Plus our study did identify a group of risk leaders (14.5%) across our global respondent base with advanced risk capabilities. The difference between leaders and laggards when it comes to risk comes down to both the speed of identification and more importantly, the speed to action. These risk leaders are better at detecting and mitigating threats than peers with less mature capabilities. They are also more likely to take actions that strengthen their risk capabilities and are far more satisfied with those actions.

In support of those leaders, our Fuel the future of insurance through technology report cites technology and platform modernization and predictive analytics as the main drivers to deliver profitable growth for insurers. The eradication of tech debt could yet be the defining KPI of generative AI.

Connect the dots to empower the business

How far does risk management percolate through the entire insurance company? How well do you know what the exposures are? And once detected, what is the speed of response?

This is dependent on integration of risk processes, resources and capabilities. To give just one example, ensuring guidelines and renewal profiles are updated appropriately. Although 75% of the study’s insurance participants say the business outside the risk function is becoming more aware of the impact of new and interconnected risks, much more needs to be done to create an organizational risk culture and mindset. The same percentage (75%) say the risk function is struggling to support the wider business in developing a risk mindset and just 36% are very satisfied with the wider business strengthening its risk capabilities to improve business resilience.

Spinning risk into opportunity

In response to a demanding risk environment, insurance risk functions are prioritizing multiple initiatives. Top among these are implementing technologies to improve decision making (36%), bringing new skills into the risk function (36%) and keeping the board and C-suite informed on emerging risks (36%). While this is all good, superior risk management activities need to focus on bringing the identification and response to risk issues to the frontline underwriting and claims processes to have the most impact in order to have the risk function better contribute to business success.

However, insurance risk functions may be juggling too many priorities. Further symptomatic of this is that the majority (78%) of insurance respondents want their teams to devote more time to value creation and innovation, which would be the next frontier, but there are roadblocks. Over seven in ten (73%) say risk professionals are not sufficiently connected with the business to do so and 80% say balancing existing duties with value-adding activities is a major challenge.

A ‘Back to the future’ model is no longer fit for purpose

We can no longer let the past predict the future. Traditionally, insurers have set their rates based on past prediction models. This alone is no longer viable.

The importance of data cannot be over-emphasized – both in the detection and mitigation of risk and to inform decision-making when it comes to an action plan both at the enterprise and the individual transaction level. According to our Transforming Claims and Underwriting with AI report, insurers have access to an underutilized asset in the massive volumes of structured and unstructured data they collect from items such as vehicle telematics devices, Internet of Things devices, interactions with customers, third party databases and more. ​

Having the right data lake architecture in place can allow for elimination of silos, faster data ingestion and cross-pollination of data across departments required to fuel predictive analytics. The ideal state is to be able to provide the front line underwriters, claims analysts, and decision makers with the risk-aligned insights to make more informed decisions. In this way, we can equip the company to truly manage these interconnected risks. Without it, the web of interconnected exposure is only going to grow and we will be blinded by the true exposures we are assuming. This isn’t a risk that can be easily avoided or transferred. It only can get better with action.

Our Accenture Risk survey 2024 finds that risk is everywhere and individual risks are now impacting each other, creating a web of threats.