Often seen as an industry lambasted for a lack of change, the insurance sector has opened its eyes to a swathe of potential innovative technologies that could revolutionise the sector throughout 2024. At the height of this movement, the principle of automated underwriting emerged as the industry’s great fascination, with many touting it as a potential silver bullet.
Leveraging advanced technologies such as artificial intelligence, machine learning, and big data analytics, automated underwriting streamlines the traditionally cumbersome and manual process of risk assessment.
Proponents argue that this significant enhancement to an insurers day-to-day can have seriously positive knock-on effects, leading to cost savings for insurers, but also delivering a faster and more seamless experience for customers, potentially reshaping the competitive dynamics of the insurance industry.
As the landscape of risk changes for insurers due to the ever-evolving economic turbulence faced internationally, Wright admitted it was time for underwriters to begin transforming their methods.
Earnix‘s Director of Strategy, Aaron Wright commented, “Risk is evolving due to multiple factors including economic, catastrophic and climate events as well as technology (smart cars and home). Underwriters need to evolve the way they work to harness the increasingly sophisticated analytics that are available and avoid taking on higher risk due to lack of agility in underwriting and limited rule sophistication,” explained Wright.
“AI enables the ability to adjust to new patterns more rapidly than the traditional regression-based approach. This means using data and analytics to drive decision making, and existing technology and processes don’t support the innovation and sophistication needed to be successful. More data and analytical sophistication are needed to make smarter decisions with more complex underwriting needs.”
By achieving this, insurers would be able to enable their underwriters to focus on more challenging tasks, and therefore avoid wasting their time focusing on the tedious and mundane challenges.
Wright explained how Earnix’s own offering is a microcosm of this shift. “By automating the underwriting process, insurers can enhance efficiency, reduce costs, and improve customer experience. This allows underwriters to focus on more complex risks that require their expertise and experience. Earnix’s Underwrite-It platform, for instance, embodies this paradigm shift, combining advanced analytics with traditional underwriting methods to deliver robust risk assessment frameworks,” he said.
Inside the key benefits
The potency of automated underwriting is incredibly clear to see. By leveraging the capabilities of AI and machine learning to dramatically enhance the efficiency and accuracy of the application process.
This advanced technology utilises extensive datasets from various sources, enabling AI algorithms to detect hidden patterns and trends. This leads to a more detailed and precise understanding of risk profiles, which is crucial for insurers.
A prime example of this technology in action is Earnix’s Underwrite-It. This platform allows insurers to rapidly adjust to market changes and evolving risk environments.
By incorporating self-learning algorithms and simulation techniques, Underwrite-It enables insurers to make informed, real-time decisions. This adaptability not only enhances operational efficiency but also provides a significant competitive edge in the fast-paced insurance sector.
The benefits of automated underwriting extend beyond simply processing applications more quickly. This technology optimises the entire underwriting process from start to finish.
Wright explained the importance of this, remarking, “Being dynamic is important not just to exploit insights rapidly since time to value is important, but also to accelerate through the whole underwriting process end-to-end and operationalise it. It is important for underwriters to be able to close the loop so that they can look back and see if the book of business is performing as expected, identify any drift and course correct if required.
“By leveraging advanced analytics and algorithms, insurers can optimise risk evaluation, adapt to market fluctuations, and enhance their competitive edge.”
Buoyed by this thought-process, insurers are now all turning to automated underwriting to solve their issues. A recent survey and report by Novarica revealed that 85% of life insurers have adopted paperless underwriting processes. Additionally, 77% of these insurers utilise automated data requests from third-party databases to meet underwriting requirements, and 77% partially depend on automated underwriting for decision-making.
But there are other solutions that are proving to be popular in the industry.
The power of loss control
The integration of risk data is emerging as a secret weapon to enhance the performance of your underwriting team. One way this can be exploited is through the use of loss control, a risk management method aimed at decreasing the likelihood of losses occurring and minimising the impact of any that do happen.
Risk Control Tech‘s AVP of Sales, David Pittman, opened up on loss control’s newfound significance in the market, remarking, “We have seen a significant change over the last few years in how insurance organisations are leveraging loss control as a discipline. What was once just an inspection/survey function, is now becoming by far the most granular data source on a commercial carrier’s book of business.”
Most insurance carriers already have some form of loss control practice in place today, whether it’s a home insurer that has deployed sprinklers and smoke detectors in the house to reduce the risk of a house fire or a much more well-developed commercial system for industrial risk.
But this is really surface-level thinking. The potential for loss control is much higher when you consider the additional level of granularity of risk data that loss control teams can produce.
If leveraged effectively, this can enable your underwriting team to delve into the nature of the risk present in an insured’s operations and gain a more holistic understanding of what they’re covering.
By having access to detailed and specific risk data, underwriters can better assess the unique risks associated with each policyholder.
This comprehensive view allows them to make more informed decisions about coverage terms, premiums, and risk mitigation strategies. It also helps identify patterns and trends that might not be visible with broader data, leading to more accurate predictions of future risks and losses.
This deeper insight not only enhances the ability to protect the insurer’s financial stability but also enables the provision of more tailored and effective risk management advice to policyholders, improving overall safety and satisfaction.
Pittman explained, “We believe it is an intuitive next step to further enable disciplines within insurance that are already exist. Loss control is definitely at the forefront of that.”
Adding accuracy to underwriting
Insurance is an inherently analytical game, centred around numbers, and often viewed by wider eyes as rather clinical in practice. However, despite the clear focus on data and information, it is often leveraged ineffectively as the insurance sector fails to move with the rapid technological transformation that is impacting the wider financial space.
Your book of business, like anything, needs to be accurately measured if it is going to be bettered in terms of risk profile. As previously mentioned, many insurance companies already invest in loss control teams. So, by pushing on more, they could utilise improved tools to collect better use data and make their gains much more widespread. Therefore, enabling them to enrich other departments throughout their firm.
Risk prediction is another key area where insurers can target if they are going to add a greater sense of accuracy to their underwriting teams. Tactics like cross-referencing historical claims, and utilising past data can enable your team to select the risks they would want to cover in the future, as Risk Control Tech’s Pittman explains.
“Historically, loss control reports are long form documents that underwriters view at the time of renewal and then they get indexed away to never really be unearthed again. The delta between what is available in a renewal or application submission and what is available in a loss control report is not only significant, but it is actionable as well. It just follows that we want to make the data that matters front and centre for underwriting.”
The future
As insurers increasingly leverage AI-driven underwriting tools and data analytics, they can assess risks with unprecedented accuracy and speed, streamlining processes while reducing human error.
Automated underwriting not only improves operational efficiency but also enhances the customer experience by offering faster, more personalised policies. Moreover, with sophisticated loss control systems monitoring real-time data, insurers can proactively mitigate risks before they result in claims, potentially reducing costs for both insurers and policyholders.
This shift towards intelligent, predictive underwriting positions the insurance industry to deliver more resilient and adaptive solutions in a rapidly changing risk landscape.
Ultimately, leveraging both burgeoning technologies to produce a solution that is at the forefront of innovation is the way to lead the chasing pack in an industry now beginning to relish change.
