How insurers can leverage AI to drive value in the cloud
You’ve probably heard by now: AI and cloud-based technologies are the future of insurance. Customers want to be protected by their insurance and they want interactions with their insurance provider to be as seamless as possible. With cloud-integrated products and customer data collection supported by AI, insurers are poised to get ahead.
The cloud empowers insurers to capture customer data for a holistic view of behavior, preferences, and risk level. AI transforms that data into actionable insights that everyone from agents to executives can use to make decisions. Insurers can deliver more personalized customer experiences while making the most profitable choices throughout the value chain, from underwriting to new product development.
As Accenture CEO Julie Sweet has said, “Cloud is the enabler; data is the driver, and AI is the differentiator.” AI empowers insurance companies to derive increased business value from their cloud-based operations and their growing volume of data.
Leveraging AI to drive value
In our 2019 Cloud Readiness Survey in Insurance, most insurers listed cost savings as a primary benefit of moving to the cloud. At that time, 90 percent of insurers said they had a long-term plan for cross-company technology innovation. The COVID-19 pandemic pushed those plans into overdrive. Cloud-based technology has enabled insurers to better meet customer demands for digital-first experiences and optimize the process of collecting customer data to be leveraged for greater personalization.
AI adds another dimension of value to the cloud, introducing automation and, maybe, more importantly, unlocking the power of data. With AI-backed data pipelines, insurers have also been able to optimize risk assessment and claims processing. The applications for AI in insurance are still expanding, but here are two key areas where AI can support cost reduction and growth:
Improve customer experience with optimized offerings
My colleague Kenneth Saldanha has noted that “real-time, personalized recommendations in digital services have become ubiquitous… Insurance customers now expect that level of personalization to help them achieve better health and overall well-being—especially Millennial and younger consumers.” AI facilitates those experiences by using data to inform personalization at every customer touchpoint. Even with an elevated reliance on technology, customers still want human interaction. AI can support better customer experience by serving up the information and insights insurers need to recommend the right insurance products at the right time.
Insights into customer behavior can help insurers make better decisions about product development and pricing. With a continuous customer feedback loop, insurers can improve their current products and launch new offerings with a clearer picture of customer demand and usage. It can also help insurers optimize pricing structures based on customer behavior data. This saves time and money through the stages of product development and raises the likelihood that new products will be successful.
Insurers that offer personalized experiences and products that are tailor-made for their customers see an 81 percent increase in customer retention and an 89 percent increase in customer engagement.
Enhance the insurance value chain
AI has important implications for underwriting, policy administration and claims. With cloud-based data collection and AI-assisted analysis, underwriters have access to a larger volume of high-quality information that helps them better assess risk and meet customer needs. AI is already reshaping underwriting and, in some cases, fully automating it.
Humans and machines can work together to reduce bias and determine the most profitable underwriting decisions. Humans bring intuition and previous experience to their risk assessments. AI can surface deeper insights across the policyholder’s peer group and their personal history. Additionally, AI can assess large datasets that extend into all areas of policyholder behavior and asset management. For example, AI allows underwriters to process a high volume of assets like vehicles and property or, in the case of employee benefits, schedules and classes of benefits.
When it comes to policy administration, AI can add value to the customer while helping insurers collect better data to optimize policy offerings. Life insurers have already begun leveraging IoT and wearables to offer pay-as-you-live policies. AI can boost the profitability of these products by bringing data together across platforms, better informing the customer experience and streamlining policy administration. In the telematics arena, usage-based insurance allows insurers to reward trucking and commercial freight companies for safe driving.
A similar business model is also cropping up in car insurance to expedite the claims process. Sompo Japan Nipponkoa Insurance leverages AI to gather data from dash cams to assess damage and fault in collisions. The technology has enabled them to process claims in just one to two weeks. North American insurers like Geico and Allstate are rolling out similar features that encourage safe driving for their auto insurance customers, leveraging smartphones as electronic logging devices.
Pushing your AI initiatives forward
Cloud adoption has been slow in the insurance industry, and so has AI adoption. Ninety-four percent of insurance executives acknowledge they know how to pilot but struggle to scale AI across the business. Through our research, we’ve found several commonalities between companies that are able to scale AI and begin to see business results from their investment. Insurance leaders can use these insights to strengthen their AI initiatives.
Use the cloud to improve your data strategy
To return to Julie’s insight, a key benefit of the cloud is that it enables data capture across channels. From employee performance to customer behavior, there’s no shortage of data to help inform business decisions and customer interactions. AI can’t operate with the wrong information or information that’s poorly organized. Data, as the driver, underpins the success of your AI initiatives. Data quality assurance, management and governance across the cloud platforms you choose is critical for the successful implementation of AI to support your business objectives.
Many companies start off with one cloud provider, but as they grow, they realize they need to take advantage of different capabilities offered by other providers. Your cloud management strategy must allow you to access and assess ever-changing sources of data for maximum visibility, including third-party data for a 360-degree view of the customer. It’s important to develop a multi-cloud approach from the outset to ensure that your data strategy remains scalable.
Align AI initiatives with business priorities
As with most technology transformations, undertaking an AI initiative should be an iterative process. Accenture research found that 70 percent of companies that (continuously) successfully scale AI projects link their AI goals to their business strategy. These companies pick a focus and stick to it. AI can solve many problems and deliver value in almost every area of the business. Avoiding scope creep and making sure that you have the right expertise to get the job done is imperative to see results from AI.
Focus on adoption and upskilling
Once you’ve clearly established a connection between how AI will help the business achieve core goals, it’s important to evangelize the benefits of AI across the organization. In Accenture’s own cloud adoption journey, we found that focusing on technical education and upskilling allowed us to achieve our goals. We’ve also found that insurers that identify as low-adopters when it comes to cloud technology cite a lack of skills as the main barrier to success. Mid- and high-adopters also cite misalignment between IT and the business as the third-most pressing struggle in their AI initiatives. Ensuring that you have buy-in and understanding across the organization helps you stay agile and pull in the same direction towards those business objectives.
Develop a cloud-native culture and democratize AI across the workforce
To underscore the point above, Accenture has also found that enterprise-wide alignment is the keystone of AI implementations that drive business outcomes. We’ve found that 92 percent of companies that have scaled and reached repeatable success leveraged cross-platform, multi-disciplinary teams. AI isn’t a novelty; it’s the way business will be done. Making the benefits of AI and cloud capabilities accessible to every team member allows you to take full advantage of the data and insights these technologies unlock.
If you’re looking for more information on how to migrate to the cloud and drive value with cloud-based technology, read Reimagining insurance: The new cloud imperative, a report I recently co-authored that focuses on guiding insurers’ cloud strategy. We’ve also developed an AI readiness quiz for insurance to help you get an idea of your business’s current state so you can take the next steps on your AI enablement journey.
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