Enabling profitable insurance growth with AI

From the Internet of Things to blockchain to digitalized pricing and customer service, insurance carriers are often overwhelmed with trying to stay current, let alone trying to be forward-thinking. Against this backdrop, how can insurers maintain relevance in today’s evolving technology landscape?

Companies that embrace new technologies across the entire value chain – rethinking everything from operations, underwriting, customer service, to claim management – will benefit the most. These adopters recognize new technologies will transform the property and casualty industry, with the potential to increase growth and profitability and reduce costs while elevating the customer experience.

Managing tension
There’s inherent tension between growth and profitability. It’s easy to gain market share quickly if insurers are willing to lose money. It’s also easy to set well-defined parameters around the bottom line, but it may be difficult to grow under those circumstances.

Technology can help insurers balance those competing priorities and explore options to find the right place on the risk/reward curve. In addition, technology can help carriers expand their range of products and deliver them to customers quickly, whether through apps on a mobile device or via an online portal. Both can help carriers grow and access customers more efficiently and cost effectively.

Insurers are using predictive models and other types of artificial intelligence (AI) to pull even greater insights from the data they already have within their own operations to drive the right product terms and conditions for the right customer. Predictive and prescriptive analytics are no longer just about pricing, but also being deployed in underwriting, claims, sales and operations to drive a customized service experience to the end consumer.

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Computer components used in the mining of crypto currency sit on a shelf in a mining farm in Japan. Photographer: Tomohiro Ohsumi/Bloomberg
Bloomberg Creative Photos/Bloomberg

We’re also seeing the emergence of electronic trading hubs and personalized aggregators that allow customers to compare policies and rates, a trend that will continue to expand into less complex commercial risks. Soon, we expect commercialized trading hubs with intelligent automation driving sophisticated pricing into the hub from the insurer’s side – and automated decision rules about what to present to the insured from the broker’s side. Insurers that connect to these hubs, and continue to successfully manage distribution relationships, will see growth because it will allow them to quote for almost zero marginal cost, while mitigating the risk of being commoditized by aggregators.

Regulatory compliance and financial reporting obligations have increased significantly in many countries, thus legacy systems that require significant manual intervention may struggle. Finance and process transformation, aided by making wider use of technology and automation, such as robotic process automation (RPA), can address these challenges while also delivering better governance and richer management information. Given the range of regulatory frameworks, there are several different strategies insurers can implement. Where the rate environment is flexible, insurers can focus technological development around pricing, whereas those in regulatory environments where pricing is relatively constrained, may want to focus on underwriting or claims optimization strategies.

More changes on the way
In the years to come, we will likely see increased connectivity in the insurance market. Companies will form alliances and partnerships with those previously regarded as competitors, and with players they just previously hadn’t considered. It’s no longer about vertical integration. It’s more about being able to connect to different providers of information and technology and integrating this technology with legacy systems.

Automated pricing and underwriting, underpinned by analytics, is already well advanced in personal lines and beginning to gain traction in the commercial segment. Moreover, appropriate use of external big data and analytics can enable insurers to provide products and prices that are better tailored to the individual customer.

In claims processing, AI applications are already being used to identify potential fraud. “Smart automation” in the claims process can extend this function to navigate claims needing attention to the right handler and process ones that don’t in a no-touch way.

Data analytics and AI will continue to be key components in underwriting, pricing, modeling, product development and marketing, but accessing data is only as good as the technology that supports it. Some carriers are more collectors than users, sitting on data gold mines, but unable to access it. Or worse, they can access it, but don’t know how to effectively use it. Data is worthless if the insights buried within its hidden patterns are not extracted, and the insights are useless if not deployed across the value chain to drive efficiencies and a differentiated customer experience.

Despite its central role, technology alone is not the answer, but human resources are limited and expensive. Insurers must quickly consider strengthening their efforts by focusing on people – by directing those resources to the points in the value chain where they drive the most benefit. A key question for insurers will be: which parts of which tasks currently done by employees can be handled more efficiently by a machine – saving cost and potentially freeing up people to focus their energy on more important and high value tasks? Which things – due to the required creativity, judgment or emotional sensitivity – are better handled by people? Distribution relationship managements and experienced based complex subjective decision making will always be a key component of managing an insurance portfolio. While knowing technology disruption will continue to upend the traditional insurance market, it’s all a matter of finding the right balance between human intelligence and artificial intelligence, working together to drive meaningful change.

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