From legacy to leading edge: How insurtech is redefining insurance

By Alastair Gill – Principal Data Scientist , GFT

 

The COVID-19 pandemic left multiple macroeconomic hurdles in its wake, not least for the insurance industry. The global event forced the industry to embrace a remote workforce and virtual customer and distributor engagement to meet evolving expectations for customised products, channels and services.

This shift enabled the insurance industry to adopt new technologies and innovations such as artificial intelligence (AI) and machine learning (ML). With the emergence and adoption of insurtech, a fresh wave of disruption has been brought about that promises increased efficiency, reduced costs and risk, and enhanced customer experiences in the insurance industry.

The rise of insurtech

Insurtech broadly refers to the use of technological innovations designed to enhance and optimise savings and efficiency within the current insurance model. From AI-powered chatbots streamlining customer service to the use of machine learning to increase efficiency in processing claims, insurtech is transforming how insurance companies operate and serve policyholders.

The global insurtech market size was valued at $5.45 billion in 2022 and is projected to grow exponentially to reach $152.43 billion by 2030. As insurers confront an uncertain market, the need to deliver greater value to stakeholders and boost operational efficiency has become a top priority. Streamlining processes by integrating innovative technologies has been critical to driving this enhanced efficiency across insurance operations.

Alastair Gill

AI and machine learning

Artificial intelligence’s powerful data processing and pattern recognition capabilities are unlocking practical use cases for insurance companies. Insurers are leveraging AI to more accurately evaluate claims risk, optimise pricing strategies and provide personalised coverage options to customers. AI can analyse a multitude of factors that influence insurance risks and outcomes. This includes everything from a customer’s personal details and history to wider environmental factors. By processing this data, AI can provide insurers with detailed risk assessments, helping them make more informed decisions.

Underwriting and claims processing are two key functions in the insurance industry. Underwriting involves assessing risk and determining the premium that should be charged, whilst claims processing involves verifying and paying out claims. These processes have traditionally been manual and time-consuming. However, with the advent of AI, these processes are being automated. AI algorithms can analyse large volumes of data, including customer profiles, claims history and market trends, to provide insights and predictions. This enables underwriters to make faster, more accurate decisions when evaluating risks, determining policy terms and setting premiums.

Similarly, from the moment a customer opens an insurance claim, AI technology can streamline the administrative process through process automation. For example, AI can assess the damage sustained by a vehicle and the cost of repairing it. This means that as soon as a customer opens a claim, they can receive immediate assistance and guidance, making the process smoother and more efficient.

The results for automating such tasks have proven to reduce the risk of human error whilst increasing the speed of decision making. Ultimately, insurers stand to save more on operational costs by automating routine manual tasks, as well as on costs associated with errors or delays, whilst better servicing customers and increasing response times.

The road ahead

Like any major change, insurtech will not become commonplace without overcoming some challenges. Cybersecurity and data privacy concerns may arise with the increased use of AI, machine learning and cloud computing, so enhanced cybersecurity strategies will be required as tech adoption advances. Consumer wariness of digital-first insurance companies could hinder adoption too, and insurtech innovations could face internal resistance from firms accustomed to legacy processes.

Meanwhile, operationally, there is no doubt that the workforce will need to adapt and develop new competencies to thrive in the age of insurtech, as the nuances of the insurance sector mean there will always be a need for human decision making. Increased productivity and automation will transform how insurance staff operate, shifting focus to higher-value tasks and responsibilities.

Finally, for consumers, insurtech promises insurance that is more personalised, transparent and convenient through digital experiences. Much of the legwork of seeking coverage could be reduced through AI-guided self-service, and some types of claims processing and payouts could become near-instantaneous thanks to automation.

Insurtech appears to have the potential to bring about changes in an industry that has been relatively unchanged for some time. Companies that strategically embed these emerging technologies will separate them from the competition on the road ahead. By leveraging insurtech’s potential, insurers can build a future that is more profitable, more transparent and more customer-centric overall.

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