Market conditions created by the pandemic are compelling underwriters to price risk more accurately and provide quicker services
Advanced analytics is enabling underwriters to build bespoke solutions while artificial intelligence is driving greater personalization
Innovative business models and collaboration platforms are ensuring seamless management of customer lifecycles to drive enhanced experience
As the insurance sector continues to face major challenges to its business models, services and profitability brought about by the pandemic, the pressure is on underwriters to price risk more accurately and swiftly than ever.
This is especially true of those working in hard hit segments. According to Fitch Ratings, US insurers in the Property and Casualty (P&C) segment suffered losses to the tune of USD 6.8 Billion due to COVID-191. Underwriters are now adopting digital technologies to speed up processes, reduce errors, improve customer satisfaction and drive profitability. Here are four key trends in underwriting that are driving profitability, agility and competitive advantage.
The amount of data available to underwriters has exploded in recent years as a result of social media and digital in general. However, this vast amount of data can be overwhelming. Data analytics, data mining and predictive modeling help in analyzing large volumes of data to provide more accurate and timely insights into a customer’s risk profile. Increasingly, this will include data collected through wearables and telematics that are analyzed along with data collected via other sources such as customer history and social media feeds.
Underwriters are creating more bespoke solutions better suited to customers’ needs based on more accurate risk profiles. Data analytics and predictive modeling help monitor specific patterns and trends of customer behavior. The result is better underwriting decisions and more appropriate pricing and, in the long term, greater profitability. Low-risk profiles are handled with automated quote generation systems, leaving high-risk profiles to be processed by experienced underwriters, thereby improving speed and accuracy.
A growing number of underwriters are using Artificial Intelligence (AI) to improve their pricing. Policies can be priced, sold and bound in near real-time, speeding up workflows. Apart from increased personalization of customer service, AI can also help insurers offer suggestions to customers for reducing their annual premiums and addressing key problems. AI can provide real-time underwriting analysis, enabling insurers to offer quotes instantly to customers.
According to McKinsey2, AI could add up to USD 1.1 Trillion to insurance values. Advanced AI can deliver even greater personalization with more accurate product recommendations through deep learning neural networks. To exploit the full potential of AI, underwriters should share their data across the organization rather than have a siloed approach. This will ensure a more unified view of customers and enable companies to pitch relevant solutions across functions such as sales, marketing and customer service.
A slew of innovative business models and processes that challenge traditional working practices are being adopted by underwriters. This includes fluid-less underwriting. Digital technologies such as Machine Learning (ML) are replacing ‘age and amount’ charts and obviating the need for fluid samples — a process that can be time-consuming and uncomfortable for customers.
Similarly, rather than attending a site or property, underwriters are using video or aerial images allied to image analytics.3 Drone imagery analytical solutions based on AI and ML deliver 95 percent accuracy in damage prediction, eliminate manual efforts and significantly reduce the time spent segregating images. This expedites claims validation and automates claims estimation reporting.
Wearable technology combined with the Internet of Things (IoT) and big data are also making risk profiling faster and more accurate. One study4 found that nearly 70 percent of its survey respondents were willing to adopt health insurance use cases based on wearable devices.
Collaboration tools and platforms are enabling greater coordination among different functions to drive effective and seamless management of a customer’s lifecycle. As a result, underwriters are taking less time to provide quotes, thereby increasing opportunities for new business.
Underwriting teams should adopt a more overarching and structured approach to assessing risks. This should bring together analyses of explicit and implicit exposures as well as real-time data, connected ecosystems, cognitive automation and other digital collaboration tools. Insurers should also look for external digital collaboration partners. Some companies are collaborating with InsurTechs5 to improve their ability to meet the risk management needs of commercial clients.
In addition, cloud-based insurance solutions can foster a culture of collaboration and facilitate re-balancing of portfolios as risks evolve to drive effective portfolio management strategy. This leads to a solid foundation for effective and efficient underwriting that meets the need of consumers and drives profitability.
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16 November 2022
03 December 2021
02 November 2022