The perfect storm of challenges facing insurers is well-known to anyone working in the industry today. Some have been bubbling away for years – such as the competition from insurtech companies and non-insurance firms like manufacturers, the rising cost of claims, and internal inefficiencies. As the tough economic climate continues to hit household budgets, many insurers are bracing themselves for the increased risk of claims inflation and fraud.

Yet the digitisation that’s swept the insurance sector over the past decade has unlocked new capabilities for companies to address these challenges and innovate. Analytics, automation and cloud computing are already changing new working practices – but AI-enabled technologies look set to transform purchasing, underwriting, claims and more.

Among them is hyperautomation – which we’ve discussed in previous blogs.

Simple linear automation has helped insurers reduce the number of high-volume labour-intensive tasks over the years. Still, as data volume and variety increase and processes become more complex, hyperautomation goes further. This orchestration of digital operating systems, workflows, RPA (robotic process automation), and AI support smarter decisions, at scale, via high-value autonomous processes.

Three ways hyperautomation could help you drive improvements across your insurance business:

1. Emphasise the customer experience (CX)

SAS research shows that 75% of consumers would consider switching to a provider that offered faster customer service.

Since many people only speak to their insurer when making a claim, which is often distressing, these interactions are critical. They also want to be able to carry out simple tasks, like updating their policy, without sitting in a queue.

Self-service portals and chatbots are already making it easier for customers to manage their claims and personal details, freeing advisors to handle more complex cases. Automating customer service and claims handling allow insurers to speed up resolution while increasing the consistency and cost of claims decisioning.

Currently, 40% of people prefer using an automated tool over a human if it means the service is faster and more efficient. It’s a significant proportion and is expected to increase as text analytics can better determine the customer’s intent and needs. When combined, in real-time, with information already known about the customer, triaging becomes quicker, better informed, uses internal resources more effectively and improves the customer experience.

This is because hyperautomation can handle enquiries more intelligently. It reduces friction and guides self-serve customers and claims handlers through data collection and fact-finding processes, using AI-powered risk and fraud models to optimise decisions. Straightforward cases are settled within minutes, while advisors are given all the relevant information and guidance to resolve complex issues promptly and fairly.

Using hyper automation to make sense of customer data rapidly allows insurers to personalise experiences beyond claims. Pre-empting what they want and need, based on behaviours and milestones, makes it easier to cross-sell and upsell highly relevant products throughout the customer lifecycle.

2. Keeps your workforce efficient

Hyperautomation enables insurers to eliminate manual processes, so staff don’t spend their valuable time on routine tasks – they can be deployed in areas that will deliver the most value (like handling complex cases and working with vulnerable customers).

Combining AI with traditional automation methods allows insurers to achieve new levels of efficiency and productivity, even with legacy systems in place. With RPA, for instance, you can programmatically control and execute linear workflows – with numerous front- and back-office processes – without needing to build direct integrations.

A low-code/no-code platform, like SAS Viya, allows non-technical staff, such as underwriters, to build, deploy, monitor, and manage AI and machine learning models faster and more transparently, helping to drive responsible innovation.  This ability to exploit a range of skills from across your workforce satisfies a top 2023 technology trend: the Composable Organisation.

3. Clamps down on fraud

As long as there has been insurance, there have been people who look to abuse the system – and in the digital age, fraud has become more sophisticated and widespread.

Against this backdrop, claims management must be sharp enough to catch the fraudsters in real time. That means having the most powerful network analysis functions to raise investigatory red flags whenever a potential threat is detected.

Hyperautomation gives them these capabilities by integrating intelligent fraud decisioning into pricing, policy management and claims processes. In the case of motor fraud, this means using live network analytics to identify possible links between drivers, passengers, and body repair shops that would once have gone unnoticed.

Find out how the SAS® Viya® platform on Microsoft Azure can support hyperautomation in your organisation.




About Author

David Shannon

David has over 20 years of experience as a Director and Consultant in Analytics. He provides strategic and tactical advice across the analytics industry delivering cost benefits, productivity and innovation. With in-depth IT knowledge and a reputation for getting things done. Today, David works for SAS leading the UK & Ireland’s Hyperautomation agenda and helping organisations drive digital transformation with automation. Outside of SAS, David is the volunteer IT Director for The MG Car Club. Formed in 1930, The MG Car Club is the original club for MG owners and one of the world's oldest car clubs with around 10,000 members world-wide.

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