The global intelligent process automation (IA) market is expected to top $14 billion by 2024. However, the insurance industry has, in some instances, been slow in reacting to the opportunities presented by the technology. This is not altogether surprising given insurers’ historic slower pace in adopting new technologies when compared to the banking sector for example.
Unlike robotic process automation (RPA), which can be considered a more mechanical process that frees up staff from repetitive job functions, IA combines RPA and artificial intelligence (AI) technologies to empower the intelligent automation of business processes. For insurers, part of IA sees intelligence injected into those business processes that focus on critical decisioning points such as underwriting and claims. So, while RPA relies on algorithms that can replicate keystrokes and greatly assist businesses with high volumes of transactions, IA includes a specific focus on automating decisioning in business processes.
Fortunately, the lockdown has contributed to a momentum shift with insurers realising they can no longer rely on traditional, paper-based processes. Instead, the focus has been on digitising as much data as possible, a critical step before any form of automation can be implemented.
A matter of IP
And yet, when it comes to the decisioning process, insurers still view it as a fundamental component of their intellectual property. One can understand the thinking behind this given the amount of time spent training individuals to become experts in their fields. After all, the potential exposure when calculating risk and performing underwriting functions can number in the millions of Rands if done incorrectly.
The reluctance to automate human expert decisioning with AI is evident. But this does not have to be the case. AI can be used to model the most highly skilled underwriters and claims experts within the insurer and has the added benefit of being available 24×7 which dramatically speeds up historically slow processes, often subject to tight SLAs. This greatly improves the customer experience as self-service solutions can be introduced where people can manage their policies at a time convenient for them.
Given their nature, insurance companies are risk averse and generally slower to adopt new technologies. They are generally reliant on their ‘human experts’ and are hesitant to replace them with automated solutions. But the need to use these experts’ time more efficiently will gradually see insurers embrace IA, thereby freeing up resources now capable of delivering more strategic functions inside the organisation.
It could very well be the focus on customer-centricity that delivers the final push needed for insurers to fully adopt IA. By improving manual and multiple step processes through automation, employees can be repurposed for other, higher valued tasks.
Real-time decisioning through AI can, for example, reduce the number of fraudulent claims. This, in conjunction with other more efficient administrative processes, will bring about a reduction in product pricing that will lead to happier customers and ultimately an increase in profitability and improved market competitiveness.