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The Actuary The magazine of the Institute & Faculty of Actuaries

The fourth industrial revolution

Ravin Jesuthasan and Day Bishop explain how technology is transforming the insurance value chain



The convergence of several transformative new technologies – collectively dubbed the fourth industrial revolution – will likely transform the risk landscape in the decades to come. The rise of robotics, artificial intelligence, and autonomous technologies also has the potential to transform how work gets done across the insurance value chain, from sales and underwriting to claim processing and payments.

Many office jobs and knowledge worker occupations are seeing automation change their work. Naturally, this has many worried that the rise of automation and artificial intelligence, or AI, will replace them. Although there’s potential for companies to save on automating parts of their workforce, this doesn’t mean business leaders should simply lay off staff in favour of automation. Instead, they should consider new ways to channel human worker knowledge and identify how best to make the most of all of that experience and expertise, even if the mechanical aspects of their work have gone away.

Although we are just at the beginning of the Fourth Industrial Revolution, it is already possible for insurers to deconstruct jobs into component tasks and choose among many emerging options for completing them, including AI and robotics, machine learning and talent on a platform. Auto insurers are using telematics to capture data on driving habits to better manage risk and set rates. And property, casualty, and life insurers are starting to employ virtual assistants to enhance customer service and help customers select the right coverage.

To fully capture the opportunities in this new world of work however, insurers will need an understanding of the enablers of automation as well as a framework to guide their decision making as they redefine employment relationships and organisational boundaries.


In this new world of work, it is critical for employers to understand which tasks might best be completed using intelligent automation versus other options. To get started on this journey, leaders should categorise a job’s activities into buckets: routine versus non-routine, and what’s transactional in nature versus advisory or consultative. Routine and transactional tasks are most easily automated. For example, an organisation might decide to deconstruct a claims processing job that’s been done the same way for 20 years, using automation to complete some of the routine tasks while hiring someone on a talent platform to tackle the non-routine tasks. Insurers should first experiment by selecting a few jobs to deconstruct, because unless you can understand how AI and robotics will transform work at the task level, it will be difficult to adopt AI and robotics at a systemic level. Experimentation is critical given the magnitude of the change and you certainly don’t want to disrupt the core operating model. So, by taking on a pilot, an insurer is able to learn quickly and fail safely.

First, a firm might want to identify jobs in areas where their organisation is having difficulties attracting talent. For instance, the ability to compete in emerging areas, like advanced analytics, often hinges on getting the right data science talent. This type of critical talent can be difficult for insurers to attract and costly to hire, so the firm could decide to deconstruct several key analytical jobs. Once these jobs are deconstructed into tasks, employers need to evaluate the speed-to-capability, risk and cost implications of different work options. They might then find that their best option is to access world-class talent via a talent platform for tasks requiring highly sought-after skills. 

Different types of automation

There are three different types of automation likely to be of particular value to insurers (Figure 1):

  • Robotic process automation can replace routine, white-collar work. It is especially effective in compliance work and claims processing where data needs to be updated or transferred from one software programme to another, such as a spreadsheet to a client relationship management or enterprise resource planning system.
  • Cognitive automation improves the quality of decision-making and interaction someone will have with a customer.
  • Social robotics are robots that work alongside humans to automate both routine and non-routine tasks. The classic example is a driverless car or truck. While the insurance implications are just emerging, it is clear that autonomous vehicles could have the ability to radically transform insurance from shifting the basis of risk (from driver to asset) to enabling greater micro-pricing of risk.


Figure 2

Greater savings compared to outsourcing

Analysis by Willis Towers Watson reveals that companies in many industries, including insurance, that deconstruct jobs and distribute the work using the most efficient and effective means can typically realise savings in the 60% to 80% range. This is significantly greater than the 30% typically achieved through outsourcing. But to capture the opportunities, organisations also need to think about work differently. In particular, it is important to understand the key decisions that need to be made in three areas, as illustrated by Figure 2.

On the left, we see traditional employment. Work is ‘constructed’ into jobs, collected at a point and space in time, and executed through an employment relationship. The organisation is self-contained, detached, insular and protective, and has a rigid shape. The reward package is permanent, collectively consistent and uses traditional elements (money, hours, working conditions). On the right, we see a world beyond employment. Work is deconstructed into tasks, dispersed in time and space, and executed through many virtual and market relationships other than traditional employment. The organisation is permeable, interconnected and collaborative, and can change in shape. The rewards are impermanent and individually defined, and use imaginative elements (game points, reputation).

Today, firms have the ability to deconstruct a job and have component tasks completed anywhere in the world faster, better and cheaper than ever before. In turn, this trend is leading to new work relationships that are shorter in duration with a greater equality of power between employers and talent. Machine learning, 3-D printing, mobile technology and algorithmic analytics are just some of the innovations transforming work, and both replacing and augmenting human capability. 

But before insurers can unlock value from this new work ecosystem, they need to be able to assess their various work options and understand how best to develop new capabilities as quickly and efficiently as possible, without taking on unnecessary risk. As work moves outside the organisation, it will be critical to mitigate the risks associated with the potential ‘lack of control’ of the workforce (liability, loss of intellectual property). As the level of skills within the organisation continues to shrink, it is essential the business insulates itself from the increasing risk of obsolescence. Insurers must communicate their plans to all stakeholders – leaders, managers and employees – who will need to understand this new way of working. Being able to deconstruct jobs and make decisions as to how best to complete the work, using resources inside and outside the organisation, can confer significant competitive advantage to insurers.

Ravin Jesuthasan specialises in the future of work at Willis Towers Watson, and is a managing director in Chicago

Day Bishop specialises in insurance consulting and technology at Willis Towers Watson in New York