Even with significant investment towards automation, most insurers are still facing challenges moving from pilot to profit on their investments.
Our experience working with leading insurers suggests that creating the right digital labor strategy is an important enabler to transforming the enterprise. And our work suggests there are clear factors that drive success in formulating and executing a digital labor strategy in the insurance sector.
As insurers rapidly become more digitally enabled, many are starting to think much more strategically about how they use ‘digital labor’ to drive their transformation strategies and achieve their long-term objectives. Activity (and investment) has been feverish.
Some insurers have been incubating their own concepts for digital labor in their digital garages and venture capital units. Others have been talking with new insurtech startups and creating partnerships to explore and exploit new technologies. Many are simply hoping that their business process outsourcing providers will continue to innovate and introduce new digital labor concepts as they are commercialized.
When we talk about ‘digital labour’, we are broadly referring to the automation of labour by leveraging digital technologies to augment, or automate the tasks undertaken by knowledge workers in your business. This extends from simple robotic automation through to machine learning and cognitive automation. The spectrum of potential ‘digital labour’ use cases can be very broad — ranging from automating simple swivel-chair activities such as cutting and pasting content from one system to another, right up through cognitive solutions (software that can think and reason) performing activities (e.g. business, medical, legal) previously performed exclusively by humans — and often performing these activities far better than their human predecessors.
Basic robotic process automation (RPA) | Enhanced process automation | Cognitive automation |
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Source: KPMG in the US, 2016
Progress has also been encouraging. Almost every insurer we work with already has some type of robotics pilot project or automation initiative under way in one or, more often, multiple parts of the organization. Many have already automated some of their more routine processes, particularly in the finance function. Most are now trialing more sophisticated robotics techniques deeper in the organization.
Recent research also suggests that insurance CEOs expect digital labor to start to make an impact on their operating models almost immediately. In fact, almost a third of insurance CEOs say it is extremely likely that 5 percent or more of their technology workforce will be replaced through automation within the next 3 years.1
However, most efforts to introduce digital labor within the insurance sector have largely been focused on RPA; basically using robots (or, more accurately, algorithms) to speed up processes that had often already been automated. RPA reduces errors, improves processing time and encourages digitization by 30–40 percent and, therefore, is a great first step towards the adoption of digital labor. But insurers will need to become more sophisticated about their use of digital labor if they hope to drive real transformation and competitive advantage.
Development phase
Commercialization phase
Here, too, competition is heating up. Enabled by newer technologies such as machine learning and natural language processing, some of the leading insurers are starting to develop new cognitive capabilities that could usher in a new era of productivity and customer-centricity. They are letting their bots watch their actuaries as they make their decisions; they are feeding them warehouses of historical data and decision records; and then they are starting to let them make key decisions in areas such as specialty commercial policy renewals and personal line claims approvals.
Interestingly, the leaders are the ones that recognize that — rather than delivering value through cost savings and head count reductions — the real value of digital labor actually comes from its ability to unlock unprecedented levels of productivity, organizational agility, confidence and competitive advantage. And that will allow some insurers (particularly larger, traditional ones) to operate and compete on a more level footing with their nimbler startup rivals not only in terms of cost, but also in terms of customer responsiveness and experience.
The problem, however, is that few insurers know exactly how to move forward from here. The vast majority are struggling to take their pilot projects into full-scale production in a way that is meaningful to the business. Valuegenerating ideas and capabilities from one part of the organization are not being shared with other parts of the enterprise. And duplication is rampant. As a result, few insurers have any real road map to help guide their digital labor strategy.
Many also face significant capability challenges. Internally, few have the resources, skills or talent to drive forward an enterprise-wide digital labor strategy, let alone the underlying supporting IT architecture. And while the external vendor environment is certainly evolving, knitting together the right combination of solutions to enable the business is still highly complex. Few insurers want to play the technology developer/integrator role. Most would much rather focus on improving their core business.
It is perhaps not surprising, therefore, that almost every (91 percent) insurance CEO surveyed by KPMG International said they were concerned about the challenge of integrating automation with AI and cognitive computing.2
We have worked with a number of traditional insurers to develop and execute their enterprise-wide digital labor strategy. And we witnessed some significant achievements and some unexpected failures; both offer useful lessons for insurers. Based on our experience, we have identified five success factors that are shared by many leading digital insurers.
Of course, there is another approach to building your digital labor force: you could always outsource it. Indeed, we’ve been working with a number of insurers (both smaller firms lacking the time or resources and larger players keen to focus on their core business) to deliver a managed services approach to the development and execution of their digital labor strategy. As with any form of outsourcing, it is critical to understand the art of the possible and identify how you want to leverage digital labor to best effect. You can then map this to a sourcing strategy, identify the right vendors, integrate their solutions and prepare for wider adoption of digital labor. Given the immaturity of the technology space, many insurers are relying on their sourcing partner to protect them from the shifting vendor landscape and the speed at which new capabilities are being introduced.
Our experience suggests that — regardless of the level of outside support you require — the adoption of digital labor will be key to driving value from digital transformation investments. Those insurers that take a well-planned and strategic approach to their digital labor strategy will be the winners in this new environment.
Recognizing the connection between improved internal processes and customer satisfaction, the executive team of one large multilateral global insurer wanted to explore how they might leverage predictive analytics and automation to help streamline their claims payment process. The leadership had a lofty goal: to reduce the total time to pay from 30 days to just 15 minutes.
The organization began by identifying the key data factors underpinning the process and, after collecting and processing the structured and unstructured data, developed a proof of concept that used new machine learning algorithms to achieve their goal.
The initiative has been a tremendous success, delivering potential savings of almost 50 percent of the cost of claims processing, improved consistency within the process and creating better global cohesion. More importantly, the initiative has helped deliver dramatic improvements in customer experience at a critical ‘moment of truth’, enabling better interactions driven by the right people asking the right questions at the right time.