By Dr Leslie Willcocks
I have been working with Dr John Hindle at Knowledge Capital Partners on a series of papers based on research during 2021 into the strategic use of intelligent automation. Our research findings are very rich, and are available at KnowledgeCapitalPartners.com. Here I want, with John, to focus on a further sector—insurance—and give illustrative examples of the headway that can be made.
Insurance: Future Vision
What will the insurance industry look like in ten years’ time? What role will intelligent automation play? What are the choices? Are you preparing? These are critical questions for an industry whose essence is calculating risk. As a data-driven business—from risk assessment and underwriting to distribution, and from pricing to claims—the entire industry value chain is ripe for intelligent automation and digital transformation. How so?
Present technological trends are consistent with the following possible 2030 realities. Insurance purchasing is exponentially faster. Risk profiles are automated and updated in real time. A much wider range of customers receive more or less instant quotes. Blockchain applications enable smart contracts and fast payments. Policies provide micro-coverage via multi-party insurance and adapt dynamically to individual behaviourial patterns and needs. Fewer agents rely heavily on technology to carry out many more tasks. Underwriting is automated to a few seconds for most customers across life, property and casualty insurance. Predictive analytics allow pro-active, complex policy offers to customers. Through automation, pricing has become massively sensitive and competitive. Differentiated customer experiences provide the key metric and expectation, but profit margins are very thin.
Claims processing, including fraud detection, is 90 percent automated, using the full array of available technologies. Headcount is 80 percent lower than today, with processing times measured in minutes, even seconds. Pre-emptive technologies, for example internet of things in the home or car, are massively focused on reducing claims before they arise. Except for unusual, contested and complex claims, customer service is largely automated and claims settled within minutes. In the face of all this, not surprisingly, regulation has become highly technologised, focused on reviewing and approving machine learning-based models, data usage, and underwriting practices.
Today’s Challenges for Insurance
How does this happen? There are some obvious drivers. Customers’ digital expectations have become higher. The pandemic crisis has accelerated the adoption and convergence of automation and digital technologies. It works, it’s available, it provides resilience and fallback. Insurers can see new uses. Furthermore, in very competitive markets, ‘insurtech’ companies already provide stiff competition. They either take a customer-focused approach and target traditional insurers’ pain-points and inefficiencies, or alternatively, they pursue a direct-to-consumer strategy, launching new easy-to-use products, and pressuring adoption of automation and digital technologies.
An even greater driver are the historic and unsustainable high operating costs across the industry. Unlike other large-scale industries such as automotive, telecoms and airlines, large global insurance players (with some leading exceptions) have generally not improved overall productivity in the last ten years. While investments in automation have boosted labour productivity, overall cost ratios have not improved. On this issue alone the industry is ripe for structural changes to business and operating models. Leaders are already taking action: according to a McKinsey study the top 20 percent take nearly all the industry’s economic profit, and are notable for their close cost management. Yes, some are very large companies that capture economies of scale. Others benefit from less complex operating models in highly-standardised market segments, e.g., bancassurance risk products. But still others have been heavily investing in digitalisation and automation and are starting to see the benefits.
The challenge, therefore, becomes structural change, not least simplifying the end-to-end business model and capitalising on the massive opportunities provided by digital and automation technologies.
In our research into leading organisations, however, it became clear that solving the insurance industry’s efficiency problem, by itself, is an insufficient strategy. It can be seen from our 2030 scenario that the industry, aided and abetted by advanced technologies, will move on from greater efficiency to becoming predictive, then future-ready. As at 2021, then, the three immediate areas for attention are efficiency, yes, but also innovation and customer experience. Let’s look at some illustrative cases.
Global Insurance Provider
In keeping with our ‘3Es’ journey narrative, this global provider began by capturing efficiency gains, thereby releasing funding and resources to support more advanced transformation programs. With a federated operating framework, the company created a global Centre of Excellence (CoE), co-located with its global IT, cloud, Infrastructure, and Business Services teams. The CoE established preferred supplier relationships for RPA platforms and cognitive tools and published guidelines at a global level, enabling local business entities to identify where to focus first, depending on their current operating state.
With overall enterprise architecture responsibility, the CoE provides advisory services to operating units, along with end-to-end ‘Automation-as-a-Service’ and RPA ‘Platform-as-a-Service’ delivery capabilities. During the first stage of deployment, the focus was on leveraging the legacy enterprise data and application estate for efficiency and cost reduction. Its larger remit is to help business groups scale automation in a cost-effective manner.
The company reports strong efficiency gains to date from 24/7 operations, supporting higher employee productivity with lower recruitment/training costs. Process improvements have seen fewer FTEs utilised, and some staff redeployed to higher value tasks. These gains, in turn, have supported wider business effectiveness from higher and faster transaction throughput, increased asset utilisation and ROI, and workload relief for IT applications developers. Automation has also improved regulatory compliance, strengthened security and produced greater employee stability and job satisfaction.
These gains in effectiveness have, in turn, led on to significant gains in enterprise enablement, including better analytics; development of new products; greater enterprise scaling; responsiveness and agility; resilience in the face of event threats (including the COVID-19 pandemic); differentiated customer experiences achieved relatively cheaply through RPA; and more agile and streamlined end-to-end value chains—all resulting in deeper and wider market penetration and share. The top three gains so far have been in workforce optimisation, customer experiences and resilience, but much more is expected, and the company is well along the path to digital transformation.
A UK insurer initially sought to capture value from what it called ‘automation arbitrage’—cost efficiencies across multiple business problems resulting from what the leading automation executive describes as ‘growth through evolution rather than design’ that had led to a very complex organisation.
Beginning in 2016, the initial strategy focused on automating stable processes for cost avoidance, concentrating in particular on reducing the transaction volumes it was sending to its BPO provider. The solution involved disaggregating the customer on-boarding process, applying digital workers to handle complex transactional parts of the process fast and accurately, while relying on the BPO provider to handle parts that required human interpretation. As a further development the introduction of more cognitive automation tools will probably see more of the process being brought back in-house.
The primary focus initially was on automating a defined set of stable processes for greater efficiency and reducing costs—there was a lot of ‘low-lying fruit’. Fewer FTEs are being used, and staff are redeployed to higher value work. Automation made inroads into cost avoidance and rework reduction. As an indicator, at one stage 21 robots were doing the work of 50 FTEs, more consistently, and at lower cost. A spin-off overall was improved data quality and integrity. The company aimed for and achieved efficiency gains of some 150 percent.
The automation targets have also moved to realising value. The company has gained greater enterprise effectiveness by applying their automation experiences to improve other processes, creating what it calls an ‘evolving business case’ as automation has grown organically. The automation lead commented: “You automate the 50,000 things you do every day; the things that take up your time.” Automation greatly improved regulatory-mandated compliance, for example—transaction accuracy, traceability and auditability. Automation led to more effective use of the outsourcer, giving them the human work in an otherwise automated system. Workforce augmentation through automation means that large numbers of new customers can be enrolled quickly without disruption, when, before, it took weeks and additional staff. Such improvements increase enterprise ROI around the clock.
Further gains in enterprise enablement came from added capability, for example applying what the company calls AFTEs (Automated Full Time Equivalents) to handle new workloads—work that wasn’t being done before or short-term demand spikes—without hiring temporary human workers. Massive gains have been made in increased resilience, and strengthened, rapid administration, especially during the 2020–2021 pandemic, not least in the healthcare parts of the business.
Taken together, the company’s automation gains have been remarkable. As mentioned, it fully captured its expected efficiency gains of 150 percent compared to its previous ‘run’ model cost, but it also estimates an additional 150 percent unplanned value gains from increased enterprise effectiveness, and a striking 450 percent gain in superior enterprise enablement. This insurer exemplifies the pattern we have seen in other sectors: intelligent automation value is exponential, not linear.
This major European insurer started with RPA in 2015 amongst the Life, Commercial and Claims parts of the business. By 2017 it had built an automation CoE, then extended to a federated model, with a hub in Claims. The concept was to help other business lines improve processes relevant to them, then scale to an enterprise connected digital workforce. Customer and governance benefits from automation have been more recent targets.
The insurer had planned 100% efficiency gains, and so far, has realised 80 percent. These gains come from 24x7 operations, fewer FTEs needed (e.g., in one country at one point 55 robots ran 125 processes), process improvements, and some cost avoidance. Automation greatly improved speed on payments, checks and response to customers (e.g., checks from 24 hours delay to one hour). Security has also improved.
As with our other two companies, a lot of the effectiveness gains—in this case estimated to be actually 100 percent —were not planned. They come from a mix of higher throughput volumes, increased enterprise ROI; avoiding the IT queue; early links with cognitive tools; optimising skills sets (recent); improved regulatory compliance; whole organisation margin improvement; better quality data for analytics; and improved customer and employee engagement/satisfaction. The company has also experienced big gains managing critical business processes e.g., disaster recovery, dealing with backlogs, handling process peak periods, and being able to switch across processes, e.g., HR, Finance and Claims.
The company is progressing enablement gains, planning 100 percent, and achieving so far 45 percent of these. The company now has an enablement platform which is already producing better analytics for decision-making. The platform has increased disruptive potential and first mover advantages in the marketplace (e.g., faster acquisition and integration of brokers). The intelligent automation platform has facilitated great strides in providing a differentiated total customer experience (e.g., faster claims, better up-to-date information, speed to quote) and offered greater resilience all round during the 2020–2021 pandemic crisis. More processes are in the automation pipeline, together with increases in the digital workforce (in one country from 75 to 120 digital workers), and a scaling of the CoE to 75 staff.
We have seen three insurance companies well on the way in their intelligent automation and digital journeys.
- 1. All three evolved their automation, gained early efficiency wins, and discovered new value as they applied automation more knowledgeably. Frequently the effectiveness gains were not even guessed at, let alone planned for. Companies that follow can no longer have that excuse.
- 2. Our executive respondents all commented how difficult it was to estimate potential and actual effectiveness and enablement gains. However, all could forcibly state where the gains had been achieved, and where future gains would arise. The estimation/measurement problem has always haunted investments in information and communications technologies. This is why we placed the vision of likely 2030 realities at the beginning of this paper. Can anyone honestly refute what the trends are, how they are accelerating, and what the likely outcomes are likely to be for the insurance industry, worldwide? The three companies we have looked at are finding their way forward. Direction, trial and error, patience, and long-term vision and investment have become the keys in the insurance sector.
- 3. Of course, the insurance sector, understandably, is, culturally, very risk averse. This is absolutely right for certain parts of insurance business. But in other parts, just because risk, cost and gains cannot be precisely calculated, does not mean that risk, cost and gains do not exist, and can be safely ignored. Sometimes the risks of taking action are much smaller than not acting. Intelligent automation and digital transformation are already game changers for insurance sectors worldwide. Are you on course for our 2030 vision, or can it be safely discounted?
Note on the Research
Our research draws upon a KCP/LSE proprietary database of 500 plus RPA and cognitive automation cases studies taken from multiple sectors and economies. These were studied over time (from 2015–2021), and included ‘leader’, ‘follower’, ‘laggard’ and ‘also ran’ users of the technologies. We gained additional insight from four annual surveys in this period and from reviewing over 350 award submissions covering innovatory and effective automation practices. Earlier findings appear in four books and in the Blue Prism series ‘Keys to RPA Success’ and ‘Just Add Imagination’, and published articles in Sloan Management Review, Harvard Business Review, LSE Business Review, Forbes and MISQ Executive. Building on these foundations, in 2021 we researched an additional 15 advanced user organisations taken from the banking and finance, insurance, health, telecommunications, and utilities sectors in the USA, Europe and Asia Pacific. We used interviews, documents, and survey questionnaires. We also reviewed over 350 award submissions covering innovatory and effective automation practices. The objective was to gain further insight into the technologies used and the business value being planned for, and achieved.
Willcocks, L. and Lacity, M. (2016) Service Automation: Robots and The Future of Work (SB Publishing, Stratford-upon-Avon)
Lacity, M. and Willcocks, L. (2017). Robotic Process Automation and Risk Mitigation: The Definitive Guide. (SB Publishing, Stratford-upon-Avon)
Lacity, M. and Willcocks, L. (2018) Robotic Process and Cognitive Automation: The Next Phase. (SB Publishing, Stratford-upon-Avon)
Willcocks, L., Hindle, J. and Lacity, M. (2020) Becoming Strategic with Robotic Process Automation, (SB Publishing, Stratford-upon-Avon).