Analysis

Robotic process automation and cognitive technologies in insurance

Transforming to a strategy centered on the needs of today’s consumer

Pilot programs exploring robotic process automation (RPA) in insurance are showing positive results and benefits that go far beyond efficiency gains: The potential for robotic and cognitive automation across the insurance value chain is significant.

Brief primer on robotics and cognitive technologies

While RPA is a first step, automation is expected to be increasingly driven by cognitive technologies in insurance. Here we explore how insurers can reconfigure operating models and adopt a more customer-centric approach to capitalize on the opportunities unlocked through cognitive technologies and robotic process automation.

Using robots to drive tangible business benefits is very much a reality today: The IT-enabled RPA market has been growing rapidly at a CAGR of 60.5% from 2014 and is expected to reach US$5 billion by 2020.1

RPA in its pure form, however, is just the beginning. Cognitive capabilities that enable machines to perform tasks normally reserved for human intelligence are now being leveraged with robotics as well. Cognitive technologies include such capabilities as machine learning, natural language processing (NLP), machine vision, emotion recognition, and optical character recognition, among others. Each of these technologies builds on the existing competencies of RPA and advanced analytics, including neural networks, data mining, and Big Data processing.

The resulting combination—termed robotics and cognitive automation (R&CA)—encompasses a potent mix of automated skills with application across the insurance value chain. R&CA is expected to foster greater collaboration between human and machine by both automating repetitive tasks and enhancing the quality of jobs. R&CA technology is now poised to unlock a world of possibilities through the synergistic combination of its key components.


1.Transparency Market Research, IT Robotic Automation Market to Reach US$ 4.98 Bn by 2020, Globally and is forecast to grow at 60.5% CAGR from 2014 to 2020, March 19, 2015

Transformation of the insurance value chain by R&CA

Impacts to the insurance operating model: People

While adoption of any new transformational technology warrants reconfiguration of the insurance operating model, cognitive technologies and robotic process automation in insurance are likely to have the highest impact on the people and technology aspects of the current operating model.

Over the next 10 years, automation is expected to displace 22.7 million existing jobs and create 13.6 million new jobs in the US economy, resulting in a net job loss of 9.1 million jobs (or 7 percent of jobs in the United States). A significant portion of this impact would be felt across the insurance industry, given that 51 percent of financial jobs are projected to be transformed by automation by 20192.

In most insurance organizations, the current delivery pyramid is significantly bottom heavy with the majority of volume-heavy transactions and reporting processes (e.g., regulatory reporting, claims processing, document verification) being performed by humans. Robotic process automation in insurance will likely reshape this pyramid as insurers automate many of these transactions/processes, potentially reducing the size and engagement of the bottom and middle layers of the delivery pyramid, with growth in the top layer.

  • Business development, product, and marketing jobs will increase due to demand for skills in areas such as data analytics, machine learning, and development of algorithms.
  • Operations, including policy servicing and reporting, will have ever-greater levels of self-service and automation, as well as completely new, highly streamlined digital processes.
  • IT and other support functions will require fewer FTEs due to reduced overhead through standardized and automated processes, and the potential migration to new strategic data platforms on cloud and other third-party analytical tools.

These shifts might very well also lead to the creation of more fulfilling jobs in the transformed insurance landscape. For example, knowledge workers might have access to personal cognitive assistants to enable data-intensive jobs and aid in decision-making. This phenomenon, widely termed "Bring your own robot," would likely make employees more productive and efficient, allowing them to focus on innovations to help serve customers better, for example.

We explore some of the key implications of this in our full report, but in summary, as jobs get transformed at all levels across the insurance value chain, it must be understood that the technology will not replace talent as a sustainable competitive advantage. New jobs with completely renewed job descriptions will be created as a result of this large-scale transformation. To gain the most, organizations will need to strike a balance between transitioning to robotic process automation and cognitive technologies in insurance and making required FTE adjustments and up-skilling their existing workforce.

2 Forrester, The Future of Jobs, 2025: Working Side by Side with Robots, August 24, 2015

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FTE impact of R&CA on insurance functions

Impacts to the insurance operating model: Technology

Insurers should prepare themselves for the imminent R&CA transformation by reconfiguring their IT systems. The transformation will be an extension of the journey that has begun in such areas as RPA and advanced analytics enablement, most likely including:

  • Modular sourcing: The R&CA technology industry is now engaged in a startup-like phase, in which nimble firms that provide specialized technological capabilities are well positioned to disrupt the incumbents. These vendors are already providing disaggregated services on the cloud. For example, one leading ecosystem player provides a series of modular services such as "personality insights," "visual recognition," "text analytics," etc. Through this approach, insurers can source different capabilities from niche vendors provided that their underlying IT architectures are flexible enough to tap into cloud-based services and use them as "cognitive operating systems" in building intelligent applications.
  • Integrated systems: R&CA technology has the inherent capability to iteratively self-learn and generate insights through access to data from multiple sources. To maximize the returns from this technology, integration with legacy systems and other emerging technologies such as Big Data, IoT, and cloud must be achieved. This will likely lead to a much desired breakdown in silos of data across the enterprise, enabling the establishment of a single source of truth and delivery of a unified data model in a significantly more consumable form.
  • Transparency and control: Cognitive technologies and systems will undoubtedly partner with humans in the near future. To gain trust in the robots, humans will need to understand how a particular decision has been reached. Given the nascent stage of R&CA technological development, humans are expected to have the ability to overturn machine-made decisions. Furthermore, regulators are likely to insist on robust audit mechanisms. The R&CA systems of the future will have to be designed keeping in view all these transparency and control features.

The technological landscape is evolving quickly, with two crucial implications for insurers: 1) the need to identify and source relevant capabilities to allow for better task design; and 2) an appropriate division of labor between humans and machines.

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Staying focused on customer centricity in an R&CA world

With the demographics of insurance customers reflecting an influx of Millennials, Gen Xers, and Gen Yers, customer interaction preferences are changing. According to one recent survey, approximately 41 percent of respondents have left an insurer because of poor customer experience.3 In another survey, 27 percent of the Gen Yers and 23 percent of Gen Xers who were questioned indicated that they want to interact with their insurer thorough digital self-service.4 Customer expectations for convenience through consistent information and service levels across multiple channels or touch points is likely to drive insurers to mirror non-insurance industry experiences, such as online retail and banking.

Insurers have already started to employ advanced analytics to gain deeper customer insights. However, the volume, unstructured nature, and velocity of data being generated are beyond the realm of traditional analytic processes. The benefit of cognitive technologies in insurance is that it can solve problems that traditional analytics cannot readily address. R&CA will help empower insurers with the ability to provide improved customer experiences and more personalized offerings.

  • Improved customer experience:
    • Robots equipped with language processing capability could replace human interaction with customers in areas such as First Notice of Loss (FNOL) and customer support.
    • Using machine learning techniques, robots will be able to iteratively improve their understanding of customer queries and grievances.
    • With advances in emotion recognition and sensing technology, robots will also be able to analyze patterns in customer behavior.
    • With machine vision technologies, customers could potentially send pictures from an accident site and the robot positioned at the other end would assess the extent of the damage. While this feature may not be immediately extended to complex claims cases, it certainly is expected to reduce the handling time for simple claims.
  • Increased personalization:
    • R&CA can enable insurers to virtualize the underwriting process to a large extent, thereby facilitating their ability to scale up to a wider customer base. With such advancements at hand, the insurance industry is expected to move away from the practice of "finding customers for products" to a model in which needs and risks of customers are understood and considered at a much more granular level.
    • Taking cues from the investment management industry, robots are being designed now to act as trusted risk advisors to insurance customers. To that end, insurance robo advisor Clark, for example, recently completed "Series A" funding of ~13 million euros.Clark uses algorithms to first analyze customer needs and then automatically propose optimization opportunities.
    • Leading insurance companies are already using analytical engines to generate a unified profile view of their customers as a means of intelligently aiding agents on their customer calls. During a customer conversation, for example, a smart assistant could provide the agent with insights about the customer's upcoming trip to Italy. It can also customize the coverage at different price points to suit a customer’s personal needs. An agent armed with an electronic smart assistant is sure to have more enriching conversations with customers.

These are just some of the ways cognitive technologies and robotic process automation in insurance can act as key enablers for customer centricity. Leveraging the plethora of capabilities offered by such tools, insurers can now design customer journeys from scratch rather than simply replicating existing journeys that are at best yesterday's stories with merely a bit more processing efficiency.

Report, “Understanding customers and risk: Your cognitive future in the insurance industry,” IBM, October 2015
Press release, “Improved Interactions Drive Gen Y Increase in Auto Insurance Satisfaction,” J.D. Power, June 19, 2015
5 Finleap, 'Insurance-robo-advisor Clark receives 13.2 million Euro', August 2, 2016

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With such advancements at hand, the insurance industry is expected to move away from the practice of "finding customers for products" to a model in which needs and risks of customers are understood and considered at a much more granular level.

How should the industry approach an R&CA-driven transformation across its value chain?

To start, the core foundation of R&CA technology is guided by four broad principles:

  • Cognitive systems need to synthesize vast amounts of data to generate powerful insights and connections.
  • Robotics capabilities play a dominant role in performing actions that would otherwise be driven by humans, the results of which produce insights that help generate and validate hypotheses to aid in decision making.
  • Cognitive systems must interact with customers and employees using natural language and demonstrate contextual reasoning.
  • Given their probabilistic nature, cognitive systems need to continuously learn from their past actions and evolve more accurate algorithms.

With a firmly established core foundation, insurers can adopt a measured approach to achieve their desired R&CA goals:

Explore our full report for more details on this framework.

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"The horse is here to stay, but the automobile is only a novelty, a fad."

The president of Michigan Savings Bank may not have predicted the future accurately in 1903, but insurers today should heed his words: Those who fail to embrace the cognitive journey will likely cede important strategic advantage to competitors and new market entrants already riding the wave.

Conversely, organizations that attempt too much too soon in pursuit of first-mover advantage in the R&CA space may also be at risk. Running a manageable set of pilot programs first to test cognitive technologies in insurance and robotic process automation in insurance is a more sound strategy. This approach can enable organizations to align business outcomes with expectations and facilitate a smoother implementation downstream. Once pilot results prove out, a longer-term strategy can be leveraged to define how R&CA should be blended into the fabric of the organization.

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So, where do you go from here?

Deloitte can help you define an optimal and successful operating model and a strategy centered on leveraging new enabling technologies like R&CA to meet the needs of today’s insurance customer.

David Kuder, principal, Deloitte Consulting LLP
Robert Kaye, principal, Deloitte Consulting LLP
Marc Zimmerman, managing director, Deloitte Consulting LLP

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