Embracing a growth mindset and understanding how new disruptive technologies could change our industry are among the best strategies to prepare for the opportunities and challenges of the Fourth Industrial Revolution. I highlighted some of the new disruptive technologies in Part 1 and Part 2 of this blog series.
At Gen Re, we advise clients to routinely update their companies’ boards on how artificial intelligence (AI) advancements and collaborative robots are changing their clients’ industries and whether technology is replacing or complementing workplace activities.
What are some critical actions for evaluating AI and developing technologies?
1. Separate the hype from reality. The amount of information can be overwhelming for any CEO or board, so consider getting assistance from trusted advisers in tracking developments.
2. Focus on the core practices, processes, products and people at your customer organizations. Your policyholders’ employees can help you analyze which industries in their portfolio are most vulnerable to automation within the next five years. If a critical assessment reveals that a significant part is susceptible to obsolescence, examine whether product development, market expansion or new partnerships can provide a buffer for anticipated premium or market share loss.
3. Don’t overlook your own underwriting and claim operations. Can you use AI to improve your own underwriting results or identify creeping catastrophic claims? Having a work culture that encourages a growth mindset and embraces new technology is essential.
4. Critically track and examine the legal and regulatory issues that can slow the adoption of AI, robotics and automation. While AI technology continues moving forward, many legal and ethical questions surrounding this technology remain unanswered. Driverless technology provides one pressing example for insurers. As Warren Buffett commented at the 2017 Berkshire Hathaway annual meeting, “If driverless cars became pervasive, it would only be because they were safer,” which would mean that “the overall economic cost of auto-related losses had gone down and that would drive down the premiums” for insurance companies. We do not know when driverless technology will be widely adopted, but we know that now is the time to prepare for its impact on auto, umbrella and workers’ comp portfolios.
5. Don’t wait. It is not too soon to start the journey toward understanding the impact and possibilities of AI, robotics and automation. Ignoring the trend can be costly regardless of what lines of insurance you write.
Over the past decade, U.S. tech firms have made significant advancements in artificial intelligence and robotics, making it far easier and more efficient to automate tasks and functions across industries. Artificial intelligence (AI) affects all types of risks and lines of insurance, and the workers’ compensation market has a particularly large stake in the developments.
Although the U.S. has experienced technological change and disruption during prior periods of industrial revolution, the pace and scope of the fourth industrial Revolution positions it to have a far greater impact on the U.S. and global economies. The recent advancements in AI and robotics are some of the most significant computer science advancements of our generation. Google CEO Sundar Pichai has compared the advances to the discovery of electricity and fire, while Bain predicts that the U.S. will invest $8 trillion in automated technologies by 2030.
The U.S. is currently the global leader in developing and investing in AI technologies and robotics; however, our global competitors are rushing to catch up. In 2017, AlphaGo, an artificial intelligence program developed by Google, defeated Ke Jie, the world’s champion Go player. (Go is a popular and complex ancient board game made digital). Since then, global investment dollars in AI continue their upward trend.
Back in 2015, China’s government launched the “Made in China 2025” campaign to become a market leader in developing these new technologies by 2025. As China and other global leaders invest in smart factories (which are driven by AI and robotics), the rise of these factories will affect not only production worldwide but also potentially eliminate jobs and keep wages down worldwide. This intense focus and investment from our largest global competitors will likely accelerate the pace and scale of change and limit our ability to manage the disruptive effects across many sectors of our economy.
Significantly, the new technologies are poised to challenge traditional assumptions that AI and robotics will be used to perform only low-level and highly repetitive tasks. MIT’s latest research shows that machines are better at pattern recognition and judgment calls. New AI technologies and robotics are also helping doctors detect early signs of cancer by analyzing a condition and comparing it with data points of other patients. (We’ll explore this notion further in our next blog in this series.)
It remains unclear whether the benefits of AI and robotics will outweigh the disruption to many traditional industries and their employees. In fact, a number of influential CEOs, venture capitalists and academics have already raised concerns about how these advances in AI and robotics could fundamentally change our society and the future of work for blue- and white-collar workers.
Blackstone’s CEO, Stephen Schwarzman, who provided $250 million to launch MIT’s new college for AI and robotics, remarked, “We face fundamental questions about how to ensure that technological advancements benefit all – especially those most vulnerable to the radical changes AI will inevitably bring to the nature of the workforce.”
Monumental changes in how and where work is performed create new risk and safety challenges. This session at the RIMS 2019 Annual Conference & Exhibition examined emerging workplace risks and effective safety strategies to address them.
Larry Pearlman, senior vice Ppesident, workforce strategies practice, Marsh
Timothy Martin, global health and safety manager, Steelcase
Ergonomics are a problem across many industries, especially with an aging workforce. Wearable devices measure body stress so that, with injuries, we can determine what happened, how it happened, when it happened and if it will happen again. Different technology like exoskeleton suits are available to help with strenuous activities, which can help retain your aging employees longer than otherwise expected.
Industries have evolved from using barrier robots (kept away from employees), to collaborative robots (good for repetitive tasks but extremely complicated to program) to now using autonomous robots. Autonomous robots are simple to program in an extremely short time, so virtually any employee can control them with little effort.
Employers are still not being proactive enough on workplace violence, despite the increasing frequency. Training does not extend to drills, and mental health problems are going unaddressed. Employers need to shift from reactive policies to predictive and prescriptive policies. Technology has evolved to provide electronic robots that can patrol your workplace, supported by a control center that can interact with employees in real time.
4. Workplace Wellbeing
Studies show that employees are stressed and in poor health. Employee wellbeing is a major problem, and employers need to implement support for total wellbeing – physical, emotional, financial, social. There is a certain way to inspire wellbeing that does not seem like you are telling employees what they should be doing, which is ineffective. There are more-effective programs available that will tailor programs to employee preferences.
5. Temporary Workers
Temp workers often do not know proper safety basics and company policies related to safety. Employers can reduce the risks related to temporary workers through hiring practices, screening exercises, onboarding and continuous training. If you use a staffing agency, you can partner with it so that it aligns with your safety philosophy. Be transparent and try to match the type of work to the worker based on physical job requirements.
6. Changing Demographics
Training methods must adapt to address the changing nature of the workplace. A blended learning approach is now necessary for different generations. Technology is addressing safety learning preferences for the younger, tech-savvy generations. Micro-learning is available to address bite-size info in real time. Geofencing can monitor and message employees at decision points to ensure rules, compliance and hazard awareness. Also, virtual reality is available to simulate situations to manage the rare, impossible, expensive and risky.
Marijuana use continues to increase as legalization spreads across the U.S. There is no accurate impairment measurement available, so it is very difficult to create employment policies and testing. It may not make sense to test any more but, rather, enhance your fitness-for-duty policies. There is a new technology that will scan an employee’s eye and tell you if he or she is fit for duty. This is a measure that you can put at the time clock to help measure impairment before the employee begins his or her shift.
Across the insurance industry, claims organizations have made significant progress in modernizing their core processing systems in the last several years. Typically, the objectives of these programs are to increase speed, improve accuracy and reduce risks in all phases of claims handling. Given that claims interactions are “moments of truth” in customer relationships, insurers have good reason to ensure that the experience for policyholders is smooth and satisfying at every step of the process.
No matter where insurers are on this continuum, robotic process automation (RPA) can help them achieve their business objectives while leveraging existing technology and boosting returns on previous and current transformation investments. In seeking the best path forward, claims leaders will want to consider:
Why robotics is well-suited for use in claims and how it complements other enabling technologies
Key components of the business case and value proposition
High-priority opportunities and common use cases
for deploying RPA
Applying the principles and techniques used by successful early adopters as they develop their own implementation approach
Why RPA? Why now?
RPA involves the use of virtual workers, or software robots, to perform business tasks similar to human users. The main appeal for insurers is the ability to handle high-volume and complex data actions at exponentially greater speed than in the past.
RPA is also notably flexible, which makes it both business-enabling and IT-friendly. It can be deployed alone or with other technologies across the claims value chain. For example, robotics can:
Automate discrete tasks or activities
Work in concert with other systems on transaction processing, data manipulation, communication and response triggering
Facilitate straight-through or “no-touch” processing, working alongside analytics tool sets and other cognitive technologies, such as machine learning and natural language processing
The cost of entry for RPA in terms of financial commitment and deployment requirements is low, compared with other technologies. There is no disruptive “rip and replace” with RPA; proofs of concepts are straightforward to launch, which helps IT and business leaders get past their “not another technology” reluctance. And many benefits can be unlocked without large-scale process re-engineering.
More than just overhauling the most routine administrative tasks, robotics creates capacity and expands the art of the possible in claims. While many assume robots simply replace human resources, RPA can – and should – be viewed as an enabler and a win-win for insurers and their workers.
RPA ROI: building the business case
A significant number of insurers have already implemented robotics, though few have done so at scale. ROI cycles for RPA can usually be measured in months rather than years. Most early adopters start with multiple functional “pilots” or proofs of concept that are completed in as little as 30 to 60 days. Broader, first-generation programs may take six to 12 months.
Increased capacity and focus on high-value work: Robotics can free knowledge workers from the burden of routine reporting, documentation and maintenance tasks. Instead, they can focus on areas where they can provide the most value, such as managing exceptions and dealing with high-risk and complex claims. A common approach is to use RPA to support straight-through processing for claims under a certain dollar threshold. RPA may also be used to handle basic data entry tasks for claims of any amount. Industry research has found that turnaround times for these types of claims may be reduced as much as 75%–85%, with 50%–70% of repetitive tasks effectively eliminated.
Higher quality and accuracy: Robots processing claims will no doubt be able to increase accuracy and reduce errors, whether related to sophisticated fraud or simple “fat-fingering,” for the vast majority of routine claims. Indeed, robots are uniquely qualified to assist quality assurance (QA) staff, given their ability to scan large quantities of data and transactions almost instantaneously. For example, RPA can help identify potentially fraudulent claims by flagging data outliers. Further, in the realm of compliance, RPA helps strengthen and streamline adherence to standard audit, risk, privacy and security policies and protocols.
Increased scalability: RPA is a natural solution for insurers that need to add temporary capacity to deal with seasonal spikes in claims activity or after catastrophes. The virtual workforce can scale to peak loads without overtime and establish 24/7 processing. For example, RPA enables insurers to increase the amount of new loss intake capabilities without a corresponding increase in first notification of loss (FNOL) processing staff. The easy scalability also makes RPA a highly useful tool for insurers exploring shared services models for claims.
Higher customer satisfaction: In identifying processes that can be automated, leaders should also look for opportunities to enrich the customer experience. Speed, accuracy, transparency and level of service are what matters most to claimants. RPA helps on all those fronts by allowing claims professionals to focus on the “art” of claims adjusting and customer experience, as opposed to the transactional aspects. RPA can also accelerate innovation programs in customer engagement and experience. Business rules can be configured directly into the robotics to align with customer expectations for personalization and timely communications.
Strategic data usage: The quality gains and capacity improvements from RPA enable claims teams to shift from simply processing data to exploiting it for more accurate and timely reporting and insight generation. In this sense, RPA can actually be an empowering force, rather than a discouraging threat, to a claims workforce.
RPA in action: where to start the journey
The use of robots and automation can take many forms in claims, including both customer-facing and back-office functions and tasks. The following represent the most common and promising use cases across the industry:
Streamlining vendor applications and estimating: Most current estimating processes require adjusters or others to rekey data from one form or system to another. Robotics along with enabling technology such as optical character recognition (OCR) can eliminate that duplicate effort by bridging the gap between claims systems, vendor apps and third-party estimating systems.
Capturing and managing claimant data: RPA can be on the receiving end of claims submissions, especially those that typically include photos from customers. Robots can ensure the right information ends up in the right systems and attached to the right claims. As such, they ensure human representatives have the information they need to move claims forward and respond to customer inquiries. Customers who prefer self-service also benefit when submitted information is more readily accessible.
Streamlining, automating and enhancing communications: Claimant communication remains a largely manual undertaking, requiring adjusters or other claims staff to initiate and, in some cases, monitor the process. RPA can help operationalize smart rules so the right letter (e.g., one required to be sent 30 days after a loss is reported) reaches the right claimant at the right time through the right channel. For instance, robots can pull data from claims submission forms and pre-populate letters that are typically housed in other systems and map distribution to customer preferences.
Scanning, indexing and converting forms and data: RPA has proven especially proficient at pulling data from standard fields on medical bills, from claimant name and address, to provide information to coding details. Standard in name only, these forms are a common source of errors. Similarly, RPA can transfer and convert data across older claims systems that may be used by individual product lines or regions to newer enterprise systems.
Validating payments: Conventional wisdom holds that 3-5% of claims payments are inaccurate, though no one knows for sure, given the difficulty and expense in auditing all claims. The key is robots’ ability to quickly and cost-effectively run QA on entire populations of forms and payments, rather than just a small sample. For example, rather than auditors discovering a $5,000 payment on a $500 settlement months after a customer has cashed the check, robots can flag the disparity beforehand. Further, they can help deliver the information and intelligence so that human analysts can investigate anomalies proactively.
Customer-facing enhancements: RPA can alleviate the need for time-consuming and costly adjuster input by supporting customer-friendly apps for capturing photos of fender-bender car accidents and submitting all claims submission forms with just a few taps and swipes. Chatbots, another automation tool easily integrated with RPA, are already handling many routine communications tasks, including notifications of settlements and customer inquiries into claim status.
Integrating other enabling technologies: RPA will become more prevalent, especially as claims groups adopt other enabling technologies. For instance, AI-powered bots will likely handle the inputs from drones conducting standard property inspections or surveying damage after catastrophic storms. Integrating RPA with machine learning and natural language processing (NLP) can enable the initiation of new claims and issue first notice of loss (FNOL) communications by scanning and analyzing unstructured communications, including emails from agents or even voice interactions. Robots will also be used widely in the real-time review of social media streams to assess claims severity and reduce fraud. RPA will receive and route advanced telematics data (including video imagery) that will be instantaneously captured during automobile accidents and downloaded from the cloud, automatically
triggering an FNOL entry.
Suggested approach and lessons learned: following the leaders
Significant numbers of insurers are already using RPA in their claims organizations. In designing the business case for robotics, claims leaders should seek an incremental approach, adopting more ambitious use cases once they have built momentum and demonstrated results through initial and targeted deployments. With RPA, there’s no need to try do too much too fast, which may be attractive for insurance executives seeking to minimize risk and disruption in their adoption of enabling technologies. Further, an incremental approach can help organizations overcome their natural wariness toward RPA in terms of its workforce impacts.
The following lessons learned come from early adopters:
Target the opportunities: In developing a business case and tangible ROI model, specific tactical questions can lead to the right strategy as well as clarify the highest priorities for near-term automation. Finding answers may require a robust assessment of current capabilities and the completion of a cost-benefit analysis, given that the candidates for automation may number into the dozens.
Engage IT early and often: To ensure a smooth implementation and integration with other systems, there are many important infrastructure, governance and security questions to address. IT leaders reluctant to deploy another technology in the claims “stack” should consider how RPA can support strategic platform upgrades and those mandated by regulatory change. Most RPA tools are product- and platform-agnostic and work with existing IT architecture.
Find the right partner: External vendors and suppliers – including insurtechs, consultants and systems integrators – will be part of the solution, so it’s important to choose wisely. Beyond technical expertise, look for those firms with deep technical and operational claims knowledge, including a clear understanding of how it affects the customer experience.
Don’t overlook the organizational factors: As with other “digital” initiatives, claims leaders must invest time and resources in education and, if necessary, evangelization regarding the use of RPA. The delicate matter of robots taking over jobs should be addressed, most likely in the context of the need to reskill claims workers, as the role will evolve to become more analytical and more focused on customer needs and the most complex claims.
The bottom line: RPA is critical to the evolving claims process
The time for adopting robotics in claims has come, due primarily to the compelling business case and imperative for claims leaders to enhance performance and contribute more value to the business. Robotics can serve as a foundation in supporting true, end-to-end automation when integrated with other advanced technologies, such as OCR, chatbots, machine learning and NLP.
Indeed, as multiple early adopters have made clear, RPA is ready to help claims organizations advance and enhance outcomes in the digital era through increased automation, higher productivity and increased capacity and strategic focus for claims professionals.
RPA is among the top enabling technologies insurers should consider adopting in claims, as well as other parts of the organization, due to:
The path to ROI
Manageable deployment requirements
Flexible use cases
For the full report on which this article is based, click here.
The Insurer of the Future will reorganize its back office using automation – but it will do so smartly. By smartly, I mean that it will figure out how and where to automate to gain the greatest commercial benefit.
Some processes will need to be transformed by using stronger, more automated, core systems.
Some processes, or sub-processes, will gain most from the use of AI/cognitive capabilities: chatbots, vocalbots, machine learning, recommendation engines etc. And any gaps might best be filled using robotic process automation (RPA) or even non-technology tools such as Lean.
There will be instances where it makes sense to use more than one of these techniques – perhaps capturing short-term efficiency gains through interim RPA of a sub-process, while a more comprehensive longer-term solution is being developed.