Artificial intelligence (AI) drives a growing share of decisions that touch every aspect of our lives, from where to take a vacation to healthcare recommendations that could affect our life expectancy. As AI’s influence grows, market research firm IDC expects spending on it to reach $98 billion in 2023, up from $38 billion in 2019. But in most applications, AI performs its magic with very little explanation for how it reached its recommendations. It’s like a student who displays an answer to a school math problem, but, when asked to show the work, simply shrugs.

This “black box” approach is one thing on fifth-grade math homework but quite another when it comes to the high-impact world of commercial insurance claims, where adjusters are often making weighty decisions affecting millions of dollars in claims each year. The stakes involved make it critical for adjusters and the carriers they work for to see AI’s reasoning both before big decisions are made and afterward so they can audit their performance and optimize business operations.

Concerns over increasingly complex AI models have fired up interest in “explainable AI” (sometimes referred to as XAI,) a growing field of AI that asks for AI to show its work. There are a lot of definitions of explainable AI, and it’s a rapidly growing niche — and a frequent subject of conversation with our clients. 

At a basic level, explainable AI describes how the algorithm arrived at the recommendation, often in the form of a list of factors that it considered and percentages that describe the degree that each factor contributed to the decision. The user can then evaluate the inputs that drive the output and decide on the degree to which it trusts the output.

Transparency and Accountability

This "show your work" approach has three basic benefits. For starters, it creates accountability for those managing the model. Transparency encourages the model’s creators to consider how users will react to its recommendation, think more deeply about them and prepare for eventual feedback. The result is often a better model.

Greater Follow-Through

The second benefit is that the AI recommendation is acted on more often. Explained results tend to give the user confidence to follow through on the model’s recommendation. Greater follow-through drives higher impact, which can lead to increased investment in new models.

Encourages Human Input

The third positive outcome is that explainable AI welcomes human engagement. Operators who understand the factors leading to the recommendation can contribute their own expertise to the final decision — for example, upweighting a factor that their own experience indicates is critical in the particular case.

How Explainable AI Works in Workers' Comp Claims

Now let’s take a look at how explainable AI can dramatically change the game in workers' compensation claims.

Workers comp injuries and the resulting medical, legal and administrative expenses cost insurers over $70 billion each year and employers well over $100 billion — and affect the lives of millions of workers who file claims. Yet a dedicated crew of fewer than 40,000 adjusters across the industry is handling upward of 3 million workers' comp claims in the U.S., often armed with surprisingly basic workflow software.

Enter AI, which can take the growing sea of data in workers' comp claims and generate increasingly accurate predictions about things such as the likely cost of the claim, the effectiveness of providers treating the injury and the likelihood of litigation.

See also: Stop Being Scared of Artificial Intelligence

Critical to the application of AI to any claim is that the adjuster managing the claim see it, believe it and act on it — and do so early enough in the claim to have an impact on its trajectory.

Adjusters can now monitor claim dashboards that show them the projected cost and medical severity of a claim, and the weighted factors that drive those predictions, based on:

• the attributes of the claimant,
• the injury, and
• the path of similar claims in the past

Adjusters can also see the likelihood of whether the claimant will engage an attorney — an event that can increase the cost of the claim by 4x or more in catastrophic claims.

Let’s say a claimant injured a knee but also suffers from rheumatoid arthritis, which merits a specific regimen of medication and physical therapy.

If adjusters viewed an overall cost estimate that took the arthritis into account but didn’t call it out specifically, they may think the score is too high and simply discount it or spend time generating their own estimates.

But by looking at the score components, they can now see this complicating factor clearly, know to focus more time on this case and potentially engage a trained nurse to advise them. Adjusters can also use AI to help locate a specific healthcare provider with expertise in rheumatoid arthritis, where the claimant can get more targeted treatment for a condition.

The result is likely to be:

• more effective care,
• a faster recovery time, and
• cost savings for the insurer, the claimant and the employer

Explainable AI can also show what might be missing from a prediction. One score may indicate that the risk of attorney involvement is low. Based on the listed factors, including location, age and injury type, this could be a reasonable conclusion.

But the adjuster might see something missing. They adjuster might have picked up a concern from the claimant that he may be let go at work. Knowing that fear of termination can lead to attorney engagement, the adjuster can know to invest more time with this particular claimant, allay some concerns and thus lower the risk the claimant will engage an attorney.

Driving Outcomes Across the Company

Beyond enhancing outcomes on a specific case, these examples show how explainable AI can help the organization optimize outcomes across all claims. Risk managers, for example, can evaluate how the team generally follows up on cases where risk of attorney engagement is high and put in place new practices and training to address the risk more effectively. Care network managers can ensure they bring in new providers that help address emerging trends in care.

By monitoring follow-up actions and enabling adjusters to provide feedback on specific scores and recommendations, companies can create a cycle of improvement that leads to better models, more feedback and still more fine-tuning — creating a conversation between AI and adjusters that ultimately transforms workers' compensation.

See also: The Future Isn’t Just for Insurtech

Workers' comp, though, is just one area poised to benefit from explainable AI. Models that show their work are being adopted across finance, health, technology sectors and beyond.

Explainable AI can be the next step that increases user confidence, accelerates adoption and helps turn the vision of AI into real breakthroughs for businesses, consumers and society.

As first published in Techopedia.

While what we see as the fundamentals and benefits of becoming an "analytical insurer" haven’t changed, being one is even more important now because of COVID-19 and its far-reaching economic impacts.

Defining the "analytical insurer"

When talking about analytical insurers, we are first referring to companies that have embedded three key characteristics in their business: a reliance on data and an intolerance of anecdotes in making decisions; the effective compilation of data to present a single source of the facts; and the ability of all decision makers to access granular insight at the point of making a decision. From those foundations, some insurers are moving on to invest in areas that we group under three umbrella sets of capabilities:

• Active portfolio management, and specifically scenario modeling
• Intelligent intervention
• Digital enabled distribution

The incentives for pursuing these attributes nearly always boils down to a handful of drivers – greater agility, rapid speed to market and accuracy of decision making, all delivered at lower cost. The insurers are reducing the analyze-decide-deploy cycle of decision making from weeks and months to days, or hours in some cases - resulting in stronger market positioning, more competitive pricing, slicker operations, increased confidence, cost reductions and a much-improved ability to adapt to changing markets.

As more companies have been persuaded to invest in the benefits over recent years, competition has continued to fuel an analytics arms race. The exceptional economic and market circumstances that COVID-19 is creating only seem likely to raise the stakes, given the likely continuing impact on premiums, business mix, profitability, resources and working practices, not to mention customer experiences that may never revert fully back to their pre-pandemic nature.

The COVID-19 effect: Consider the dilemma facing hospitality or commercial property insurers. An insurer’s hospitality clients are essentially economically inactive, with the prospect that some will never recover. At the other extreme, some manufacturing plants are working flat out in ways that were never anticipated, potentially raising the risk of things like electrical fires or accidents involving tired employees. Understanding the change in both exposure and underlying risk of a given situation is vital at both case and portfolio level. Being able to scenario model differing lockdown and economic outcomes is key to successfully navigating the post-COVID risk landscape.

That’s not to say that COVID-19 is a signal for kneejerk reactions from insurers. Importantly, responding to the short-term pressures and realities that the virus brings to insurers can be compatible with longer-term ambitions linked to agility and pace of operations. For example, enhancing understanding of your portfolio is going to be just as important to insurers’ longer-term fortunes as it is in the short term, and the same applies to most aspects of capitalizing on the opportunities to build from a stronger analytical base.

Here are a few thoughts on how stronger analytics can assist insurers through the COVID-19 crisis, but also create building blocks for longer-term business benefits:

Active portfolio management and scenario modeling 

Going back to our hospitality and manufacturing examples, the uncertainty of COVID-19 and the potential new normal it will create could potentially decimate some portfolios and the basis on which they’re priced. 

More granular policy information makes ground-up scenario building possible, putting some meaningful number ranges on observed and anticipated trends, and teeing up a whole range of things, such as evaluating what portfolios will suffer most, or even disappear. 

See also: How Coronavirus Is Cutting Connections

The recent work we’ve been doing with the Lloyd’s and London market on active portfolio management demonstrates, however, that this is anything but a COVID-19-related issue; the issue is widely seen as critical to longer-term performance and profitability.

Equally, the COVID outbreak has vividly highlighted the opportunity to derive benefits from modeling more widely – say, moving from claims cost to more sector-based analysis using rich exposure data within pricing systems to look at what companies want to do and need to do in their portfolio mix. 

The ability to rapidly test hypotheses, and deliver against options, and then monitor and change tack if necessary has already become a backbone of dynamic pricing in personal lines. Real-time scenario modeling can be a similar enabler for underwriting, pricing and claims professionals in the commercial, life and health sectors.

Intelligent intervention

Whether it’s in underwriting or claims, the objective of intelligent intervention should be to deploy the right resources to the situation at hand. This could mean completely automating a process that is relatively straightforward or using experienced teams where complex judgment is needed. Whether adopting a low-touch, volume approach driven from portfolio data or making sure subject matter experts have the right insight available at the right time to make an informed decision, insurers' data assets make this possible. 

The intelligence comes from deploying a more granular approach and, where appropriate, predictive models to support routing and evaluation decisions. Using large loss propensity models to optimize survey and risk appetite decisions and using conversion data insight to prioritize underwriting activity are simple examples of this. 

From an automation point of view, it could be about adding granularity to feed a company’s level of automatic underwriting appetite and claims handling. Some insurers use relatively simple decision rules, such as that they’ll automate a risk if it has fewer than 10 employees, or if a claim is of a certain value. Adding additional decision layers (e.g. trade, geography, portfolio context, trust indices, etc.) refines the decision process and allows the safe expansion of automated approaches and lowers costs. At the same time, you get the most from your underwriters and claims experts by allowing them to use their expertise and add value in more complex, individual cases.

The ability to flex the mix between technology and human input is also highly desirable. For example, if a pandemic were to affect a significant proportion of the team, it would be possible to expand the automated or self-service footprint to bridge the gap. Such flexibility can also provide short- or long-term help in areas such as product simplification and cost management.

Digitally enabled distribution

One thing COVID-19 has done is shine a light on organisztions that are better or worse at interacting digitally with concerned customers. In the process, digital capability has become more a matter of reputation as well as a factor in general cost of doing business and customer experience.

Yet, the digital component is only the tip of the iceberg. Below that there are a lot of hidden but hard-working data assets, supporting applications such as products broken into components, the ability to manage channel conflict and active management of cross subsidies, not to mention addressing the widespread challenges of integrating legacy platforms. 

The benefits of getting the beneath the waterline on digital infrastructure right are already considerable, and growing outside the personal lines market when Lloyd’s is creating its digital trading platform, when self-service claims operations are making steady inroads, when initiatives are underway to allow brokers to simplify the binding process and when new digital distribution opportunities, perhaps where insurance is part of something else, increase.

See also: COVID-19: Technology, Investment, Innovation

Building for the future

At present, it is hard to understand the implications of the new normal, but foundational analytics capabilities should help insurers to not only better navigate that uncertainty but leave them better-equipped for the longer-term fallout and continuing market transition. As part of an insurance future that will inevitably demand more operational flexibility and nimbleness, with digital platforms coming more to the fore, data and analytics and the wherewithal to use them effectively will mark out analytical insurers from the crowd.

The options for digital communications keep expanding. Insurers' mobile interactions with prospects, producers and policyholders have become common, while methods like e-mail and web portals are extensively used. Now, there is a whole new world of messaging platforms, chatbots, business texting, voice assistants and more.

All of these methods are in widespread use in the world today, but not necessarily in insurance. Which methods should insurers employ, for which types of interactions and for which constituents? 

These are important questions because many insurers have expended considerable effort and money to implement various newer communication technologies only to find that the take-up was low. There are no magic answers, but the key to success lies in taking an outside-in approach.

Traditionally, system have been designed from an inside-out approach – taking into consideration the organization, products, IT systems and channels to reach out to external parties. These are critical factors, to be sure. But the better approach is to lead with an understanding of customer needs, customer journeys and the value that customers place on specific capabilities.

This requires more than just asking customers what they want. Whether the party receiving the communication is a prospect, producer, policyholder or even an employee, it is best to gain a more thorough understanding of segments, relationships and needs.

During our recent Digital Communications Virtual Event Experience, SMA asked insurers about their interests and objectives for digital communications, with nine possible responses. The top two choices were overwhelmingly 1) that digital communications are a vital part of the overall digital transformation strategy (83%) and 2) that digital communications will improve the customer experience (75%). Forty percent said reducing internal operational expenses was a key goal. Surprisingly, expanding capabilities for policyholders was way down the list, and expanding agent capabilities was even lower.

Incorporating new communications into the overall digital transformation and improving the customer experience are admirable goals. But it seems to me that, to achieve those goals, it is critical to provide agents and policyholders with new capabilities.

This doesn’t mean just throwing out a new option like a chatbot because others are doing it, and because it seems like a good idea. Decisions should be made in the context of an overall assessment of agent and customer needs.

Insights from three lenses should be used to inform the decisions on specific technologies and use cases. First, look at what interaction methods people are actually using today and throughout the lifecycle. This needs to be done in the context of each segment. Second, do extensive research to determine what new modes people would value for various types of transactions and interactions. Third, evaluate what others in the industry are doing – not just what capabilities they have released but what kind of success they have had (to the extent possible).

See also: The Missing Tool for Cyber Resilience

Finally, be sure to build in flexible configuration capabilities to enable individual users to customize their communication preferences. In the increasingly digital world, placing an emphasis on providing a rich set of communications options is an important ingredient in improving experiences, which leads to both top line growth and profitability.

I’ve posted previously on the implications of COVID-19 for insurers’ business models and for insurance products and services. And my survey on changed priorities in the wake of the pandemic showed that insurers feel they have much more work to do on both workforce flexibility and new or revised customer communication and servicing channels.

It seems timely, therefore, to provide a few thoughts on:

1. The steps an insurer can take to re-design its operating model to meet its new priorities; and
2. What the new insurance target operating model might look like.

This article covers the first point, and a future article will address the second.

Definitions

First, a couple of quick definitions. An operating model is a simplified depiction or visualization (a model) of how the insurer operates to deliver on its business objectives. It is both narrower and more granular than the insurer’s business model. Unless it’s a start-up, the insurer will already have a current operating model. Its design for a better operating model for its future is known as its target operating model (TOM).

Scope

Unfortunately, there’s no commonly agreed set of dimensions for a TOM.

My own view is that, at a minimum, a TOM needs to consider:

• Major Business Processes
• People Organization
• Key Technologies
• Locations
• Governance

This list can be expanded, when appropriate, to include additional dimensions such as:

• Customer Journeys
• Management Information Requirements
• Culture

Approach

At its simplest, the operating model can be re-designed using a three-step approach.

In the Understand phase, the insurer first needs to establish the scope of the target operating model it wishes to develop, selecting from the list of parameters in the Scope section above. The insurer should also agree on the templates it is going to use to document its current and future models.

In addition, the insurer needs to understand and agree on its value chain. This is important because the value chain captures, in simple terms, what the TOM will be required to deliver.

See also: 7 Business Models of the Future for Insurers

And the primary and support activities in the value chain model also provide a key underpinning for the current and target operating models, because we can structure those models to show how each element of the value chain is currently delivered, and will be delivered in the future.

A typical insurance value chain (which, at this level of abstraction, covers both P&C and life) appears below.

Once the value chain is agreed on, the insurer should then document the current operating model and (through document reviews, interviews or workshops) establish the challenges arising from the current model.

Some of those challenges may well have sparked the project in the first place. The review might have started, for example, to address a cost problem. But even where the primary challenge is clear, it would be a waste not to consider other difficulties (such as friction points in the customer or intermediary experience) that might also be resolved through a new operating model.

The Analyze phase focuses on understanding the challenges in more detail and considering the ways in which a new TOM could resolve them. In the example I’ve just given, that would require figuring out what types of changes in the operating models (the levers) could be used to address the cost and customer experience issues identified.

It’s possible to jump straight from these levers to potential options for the TOM design. But, in my experience, the range of options available is so wide that a useful interim step is to agree on a series of high-level design principles that the solution must comply with. Examples might be that, “All verbal customer interactions must take place in the customer’s country of residence” or “All locations should use the same core IT systems.”

The Re-Design phase refines the options down to a single TOM, documented using the agreed templates. Of course, this isn’t just a desk-based exercise, as buy-in to the result is likely to be required from multiple stakeholders. The insurer will need a process that involves those stakeholders in the decision-making, both to improve the decisions themselves and to harness stakeholder commitment to the forthcoming transformation.

Often, however, the "target" operating model is not enough. Although it’s the target, it might involve such radical change that it can’t be fully implemented in an acceptably short time. If that’s the case, the insurer may also need one or more interim operating models through which it will pass along the way.

Whether any interim models are required, the final step in the Re-Design phase is to set out the road map for delivering the new operating ,odel(s) and mobilize the transformation program.

See also: How CISOs Are Responding to COVID

Following these steps will enable an insurer to resolve its operational challenges and lay the foundations for future success.

In Part 2, I’ll offer my thoughts on what the new TOM for an insurer might look like.

This article originally ran here, at Insurance Journal.

Insurtech was once the Wild West of the insurance industry. Many of insurtech’s early players came from outside insurance after observing the industry struggle to deliver what was, in their view, a competitive customer experience.

Led by ambitious entrepreneurs from outside insurance, backed by Silicon Valley and focused on industry disruption, early insurtech promised to displace incumbents and usher in a new era of insurance offerings and tech-driven solutions.

Nearly 10 years since its inception, the reality of insurtech has evolved.

The messaging about supplanting industry giants is gone. In its place is a more collaborative environment led by insurance industry leaders partnering with tech solution providers. The simple reality is that technology cannot do everything. The integration of experienced insurance professionals and tech is needed to manage across the insurance value chain.

There are powerful drivers of change toward greater automation: insurance professionals aging out of the industry, consumer expectations changing, the transformation of risk itself through the Internet of Things, the continued fragmentation of the industry and legacy systems that don’t talk to each other. Startups and incumbents alike are embracing these challenges through innovative methods designed to drive change across the value chain. Customer journey mapping, design thinking, lean process mapping and intelligent automation all have become increasingly part of the industry’s response to evolving customer service needs.

The new promise — the modern concept of insurtech — is the embrace of a strategy driven by collaboration and innovation rather than disruption.

The Era of M&A Is Here

Currently, insurtech is creating buzz through mergers and acquisitions, further integrating innovative technologies with insurance industry leaders.

Last year’s acquisition of Indio Technologies by Applied Systems is one such example. Applied saw the acquisition as an opportunity to bring Indio’s digitized commercial insurance application and renewal process to Applied’s agency management system, Epic, which serves thousands of agency and brokerage customers.

According to Applied CEO Taylor Rhodes, the integration of Indio reduced double entry for customers at the point of renewal or application within the company’s Epic system. It also allowed for a more productive application of Applied personnel elsewhere in the renewal and application process while improving customer experience.

Another example of this M&A era is the 2017 deal between Vertafore and RiskMatch. The latter is a business intelligence and analytics company serving insurance brokers and carriers. The deal allowed Vertafore, an insurance technology firm, to better compete with competitors like Applied Systems for analytics and risk placement services by substantially enhancing Vertafore’s data and market insights to improve efficiency and profitability.

See also: 5 Hurdles to Insurtech Success

In both examples, as seen elsewhere across the industry, standalone technology solution companies are either being acquired or are partnering with industry leaders to apply those tech solutions to operational capabilities with existing reach into the insurance space in an effort to reduce complexity, create efficiencies and maximize the productivity of insurance professionals. And the numbers back up this assertion.

Deloitte Center for Financial Services reported in September that insurtech investments for the first half of 2019 were on the rise at $2.2 billion, while the number of insurtech startups had declined. (Editor’s Note: In a recent update, Deloitte reported an increased figure of $3.3 billion.) Additional examples of big carriers investing in digital platforms that support their core and ancillary business markets are ample, such as Chubb’s 2018 investment in Bunker, Munich Re’s 2016 partnership with Slice Labs and Prudential’s $2.35 billion acquisition of Assurance IQ. There is a veritable laundry list of insurance leaders investing in or partnering with technology startups to apply digital solutions to their established processes to maximize the customer experience.

The Challenge

The reality is simple: Technology alone will not fully eliminate the challenges that surround key processes like claims, which is the foremost area the insurance industry is moving to address.

The combination of innovative technology solutions and startups with more established industry players offers exciting promise for the industry — assuming we don’t lose sight of the need to ensure that a solution that serves humans must also be driven and populated by humans.

Put simply, there is no general artificial intelligence (AI).

Algorithms, bots and other technologies are not end-to-end solutions. These tools are highly localized and offer a narrow focus.

As part of a process, they offer greater efficiency and a streamlined manner to consumer data analytics. However, as the insurance industry’s past has proven, technology alone is not a solution. In fact, adoption of technology without an underlying strategy can create tremendous inefficiency to insurance processes, adding complexity and creating more costly issues for companies in terms of time, personnel and customer service.

There is tremendous emotion around claims and losses. Technology can help in managing the claims process, but humans with customer service skills will remain a critical part of the process, allowing for insight, empathy and creative thinking that no algorithm can yet replicate.

With a hard market on the horizon, the complexity of applications and claims will grow. As this more complex situation evolves, standalone AI solutions will likely fail to adapt, while integrated technology solutions driven and overseen by insurance professionals who have lived through prior hard markets and know what to expect can help best guide their companies and their customer service experiences.

Advice for the Future

Companies that will succeed in this new industry landscape will be those whose leaders think big but start small. The temptation is to chase the big, shiny objects. This was an early mistake of many insurtech startups. The reality is that so much can be gained from small, incremental improvements.

Start by taking a close look at existing processes through the eyes of the customer. Design thinking and customer journey mapping ought to be part of the daily conversation of management looking to insurtech for solutions. Insurtech is the culmination of a lot of these things. Look outside of the insurance industry for inspiration.

Look for companies that can help alleviate some of the more complex pieces of digital transformation. Some of the most successful advances in insurtech to date have come from organizations that took an honest look at their tech and innovation deficits and identified an effective partner to maximize what they do best with new thinking and processes. By freeing time to focus on the core business pieces, they seek to drive growth and success.

See also: A Quarantine Dispatch on the Insurtech Trio

As we move into a harder market, additional burdens will be placed on agents and carriers to manage submission flow, markets will become more restrictive and submission volume will go up, along with exceptions and exclusions. Insurtech alone cannot solve for these realities.

In the hard market to come, there will be a premium on customer service and customer satisfaction. Technology can certainly help mitigate some of the burden agents and carriers will face. Addressing coverage needs and solving claims challenges, however, is a big part of what will be needed.

This will require both a tech-based and a human-centric solution.

Confronted with a new, remote working world, customer service programs have undergone enormous transformations to processes and tools. At the same time, the programs have handled huge increases in customer inquiries, which as of June 2020 are up an average of 48% across business sectors. For the insurance industry, in particular, meeting increased customer demands with excellent service requires the right combination of technology and training. By implementing more automated and virtual processes, insurance companies can set remote teams up for success. 

Ensuring representatives are prepared for the new environment

The pandemic has demonstrated that "virtualizing" the customer experience (CX) is no longer an option but a necessity. Insurance companies need to equip and train representatives to use necessary technology while at home. Companies should lend headsets, laptops and other equipment to employees. Maintaining an excellent CX program may also require new digital technologies—such as chat and video— which representatives need to be fully proficient in. Keep in mind, a well-trained representative can better personalize the customer experience, resolving issues faster and with better customer satisfaction.

Meeting your customers on the right channel at the right time

Customer experience often acts as the differentiator when it comes to the crowded markets of health, home, auto and travel insurance. Now that teams are working off-site and traditional support interactions have shifted to be primarily virtual, it’s imperative to use every customer inquiry as an opportunity to strengthen their loyalty. A successful relationship relies on open communication, and that means the ability for the policy holder to reach the provider when needed. Insurance companies, especially ones with a global footprint in different time zones, can no longer rely on nine-to-five service hours. Their clientele, when faced with an unexpected catastrophe, will reach out expecting fast and accessible support. 

As demand for 24/7 service grows, customers are turning toward varying platforms such as intermediaries, service centers or digital channels to reach their insurers. Since the end of February, there has been a global increase in digital channels being used to contact customer service, with WhatsApp up 148%, texting up 26% and direct messaging over Facebook and Twitter up by 21%. These shifts reinforce the need for insurance companies to virtualize their customer service and meet customers on increasingly diverse channels.  

See also: Why Customer Journey Mapping Is Crucial

With new communication forms on social media and online, it’s critical to meet customers on the platforms that are comfortable and accessible for them. For insurance companies, this ease of access comes in the form of offering personalized service supported across communication channels. If a policy holder poses a claim question via an online customer service chat, the information shared should be reflected in the person's online account and accessible across all other channels. It’s a matter of ensuring that customers don’t need to repeat their question or information and that they get the same quality of response across channels. 

Relying on AI-based technology 

For many years, a digitized customer relationship has been key for creating a successful CX journey in the insurance world. If you have the technology, use it. AI-based technology has been proven to address customer inquiries more rapidly. If simple customer requests around account updates, such as resetting a password, are handled by an automated system, representatives are free to spend the bulk of their time addressing more complex problems. This simple redirection of workflow allows resources to be redistributed in a more efficient and effective way. 

While insurance CX teams are no stranger to chatbots and other technologies, the newly remote environment requires their increased use to maintain policy holder satisfaction and loyalty. Insurance companies should be evaluating which tools can best support virtualized customer service teams by considering the following: 

• Predicting problems: Chatbots and AI can help you anticipate customer needs and dissatisfaction. 
• Helping your workforce: Representatives are dealing with a higher volume of complex interactions. Can tools such as text-based messaging help ease their workloads by quickly handling simpler tasks? 
• Connecting with customers: Prospective policy holders are increasingly seeking insurers that offer a more personalized experience. Can adopting new technology help you deliver more tailored information? 

Final thoughts

Insurance companies have the opportunity to lead in the new world of remote customer service – one in which increased virtualization enables better experiences with insurance. By virtualizing the customer experience, insurers can make service and support accessible across diverse channels. For this to happen, representatives must be enabled to use the right tools and rely on AI-based technology whenever possible. This game-changing combination of technology and training will give representatives the support they need to deliver excellent customer service across channels. 

If necessity is the mother of invention, the insurance industry can proudly say that, in the face of COVID-19, necessity also became the mother of innovation. 

Kudos to the Insurance Industry

From repositioning hundreds of thousands of employees from offices to a fully effective remote work-from-home format in less than a month to quickly implementing technologies enabling them to continue to offer products, services and support, barely missing a beat, the industry rose to the challenge.

These accomplishments did not just happen. It took decisive leadership, starting in the C-suites of the industry, and focused, well-articulated action plans that flowed down into middle management and out to the front lines.  It also took increased investment, some of which was unexpected and unbudgeted. Marshaling the capital required a compelling justification, and in business there is no more convincing target than results and outcomes, which are measured by a variety of metrics beyond just financial results, including customer experience and satisfaction, retention, market share growth, reputation management, credibility and competitive strength. 

More Work to Do

But this transformation is far from over and will no doubt continue long after the pandemic recedes. There is a sense of urgency not evident prior to March 2020. Events over the past few months have forced C-suite leaders to realize that their digital transformation efforts need to be expanded and accelerated to light speed. It is now broadly accepted that a comprehensive digital strategy and implementation plan is critical to carriers that are serious about becoming digital insurers. 

Immediate, Enterprise-Wide Digitization Now Job #1  

Unfortunately, not all carriers will succeed in this journey. The survivors will be innovative, nimble and fiercely customer-centric. They will be committed to enterprise-wide conversion to digitization. Investments in mission-critical technology will need to be prioritized. Speed to market will be mandatory. The hallmarks of successful carriers will include leveraging high-powered transformational technologies, including IoT, telematics, sensors and more. These same market leaders will learn to find and engage with traditionally unreachable customers and convert them into their brand ambassadors. And these leaders will adopt digital technology as a strategic priority and achieve automation efficiency by arming their companies with the very latest in client communications, finance processes, digital and touchless claims processes and digital marketing.

See also: COVID-19: Technology, Investment, Innovation

According to Reuters Events’ Connected Insurance 2020 Report, in 2019, 63% of insurance carriers rated the development of new digital products and services as a key expected outcome over the next 12 months. In a post-pandemic world, it is likely that figure will be nearer 100%.

We need to take every opportunity to listen and learn from our industry leaders, who understand what it takes to survive this challenging period and emerge even stronger.

This theme will be explored in depth in the Reuters Events webinar titled “CNA, Nationwide and Quadient: A C-Suite Take on Results Driven Technology” on Sept. 3, 2020. Register here. This webinar is being run in conjunction with The Future of Insurance USA 2020, which takes place online Nov. 16–18.

Since the stay-at-home orders first started in March, chief information security officers (CISOs) have been sharing both their horror stories and how they’ve shifted priorities to keep their companies safe. These CISOs work in a wide variety of companies, and the anecdotes we’ve been hearing run the gamut. 

Changes are happening in how CISOs make decisions, so, in line with Arceo’s mission of driving comprehensive cybersecurity management, we wanted to look at how the rapid expansion of remote work is affecting cybersecurity business decisions directly.

We collected one of the first sets of quantitative data on how CISOs’ priorities have changed since many businesses started moving to work from home. With our research partner, Wakefield, we surveyed 250 CISOs at companies with $250 million to $2 billion in annual revenue. We asked them about their current and changing approach to cybersecurity risk management. Below is a synopsis of some of the results we found most interesting; the full report is available on our website.

Many CISOs say they need more options and coverage for cybersecurity insurance. However, they aren’t getting the coverage they need or the post-breach services required to recover from certain incidents. Almost four-in-five (77%) reported that there are incidents they feel they need coverage for, but that they are unable to get it. 

Additionally, nearly all (96%) of the CISOs surveyed want additional coverage for the increased vulnerabilities resulting from the work-from-home surge. This means that almost every CISO out there is worried -- likely because the security practices followed when working remotely are laxer than those followed in the office, leading to a higher risk of attack. In fact, over 40% of CISOs said that cloud usage (49%), personal devices usage (45%) and unvetted apps or platforms (41%) usage posed the biggest threats during this work-from-home period.

The overwhelming majority (88%) of CISOs are not completely satisfied with the performance of their company’s primary insurance brokerage. Additionally, CISOs want more help when they need it most. Nearly all CISOs (98%) want additional support from their cyber insurance provider after a serious incident. 

Nearly half of all CISOs (48%) report they have experienced a security breach. Insurers and brokers need to step up and are likely in a position to play a bigger role in the prevention and the aftermath of a breach because nine in 10 CISOs are open to purchasing cybersecurity tools along with cyber insurance from the same company. 

See also: COVID-19: The Long Slog Ahead

Now more than ever it seems CISOs seem to be concerned about disruption to continuity, which is a greater risk as staff works from home. More than half of CISOs want cyber insurance to cover business email compromise (56%), loss of electronic data (55%), cyber extortion (53%) and ransomware (52%). 

CISOs recognize they need more influence, and nearly all CISOs (97%) agree that the opportunity to interact with the board is crucial to their success as a CISO. 

Check out the full “Quantitative Analysis of Unmet Insurance Needs and Cyber Security Tools Among CISOs” report to find out more about how CISOs view the changing landscape and how cyber insurance needs to adjust to fit their needs.

Although 2020 kept dishing out pain last week -- the pandemic, the economic crisis, the protests and counter-protests on racism, our crazy politics and even wildfires and hurricanes -- one event wasn't as absolutely awful as it could have been.

It was still awful: Hurricane Laura caused billions of dollars of damage and killed 14 people in Louisiana and Texas. But the hurricane didn't cause nearly as much damage as initially feared.

That suggests that people are starting to take the sorts of precautions that will be increasingly important as we have to adapt to the changing climate. Those precautionary principles also represent a key opportunity in front of the insurance industry: to go from indemnifying customers after a loss to helping them avoid those losses in the first place.

Now, some of what happened with Hurricane Laura was just good fortune. The hurricane pretty much threaded the needle between New Orleans and Houston, so it hit mostly rural areas, not the dense populations and expensive properties in those metropolises. The hurricane moved inland quickly, rather than sitting over an area and dumping tens of inches of rain, as Hurricane Harvey did to Houston in 2017. The storm surge, predicted to be as high as 20 feet, peaked at about 11 feet -- still an almost inconceivable wall of water washing inland, of course.

But, as this New York Times article details, people mitigated the damage because they learned lessons from Hurricane Rita, which hit Louisiana and Texas in 2005. Rita killed 120 people and did some $25 billion in damage (measured in today's dollars), including business interruption. Because of Rita, building codes have become much stricter, and structures more resilient. Some houses near the coast, for instance, are now on stilts 15 feet high. Partly as a result, while Laura's winds were even stronger than Rita's when the hurricanes made landfall (150 mph vs. 130 mph), the early estimates are that Laura did about $20 billion of damage while killing those 14 unfortunate souls.

Again, the storm was a catastrophe. I grieve for those 14 people, for their families and for all those who are now having to try to knit their lives back together after suffering $20 billion -- $20 billion! -- of damage. But, assuming that the difference between Rita and Laura wasn't just 2020 finally cutting us some slack, there has been considerable improvement in the resilience of those in the hurricanes' path, and I vote for more resilience, with the insurance industry helping as much as possible.

Technology should help. With Laura, the National Hurricane Center got the time of landfall precisely right, more than 3 1/2 days in advance, and was only a mile off in its prediction of the location of landfall. Predictions will only get better, giving people more time to evacuate or find shelter.

The industry can also mine its data for insights that will help people prepare better. For instance, of the 14 people who died in Hurricane Laura, more than half succumbed to carbon monoxide poisoning emitted by emergency generators. With that pattern identified, carbon monoxide poisoning seems like a danger that can be reduced or even eliminated through better inspection or education for those using generators.

Government will need to play a role, too, as climate change intensifies storms and raises the level of the oceans, endangering coastal communities. The Federal Emergency Management Agency (FEMA) has already funded "buyouts" of 43,000 homeowners in the U.S. who chose to relocate rather than continue to fight nature in places such as Isle de Jean Charles, in Louisiana, which has been 98% swallowed by the Gulf of Mexico.

We're still not out of the woods even on this year's hurricane season, let alone on everything else that 2020 is throwing at us, but maybe we can take a lesson from Rita and Laura. Maybe we can learn how to be even smarter and more resilient, and maybe the insurance industry can lead the way.

Stay safe.

Paul

P.S. Here are the six articles I'd like to highlight from the past week:

3 Big Opportunities From AI and ML

Machine learning can speed underwriting while reducing costs and providing valuable information on why certain proposals fail.

How CISOs Are Responding to COVID

77% of chief information security officers identified incidents that they feel they need cyber coverage for and report being unable to get it.

COVID-19: What Buyers Want Now

Insurers must examine customer pain points and life changes and accelerate digital adoption.

New Sense of Urgency on Going Digital

Events have forced C-suite leaders to realize that their digital transformation efforts need to be expanded and accelerated to light speed.

The Missing Tool for Cyber Resilience

With AI able to assess cyber risk, cyber insurance no longer has to be a long, drawn-out and complicated process.

Payments at the Speed of Light

Insurers and solution providers are making significant advancements to speed delivery of payments and expand digital payment options.