The global insurance industry is making a slow but remarkable recovery from the COVID-19 pandemic. 2022 is expected to continue this momentum, facilitated by trends in insurance technology that will dominate in the years to come. Let's review.

Applied Artificial Intelligence

At present, very few insurance carriers are harnessing AI to its full potential. Regardless, the pockets where insurers have been successful in implementing AI have raked in significant ROI in various forms. For instance, 65% of insurance agencies believe that AI investments in customer experience (CX) have lived up to expectations. 49% believe that improvements in internal decision-making have likewise met expectations, and 45% say the same about innovation in products and services.

As technology matures, AI is bound to diversify and find deeper and more meaningful applications to augment business capabilities. As a result, it will continue to reengineer algorithms and core processes to make insurance more predictive and intuitive. So, whether businesses are looking to tailor their services or predict the risk or probability of an event, AI solutions can step right in and bridge projections with reality.

Process Automation and Virtualization

Robotic process automation (RPA), as we know it today, has evolved from a series of technologies such as industrial bots to machine language-driven assistants. Currently, these operate as low-code, rule-based bots targeted to perform routine, repetitive tasks.

These bots can integrate seamlessly with legacy systems and streamline everyday business processes. To achieve the latter, RPA can complement any individualistic element of insurance business operation, such as underwriting, policy management, claims and regulatory compliance. Alternatively, it can spearhead end-to-end process automation requiring minimal human intervention. 

By patching together isolated systems and optimizing business processes, insurance agencies can foster efficiency at the grassroots level. Plus, RPA executes change in minimal time, which generates immediate value and holds a certain amount of elasticity even in the face of disruption.

See also: Workers Comp Trends for Technology in 2021

Blockchain and Distributed Ledger

Insurance technology expands its reach to subsume cybersecurity through the introduction of blockchain and distributed ledger technology (DLT) to cater to trends in insurance technology. While the technologies are still up for debate to some extent, blockchain and DLT introduce greater security, transparency and immutability to operations.

Insurance service providers can use blockchain technology to cut down on administrative costs, verify payments made by third parties and install a layer of protection from fraud. DLT can also come in handy while implementing traceability for quick audits and inspections.

According to a survey conducted by MarketsandMarkets, insurers plan to deploy such solutions primarily for:

• Identity management and fraud detection
• Smart contracts
• Payments
• Governance, risk and compliance management
• Claim managements

Mobility Solutions

Insurance tech gives birth to a distributed infrastructure having a centralized database. And as companies are no longer chained to their on-premise equipment or technology, they can finally explore flexible, mobile, and next-generation options.

In this respect, cloud architecture will play a greater role in maintaining information accessibility with a high degree of modularity, as expected from such applications. In addition to centralizing data, insurers can launch agile products and maintain computational and operational scalability. 

Mobile apps will break new ground in improving CX by offering a bouquet of services -- from policy management to claims settlement -- at the customer’s fingertips. Nearly 74% of insurers are banking on mobile app-driven convenience to ramp up customer satisfaction levels, partly by making it easy for customers to contact insurers. Such apps will unlock multiple channels and entry points for data collection, which will enrich the database.

Connected Networks

The future points toward greater connectivity that goes beyond smartphones. Whether you view it from the smart home/smart devices angle or consider the case of telematics, the key piece to the puzzle lies in connected networks. As such, the Internet of Things (IoT) will continue to remain one of the most prominent trends in insurance technology. 

Insurance companies, across varying segments like life, auto, health and P&C, can harness first-hand data obtained from such networks to gain a holistic understanding of the insureds. Businesses would be laying the foundation for greater customer satisfaction, improved accuracy, better risk assessment and several other non-tangible benefits, in addition to the most obvious and quantifiable metric-- revenue.

See also: Technology and the Agent of the Future

Closing Thoughts

For 2022, we can expect the continued upswing of insurance technology, influencing core products, services and functions.

Insurance in the U.S. goes back to the mid-1700s and Benjamin Franklin. It has become one of the most essential parts of our lives and one of our most important economic industries. We depend on insurance companies and policies to protect us and our assets in times of loss and catastrophe. As it is such a critical piece of our social and economic fabric — it is also one of the most regulated and scrutinized industries — we fundamentally want and need to trust insurance.

For the most part over the centuries, consumers and businesses who purchase insurance have felt a relative transparency and obvious correlation between the relationships of risks and insurance; if you live in a flood zone or have a history of speeding tickets, insurance costs more. However, as carriers are touting proprietary advancements in big data and artificial intelligence (AI), insurance becomes more complex, and questions arise.

As society at large is challenging a lack of equity and fairness across races, genders and social statuses, insurance, too, is under scrutiny. Exactly what “big data” is being used, and how are those factors influencing model-based decisions about prices or coverage? There is an expectation to prove fairness and sometimes to “eliminate bias,” but delivering on this expectation is not so simple. In actuality, it is IMPOSSIBLE to eliminate bias from insurance. Insurance fundamentally needs to be biased; it needs to bias away from unreasonable risks to be financially feasible. Insurance can, however, put processes in place to mitigate disparate impact and unfair treatment.

So how does insurance move forward in a world not simply expecting proof of fairness but also an unrealistic expectation of eliminating bias? The solution has to come from and live within a corporate prioritization framework and a cross-functional lifecycle approach to model governance.

Prioritize Fairness as a Pillar of Corporate Governance

Data and model governance (AI governance) needs to be a C-level priority. Committing to fairness and transparency is a corporate responsibility. Managing AI risks like bias is a business problem, not just a technical problem.

Mitigation of unfair bias needs to be incorporated into compliance and risk concerns of the board and enabled through strategy and budget by the C-suite. The best strategies fit within a broader vision or plan, and, in this case, incorporating mitigation of bias aligns well with ESG or CSR efforts. As the SEC, regulators and investors demand more attention to these areas, executives have a unique opportunity to take advantage of the momentum and incorporate data and model fairness as central tenets of corporate governance. Leadership can ensure that AI governance is properly funded to deliver results and avoid the challenges of distributed ownership and budgets across the company.

Finally, it’s important to promote and celebrate these efforts externally. Show consumers and regulators evidence of your awareness and investments in building greater oversight and accountability of your organization’s use of data and modeling systems. Sharing these efforts is investing in brokering trust and confidence -- important and lasting competitive advantages.

Establish Stakeholder Alignment and Shared Lifecycle Transparency

When it comes to AI and other consequential decision systems, the technical nature of the work tends to silo the essential stakeholders from one another. A line of business owner greenlights the project. A team of data scientists and engineers develop on their own. Risk and compliance teams come in at the end to evaluate a system they’ve never seen before. Such a pattern is a recipe for bias to enter the equation unknowingly.

To combat this, companies need to invest time and effort in creating transparency across teams, not just in the decisions that their models are making once deployed but also in the human processes and human decisions that surround the model’s conception, development and deployment. Every person involved with a project should have access to the core documentation that helps them understand the goals, expected outcomes and reason that a model is the best way to solve the business problem at hand.

Once a model is in production, non-technical team members should have user-friendly ways to access, monitor and understand the decisions made by their AI and ML projects. Technologists can do much in designing their models for governance to provide more visibility and understandability of its decisions, and hiding behind the veil of the “black box” only creates more work for them in the end when they have to go back in time to explain odd or unexpected behavior from their models. Business owners should be able to evaluate system performance, know when problems of bias arise and understand the steps that were taken to identify and correct course.

See also: 3 Big Opportunities From AI and ML

Require Objective Oversight

Objective oversight and risk controls are not a new concept for your business, so continue this best practice when it comes to data and models. There needs to be a separation of duties and responsibilities between the teams who build the models and modeling systems from those functions who are responsible for managing risk and governance. The incentives are different, and so the objective motivations of mitigating risks that sit within governance functions need to be empowered and expected to oversee modeling systems. While there are technical tools being developed for data science teams to monitor, handle version control for and explain AI/ML systems, the tools are not oriented toward the non-technical, objective risk partners. The modeling team cannot, and should not, be expected to self-govern.

Thanks to the thorough approach to corporate and model governance covered above, second and third lines of defense will have intuitive and context-rich records and interfaces to discover, understand and interrogate models and the decisions the models have made for themselves. Because all of this evidence is mapped to a previously established model governance methodology, the objective governance teams can readily pass or fail adherence with policy.

Of course, this sort of objective governance and control will require front-end work and focus on collaboration, but it is an obvious and necessary approach to enhancing the fairness of systems. There’s a secondary benefit of that effort: Understanding the boundaries gives your R&D teams a much clearer path to develop systems that operate within them, thereby unlocking innovation rather than stifling it.

Perfection Is Not the Goal – Effort and Intent Are

Despite all best practices and efforts, we depend on humans to build and oversee these systems, and humans make mistakes. We will continue to have incidents and challenges managing fairness and bias with technology, but insurers can implement risk governance, transparency and objectivity with clear intent. These efforts will yield positive results and continue to cultivate trust and confidence from customers and regulators.

The job of an insurance underwriter is complex on many levels and requires a highly skilled workforce. Underwriters must possess a combination of actuarial, risk management and people skills to assess complicated policies or claims in a highly collaborative and customer-centric environment. Given that underwriting decisions involve huge cost implications, training on the job is not a viable option; these professionals must gain their experience somehow in a safe training environment, where mistakes don’t have real-world financial consequences.

Adding to the challenge are the significant technical skills needed to work with smart systems that aid in the underwriting process, and a tight talent pool generally in financial services for highly skilled employees. These combined pressures have put the lens on workforce training as a way to quickly onboard and close knowledge gaps for highly skilled employees, while keeping them engaged and invested in the job to minimize turnover.

These considerations were top of mind for the chief underwriting officer and HR managers at the Hiscox Group, a Bermuda-based global insurer with a workforce of nearly 4,000 staff across 14 countries. The company sought to hire and retain junior underwriters to help manage policies within a balanced portfolio of catastrophe-exposed, globally traded risks and less volatile retail insurance business. 

Hiscox’s novel approach in addressing this need was to engage strategic partner Attensi to create the first-ever “underwriter simulator” program of gamified learning and 3D interactive scenarios – a new approach to learning that is helping redefine what is possible for workforce training in the insurance industry.

Solving a Unique Training Need

Like other companies weighing training investment, Hiscox did not need to look far for data points to demonstrate the value: Research from LinkedIn shows 94% of employees say they would stay at a company longer if it invested in their learning and development. Furthermore, people working at companies that prioritize learning investments are 83% more likely to feel happier at their jobs.

Though Hiscox was sold on the why, the bigger question was exactly how to train this niche cohort of newly onboarded junior underwriters on the demanding skills needed to apply technical concepts throughout the underwriting cycle. This was needed to free experienced underwriters for more complex tasks as the company pursued aggressive growth targets. Hiscox set some specific educational goals that were ambitious enough to require a new approach to training that went beyond traditional online or classroom models.

See also: The Defining Factor in Underwriting Success

To begin with, junior employees needed to be brought up to speed quickly with an engaging curriculum that could teach a combination of skills needed to balance the judgment of a risk analyst and the interpersonal skills of a customer-facing financial representative. The training also had to be online and mobile – both due to COVID-19 work-from home restrictions and because many junior underwriters are digital natives with high expectations around mobile and online options.

These factors helped shape requirements around three core characteristics to guide development of the training. Hiscox and Attensi agreed that the training solution would have to be:

• Engaging through gamification and real-world scenarios. The curriculum should ideally leverage knowledge of what fascinates people about video games and incorporate those dynamics into a remote learning and training approach. And the solution should use real dialogue and lifelike office scenarios to simulate the work experience as closely as possible;
• Immersive through the use of 3D graphics and competitive challenges to drive staff to not only complete trainings but continue playing to quickly build expertise and close knowledge gaps; and
• Measurable, to reap advanced insights on the training process that go beyond a checkbox approach, allowing enhanced evaluation of employee performance and improved program efficacy.

With these requirements in mind, Hiscox and Attensi set about crafting a bespoke training solution that could fit the bill.

Creating the “Underwriter Simulator”

Attensi and Hiscox collaborated on a 3D insurance training simulator for underwriters that teaches key skills by challenging users to compete in a series of realistic and gamified scenarios via an app.

Learners were given simulated data sets for digital case studies to train around skills like account analysis, segmentation and profit improvement planning. Each case study allowed the learner to manipulate the data sets to solve the case and then deliver a custom analysis to demonstrate understanding. Multiple modules were designed to cover key areas, including equity capital, profit after tax, return on equity and net asset value per share.

Great care was taken to customize the curriculum with cross-disciplinary domain expertise from pros in game design, insurance, risk analysis, education and behavioral psychology.

To add to the realism, the simulator allows in-platform use of tools needed on the job, such as MS Excel. And, in a feature that proved highly engaging and effective, learners interacted with 3D avatars of office colleagues and stakeholders – such as brokers, chief underwriting officers and product leads – to replicate the real-world collaboration needed to conduct the underwriting process.

The results speak for themselves: Hiscox is on track to have more than 90% of the junior underwriters in the program fully trained by the end of the year, and some 85% of the participants say the training has helped them understand their jobs better by practicing in a virtual “safe” environment before working with real financial data, colleagues and customers.

In addition, many staff continue to be engaged in the competitive elements of the game – eager to repeat the training modules up to 10 times to achieve better scores and higher placements on the leaderboard. Hiscox has already used these positive outcomes as inspiration to expand the gamified, 3D simulation approach to new use cases such as sales development and internal onboarding.

See also: Underwriting in the Digital Age

Conclusion

It took aggressive growth targets and the challenge of training a unique demographic of junior underwriters as forcing functions to break new ground in workforce training for the insurance industry. In doing so, Hiscox and Attensi are helping redefine what’s possible in talent development around some of the most demanding work in financial services.

December 2021 FOCUS OF THE MONTH

Smart Home

FROM THE EDITOR

For nearly 30 years, I've been hearing about smart homes. Even before a commercial version of the internet browser was invented in the early 1990s, the rich, geeky types I dealt with in my travels at the Wall Street Journal were figuring out ways to wire their homes to ward off possible intruders. 

They'd turn lights on and off remotely to simulate being there. They'd install cameras that they could monitor from their computers -- smartphones were still a ways off even for this crowd. They'd install sensors that would alert them about any unusual activity.

What began as a sort of hobby is now going mainstream, as you can see from my interview with Matteo Carbone, who has pretty much established himself as the king of telematics, and from the smart home articles we've curated for this month's ITL Focus. 

It's still not possible to make a full-on economic argument for installing sensors everywhere to monitor for water leaks, gas leaks, intruders, etc. -- the cost of installing sensors and cameras everywhere would exceed the losses that they'd prevent. But smart home technology has declined in cost enough that many people will start investing in it for the peace of mind. And many insurers will start subsidizing the technology, both to reduce losses and to show customers that they're partners in protecting customers' well-being.

We haven't "crossed the chasm," to use the Silicon Valley term, to a true mass market, but we're well past the hobbyist phase.  

Cheers,

Paul Carroll, ITL’s Editor-in-Chief

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INTERVIEW WITH MATTEO CARBONE

As part of this month’s ITL Focus, we spoke with Matteo Carbone, founder and director of the IoT Insurance Observatory, on the intriguing opportunities that are taking shape for smart homes.

“Today, we have the same mood among insurers about the smart home, and I’m telling people not to make the same mistake that they made on personal auto telematics.”

Matteo Carbone 

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WHAT TO READ

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WHO TO KNOW

 

This paper identifies a series of events leading up to a new cause of plumbing failures in CPVC pipe. The story demonstrates how unbalanced market forces can exacerbate a problem if information is too centralized and cannot reach solution providers in time. Finally, we demonstrate how decentralized information may be superior to centralized information when confronting systemic risk exposures.  

Beginning in the mid-1990s, the EPA began publishing mold remediation documents in response to flooding events. Soon after, they published on the health impact of mold, including allergic, asthma and respiratory ailments. In the early 2000s, increased energy-efficiency certification led to buildings that were sealed tight. This increased the mold problem as moisture from appliance, humans, condensation and showers was unable to escape from the interior of buildings. Building envelope laws were passed in many states. In the mid-2000s, the EPA published Document 402-K-02-003 "A brief Guide to Mold and Moisture in Your Home." (https://www.epa.gov/mold/printable-version-brief-guide-mold-moisture-and-your-home)  

Soon, every real estate agent was giving the EPA 402-K-02-003 pamphlet out to their clients. Contractors, bankers and insurance agents began quoting from the document. M-O-L-D became the new four-letter word -- whose name shall not be uttered. Predictably, mold remediation services started popping up all over the place either as add-on to pest control business or as stand-alone national franchises. Specialized “mold sniffers” (reminding me of Ghostbusters) would come to your house to detect the presence of mold, nixing many a real estate transaction, forcing price adjustments and generally frustrating agents and sellers alike.  

Fortunately, a compound known as quaternary ammonium chloride, or “quat,” for short, had been used in commercial cleaning for several years. There are upward of 100 different formulations of quats -- each with different characteristics. Quats are the main ingredient is many household, non-bleach surface cleaners that claim to kill 99.999% of bacteria without bleach. They are also very effective on viruses, but this is generally not a listed selling point.  

As it turns out, quats are very effective at treating and inhibiting mold on both porous and non-porous surfaces. Some new construction is treated after framing, and occupied structures can be treated retroactively. Some applicators used electrostatic spray guns that would charge the mold-inhibiting compound such that droplets would repel each other, forming a mist that was electromagnetically attracted to a negatively charged surface. This attraction guaranteed nearly 100% uniform coverage of surfaces, around corners and inside every crevice. Quats proved to be cheap, safe, effective and versatile – who could ask for a better solution. So far so good, right?

Premature CPVC Failures

Chlorinated polyvinyl chloride (CPVC) is a polymer that has unrestricted approval for all domestic water, drain, vent and fire sprinkler systems in the U.S. Sometime after 2005, there was an increase in leaks and failures of CPVC pipe. These were mysterious failures involving small cracks on the exterior of a plastic pipe and progressing inward. Pipes began leaking and failing at less than half of their rated pressure loads. These types of failures are labelled “environmental stress cracking,” or ESC. ESC is the combination of load stresses applied to a plastic plus a contaminant that acts to lower the mechanical properties of the material. 

In short, quats are hydrocarbons, as is CPVC. The two compounds have an affinity to react with each other. Anything that interferes with the length and entanglement of plastic molecules will affect the strength of plastic. The CPVC would normally be able to handle pressure and heat loads, except in the presence of the contaminant. CPVC pipes exposed to quats are now beginning to fail – sometimes catastrophically.    

See also: 3 Keys to Building a Safety Culture

What does this mean for the insurance industry?

This is a classic example of systemic risk, where the solution to one problem creates another problem somewhere else in the system. External factors such as propagation of mold warnings, legislation, insurability, financing and increased real estate values amplify the problem to a fever pitch. Entrepreneurs, driven by the invisible hand of capitalism, quickly enter the pain market with little or no consideration for other systems in the home.  

Quats were the workhorse of the cleaning industry for several decades and only increased in usage since the COVID-19 pandemic for their incredible performance in making a surface inhospitable to nearly any pathogen. However, the unknown impacts of incompatible materials will also accelerate. Next to fire, water damage is the second most expensive peril that can afflict an insured building. Even if no major breach appears, widespread leaks in a plumbing system would require a complete replacement (and, ironically, mold mitigation due to the leak!), which would likely be insured due to the accidental nature of the unknown attack agent. 

Because plumbing failures are covered by insurance in a completely different risk pool, the mold/health peril and the failing water system exacerbate each other. Lawsuits, settlements and expert testimony are often not made available to the public so that there is no feedback to the service providers about the impacts on other building systems. 

As with many building materials, there is little public data to track what is failing and why failures occur and then deploy solutions to the market, due to a high degree of centralized, private or proprietary information. As a result, engineers may not be efficiently deployed to find solutions to mitigate risk outside the manufacturers' technical bulletins. Ultimately, premature failures in CPVC pipes may be due to the over-centralization of failure data.

It’s about time, volume and volatility. Any one of the three by itself could push commercial companies to improve underwriting automation, but all three working together are pulling insurance executives out of their comfort zones and into action. At one time, underwriting automation was simply about growth, competition and consistency. Can we beat the competitor next door with our time to quote? Can we capture more business through better underwriter/agent/broker relationships? Can we help the underwriter in the next office to perform like the one in this office so that our appetite for risk looks almost the same across the book of business? But the world is changing, and commercial underwriting, if you picture it properly, is about whole-world management. Commercial underwriting is going to be called upon to minimize the impact of complex risk upon an ever-riskier world. We are entering new realms, where underwriting must have better technology, or else… 

For worse and for better — a connected world

We are living in a world interrupted. Southwest Airlines canceled 2,000 flights recently, a record number, for reasons that it can’t even figure out. In June, Home Depot responded to COVID-related supply chain issues by renting its own ocean-going cargo ship. Costco followed suit in September, chartering three ships. Labor shortages are shutting down businesses, cutting services and driving higher prices. Weather volatility seems to be growing, affecting claims of all kinds, from storm damage to crop loss. Increasingly, it seems like any event can trigger any reaction.

The business takeaway for insurers is the concept of dominoes. If one event can trigger chain reactions across hundreds of industries, channels, products and people, how do insurers understand and underwrite for those kinds of risks?

The answer: Change underwriting to meet the shifting world

The connectedness that is driving new risk is the same connectedness that can improve P&C underwriting. Commercial companies must know more and more frequently and predict better. Fortunately, they can. They can use data collection tools to gain better information. They can use artificial intelligence to gain deeper insights, make decisions and warn about risk, preventing or at least minimizing it. They can hand underwriters better tools for communications and visibility, pushing out their manual tasks and time-consuming steps into digital realms where workflow and process management might be handled by next-gen underwriting solutions. The P&C industry needs connected, intelligent underwriting more than ever before. Underwriters need total clarity into risk ratios, portfolio views, geographic risk and rating tools that don’t test a human’s attention span. It is time for a new era in commercial underwriting.

On Sept. 1, Strategy Meets Action released a Majesco-commissioned report, describing the future of P&C underwriting titled, Digital Underwriting in P&C: Leveraging Digital Thinking and a Digital Platform for Transformation. The report describes current and future pain points and opportunities for underwriting transformation. It is an excellent overview of a process and an industry that must change to meet the changing environment. I’ll discuss just a few of the findings here.

Underwriting’s pain points

At some point, as most of us grow in our occupations, we realize that we should be handing some of our simpler tasks off to someone with less experience, so we can focus our efforts on the talents we have honed. In no occupation is this more pronounced than with underwriters. Underwriters learn and grow. They become wiser and better at what they do. Yet many of them are still saddled with items that they absolutely should not be handling. It isn’t about a feeling of superiority; it’s about wasted time and talented resources that can support more business. SMA, in the report, points out that:

“Most underwriters, especially those handling more complex risks, are frustrated by tedious tasks and lower-level activities that are time-consuming. Inefficient collaboration and communication (internally as well as with external partners, agents/brokers and customers) take away time that could be spent on more value-added tasks. Ideally, underwriters prefer to apply their expertise and experience to decision-making. They would also prefer to spend their time establishing and building relationships with distribution partners.”

See also: Tech Pulse Quickens for Commercial Lines

The issue isn’t that underwriters feel under-used. When talent comes at a premium, and technology is able to accomplish some work faster and easier, wasted expertise is an operations issue. Everyone, including the underwriters, feel the magnetic pull of the better way.

Underuse and mis-use of data is also a concern. According to SMA,

“Underwriters need and expect a rich set of data to aid in their risk analysis. Acquiring that data efficiently from both internal and external sources is key.... Analyzing the data to gain insights is difficult. Gaining access to holistic data about policies and claims is vital yet often difficult to achieve with many of the legacy systems in place today.”

What makes it so difficult for organizations to prioritize their systems for gathering, analyzing and using data? Most of us know the answer: core systems that weren’t built to be data-savvy, and the constraints of data silos that were only constructed for certain types of data. Insurers are in desperate need of modern data management and warehousing tools that will expand to accept new data streams and easily plug in to machine learning systems that will filter, cultivate, present and use AI to decide. Using underwriters to their full capability will involve versatile next-gen data systems that are easily used with intuitive, transparent interfaces. Insurers don’t just need this for individual policy quoting and review — it is today’s “must have” feature to reduce risk across full portfolios of business. 

Why not add underwriting capabilities to existing systems?

As on-premise core systems were modernized over the past decade, many carriers used the on-premise policy underwriting capabilities to handle most functions with point-to-point integration of data and communication features. When a new capability was needed, it was added as a feature. Some built their own underwriting workbench, but often with limitations. The result, over time, has been a patchwork of layered features and tools that tie anything new to legacy constraints. SMA has identified multiple issues with this approach:

“Historically, larger, complex commercial lines risks have seen more layering of tactical tools but have not had the same attention, priority or technology investment as small commercial or personal lines. Unfortunately, with only 10% of implementations considered highly successful, the layering of incremental change may create significant change fatigue, especially when the current state is viewed as only semi-automated. The layering of more (but necessary) incremental changes will create personnel and execution risk.”

Creating an entirely new underwriting model

An overhaul of the model is needed if carriers are going to address underwriting’s pain points and grow their businesses with a better use of resources and improved information.

SMA has identified four key opportunities for improvement in commercial underwriting.

• Workflow management and automation
• Better use of data sources
• Increased collaboration
• Portfolio analysis capabilities

Their suggestion is an entirely new framework, where all of the related components are designed to work together. This holistic framework will make the best use of the technologies and data available and at the same time return far more timely, relevant and viewable data into the business. 

“The framework must support the workflow of relationship management, transaction processing and the portfolio management of their book. In addition, it must support and enable the processes to be automated, and the decision-making must be infused with new data, new models and new analytics.”

The communication component is also key. If workflow, information and communication are all improved at the same time, the results will be exponential. While the underwriting process will be dramatically improved, the value of having a fully digital, flexible plug-and-play underwriting system will grow with use. Today’s underwriting technologies will be learning and teaching as they grow.

What is required within a digital underwriting platform?

Now that we know what is needed in commercial underwriting, is there a right way to approach bringing it all together? SMA has a short list of requirements:

“This new evolution of underwriting will be powered by next-generation underwriting solutions that leverage a digital no-code/low-code platform, AI and advanced predictive analytics and new communication and collaboration tools. This can be a set of microservices that runs standalone and integrates seamlessly with other systems and data or a set of microservices for new capabilities that are plug-ins into the policy-admin and other key systems and data. Combined, the no/low-code and microservices approaches enable more rapid implementation and more flexibility for enhancements and upgrades.”

See also: How to Improve the Customer Experience

Something will change today. Is your underwriting ready?

As the world has grown more unpredictable, insurers know that they need to prepare. SMA’s research with insurance executives shows that they are well aware that change is going to affect underwriting: 13% of insurance executives expect big change, just this year; 80% expect big change in the next five years; and 94% expect big change in the next 10 years.

Is it about time for your organization to shift underwriting gears? Are you prepared for the future, with underwriting that will anticipate, learn, communicate and keep your organization protected from the risk of increased volatility? Changes keep happening. Commercial insurers can take any day’s news as a mandate for change.

For a better picture of the future of digital underwriting, download the SMA report, Digital Underwriting in P&C: Leveraging Digital Thinking and a Digital Platform for Transformation, or view the webinar profiling the report and Digital Underwriter360 for P&C.

Time to Get Rid of the IT Department? Paul Carroll, Editor-in-Chief of ITL An essay published last week by a principal research scientist at the MIT Sloan School of Management says it’s time to do away with the IT department, a stalwart of corporate organizations since the dawn of the Computer Age in the 1950s. He’s not arguing for the demise of the work, of course. IT remains at the heart of much of the innovation that companies must pursue to stand out from competitors in the market. But he says it’s time to integrate the functions of IT with front-line operations so a combination of business people and programmers can innovate in ways that matter most to those who matter most: the customers. The essay makes a compelling case, while offering insights from pioneering companies that have done away with the IT department. Joe Peppard’s essay in the Wall Street Journal argues that “having an IT department is exactly what will prevent companies from being innovative, agile, customer-focused and digitally transformed.” continue reading > New Majesco Podcast Join Denise Garth for her latest discussion featuring NFP’s Head of Innovation Mark Rieder on challenging the traditional voluntary market operating models, new technology trends and the role of innovation.   Listen Now SIX THINGS Buckle Up for Telematics 2.0 by Stephen Applebaum and Alan Demers For as much coverage as telematics has received for decades, its impact is just beginning to be understood. Read More Breakthroughs Via Low-Code and No-Code by David Kuhn Low-code and no-code programming are being used to create applications, improve efficiency and enhance the customer's experience. Read More Creating Room for Innovation  Sponsored by Rimini Street  What if it’s possible to spend less time and money on legacy systems, freeing resources to focus on developing systems that will really move the needle for the business? Read More First Steps to Digital Payments Processes by Elisa Logan Needing to cut costs, insurers can generate ROI on day one by implementing digital payments, with little risk of a hit to customer satisfaction. Read More How to Transform Claims Experience by Brent Williams Carriers that transform claims and service operations can turn a cost into a revenue-supporting, loyalty-driving, growth opportunity. Read More Why Some Workers Don’t Heal by Gerry Stanley That 20% of patients struggle and fail with recovery is a problem that is easily fixable once it is identified. Virtual reality plays a key role. Read More How to Transform Product Creation by  Greg Murphy With SaaS-based technologies facilitating much easier underwriting, the next focus in innovation needs to be the product itself. Read More After Finding Success in Ohio, Beam Dental is All Smiles Sponsored by JobsOhio Beam Dental, an innovative insurtech business, was growing. With the help of JobsOhio, Beam Dental moved to Ohio and found the perfect market for a growing startup. Watch Now MORE FROM ITL November Focus: Telematics In all my years covering all manner of technology, telematics may have caught me off-guard the most. When I first wrote about Progressive’s auto telematics program, Snapshot, in 1998, it seemed like a slam dunk. Of course, it made sense to monitor how people drove and to price their insurance accordingly. Or not. Read More Global Insurance Forum Experts Series   Sponsored by International Insurance Society  Over this six-part series, hear from industry leaders about building an innovation culture, leveraging data for success, and more. Watch Now Partner with ITL to create expert thought leadership content. Custom Content Promoted Content Display Advertising Custom Webinars Monthly Topic Sponsorships ITL Partner Packages and more Learn more and get the 2021 Media Kit GET INVOLVED Write for Us Our authors are what set Insurance Thought Leadership apart. Get Started SPREAD THE WORD Share Share Tweet Forward

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According to the National Association of Insurance Commissioners (NAIC), the top 24 commercial auto insurers write more than $45 billion in premiums, but for the last decade commercial auto insurance has been a challenging and mostly unprofitable line of business. According to a report from AM Best, underwriting losses for the commercial auto insurance sector reached a high of $4 billion in 2019. Between 2013 and 2018, commercial auto insurers reported $14 billion in losses.

Litigation, social inflation, driver safety, rising accident costs and a decaying public highway infrastructure have all contributed to a hard market for commercial auto lines and ever-rising insurance premiums for companies that operate commercial fleets.

“Commercial auto’s been pressured for roughly a decade, and I think a lot of carriers continue to struggle with auto performance,” said Tony Fenton, vice president of commercial lines underwriting and product, Nationwide, one of the top five commercial auto insurers, in a recent podcast. “There are a lot of different moving parts there. You have distracted driving, you have social inflation in terms of the results and loss pressures, but it's also keeping up with the technology, and understanding driving behavior and leaning into truly matching up rate and exposure. So that’s an interesting line that I think continues to be a pressure point in the industry.”

The COVID-19 pandemic brought a brief respite. In 2020, the commercial auto insurance segment posted its best underwriting result in a decade, largely attributed to continuing rate increases and a steep decline in driving due to the pandemic. According to a Fitch Ratings report, the commercial auto combined ratio of 101.6 for 2020 was nearly eight percentage points better than the 2019 rate. Fitch said it expects further improvement to move the commercial auto combined ratio to approximately break-even in 2021. Fitch also observed an “unprecedented decline” in commercial auto claims frequency. Industry data reveals a 26% decline in total reported liability claims in accident-year 2020.

Unfortunately, Fitch was quick to point out that the road to future profitability “may be challenged as driving activity returns to past norms, while claims severity patterns remain problematic and pricing momentum may have peaked.” As the economy recovers post-pandemic, our roads will get a lot busier. The U.S. Department of Transportation estimates that an additional 2.6 million vehicles will be registered in 2021.

“We believe underwriting profits for commercial auto insurers will likely remain elusive as the economy opens back up,” predicts Standard & Poor's in a Global Ratings report, “Commercial Auto Insurers Face a Long Haul to Profitability as the U.S. Economy Reopens and Confronts Shortages.”

With the hard market – characterized by increased premiums, reduced capacity and more rigorous policy requirements, underwriting rules and risk appetites – not likely to go away any time soon, commercial auto insurers are reimagining how they’re doing business today. Insurers are increasingly focused on operational efficiencies and technological advances as a means of improving underwriting margins and paving the way to profitability.

“The auto insurance industry needs to prepare for fundamental transformation, similar to the digital revolution we’ve seen in general,” says Abel Travis, VP & head of Fundamental Underwriters, a division of AF Group, and a specialist in commercial auto insurance. In this article, we look at a few of the key market trends and technologies to watch in commercial auto insurance in 2022 and beyond.

1. Telematics in Top Gear

Over the past few years, we have seen astonishing advances in on-board vehicle technologies that have the potential to make the roads safer for everyone. Commercial fleets were early adopters of telematics solutions, and the technology has become a mainstay. Telematics solutions send data from sensors and devices in the vehicle to the cloud, where it can be aggregated, processed and analyzed to provide insights. The types of information captured through telematics might include vehicle performance and maintenance data, mileage and driver behavior. Commercial auto insurers can leverage this data to more accurately assess and price risks during the underwriting process and to settle claims more effectively. Policyholders can benefit from telematics because, if the data demonstrates a track record and culture of driver safety, it can reduce the cost of their premiums upon renewal.

“Telematics is a slow-moving cyclone that is gaining speed over warm waters,” says Carey Anne Nadeau, co-founder and co-CEO of Loop and former CEO and founder of Ometry. “Telematics is a rich, real-time source for information about the location, usage and behaviors of drivers. I think there will be a derivative market of new products built from these data that help carriers realize more value from their telematics investments.”

Rob Galbraith, insurance futurist and best-selling author of The End of Insurance As We Know It: How Millennials, Insurtech and Venture Capital Will Disrupt the Ecosystem, sees telematics as part of a fundamental shift from “a point-in-time, periodic and historical view of risk to one that leverages the power of modern technologies such as sensors, cloud computing and advanced algorithms including AI to move closer to a real-time view of risk.”

Galbraith points out that turning the massive amount of data collected through telematics into actionable information remains a work in progress for insurance companies: “Insurers can now directly ‘observe’ behavior and conditions, ‘see’ near misses and have access to a ton more data than ever before. I’m not aware of a single carrier, however, that has fully been successful in not just capturing and integrating this data but using it in their pricing and underwriting processes.”

See also: Touchless Auto Claims: One Year On

Insurers that can effectively turn this data into meaningful information that an underwriter can easily digest and use will gain a significant boost. Eight hours of dashcam video from the cab of a transport truck, for example, isn’t particularly useful to an underwriter. To create real value, the data needs to be distilled in a human-friendly way that is easy for insurance professionals to consume.

“Harnessing large volumes of data from real-time sources can help insurers develop new products and refine pricing strategies. When combined with a robust operating strategy, advanced analytics can significantly increase underwriting profitability and provide a valuable market differentiator,” according to Ernst & Young (Source: IMS, "Commercial Insurance Telematics: Key Market Trends and Growth Opportunities”).

2. Tackling Distracting Driving

According to a recent survey from National Institute of Occupational Safety & Health, 47% of commercial drivers surveyed admitted to reading text messages while driving. Even more alarmingly, 34% of surveyed drivers said they have fallen asleep while driving, and 24% said they’d had a near-miss accident in the past week. According to Standard & Poor's, truck accidents are typically caused by driver error such as failure to follow speed limits, distracted driving, fatigue, mechanical failures and poor road conditions. Emerging telematics-based insurance solutions that provide real-time feedback to drivers may hold the key to addressing the problem of distracted driving.

“I believe that auto telematics will continue to drive a culture of safety across mobility,” Abel Travis says. “Telematics developers will continue to improve this technology, to help correct unsafe driving behaviors in real time, thereby improving driver performance. Distracted driving will continue to be tackled by technology providers, and autonomous features will identify and correct those unsafe behaviors. Some of this is already occurring today, especially in trucking and health and human services, two industries served by Fundamental Underwriters.”

Today’s telematics-equipped vehicles know a great deal about their drivers' behavior behind the wheel – everything from driving patterns, speeding, texting, multitasking, hard braking and airbag deployments in the event of a collision. AI, sensors and cameras trained on the driver can also detect dangerous behaviors such as distracted driving, bad habits or falling asleep at the wheel and provide real-time feedback.

“To understand how much risk the driver was taking at a given time, you really have to observe the driver,” says Roberto Sicconi, CTO and co-founder of dreyev (pronounced “drive”). “And the best way to observe is by using a camera that looks at the face of the driver, maybe even the hands, and then puts that into context. This is what we want with dreyev. We want to make sure that we understand what the driver is doing at any given time, in the context, and then based on that we warn the driver when there’s a need for it.”

For insurers that are equipped to harness this data, it provides invaluable usage-based insights for pricing: Commercial vehicle owners with good drivers are rewarded with better rates, while the dangerous or reckless behavior of bad drivers can be addressed by commercial fleet operators, either through retraining or replacing the driver.

A serious or fatal crash can be transformational to the business,” Carey Anne Nadeau says, “and we want to be making sure, as responsible commercial auto insurers, that we’re providing the risk management tools that the risk managers within the fleets need to keep people safe on the road.” Insurance carriers and brokers and their commercial clients need to work together to identify and mitigate liability risks, so everyone wins.

3. Autonomous Vehicles – AI in the Driver’s Seat

One technological breakthrough that everyone including the commercial insurance industry has been anticipating for some time is autonomous vehicles. When we first heard about them, the predictions were that we’d see them on the road in just a few years. Today, we know they’re out there being road-tested, but now the auto industry is saying it will be more like 10 to 15 years before they’re in widespread use.

“I think insurers run the gamut from still believing in science fiction to totally embracing it,” says Guy Fraker, chief innovation officer, IE Advisory, and one of the world’s leading authorities on the risks and opportunities associated with autonomous vehicles. “And the commercial fleet is a really interesting question. I’ve always hypothesized that it’s the tip of the spear, that this is where we’ll see the adoption first.”

But the mainstream rollout of autonomous commercial vehicles has hit a few bumps in the road. Questions remain about whether the public is ready for self-driving vehicles – especially a fully loaded 35,000-pound semi-truck barreling down the highway with nobody at the wheel.

One reason for the delay in adoption is an inbred distrust of artificial intelligence, and the unreasonable expectation that AI must be a perfect driver when we know that most human drivers are far from perfect. In a webinar on “The Ways Machine Learning and AI Can Fail,” Brian Lange, partner and data scientist at Datascope, cautions, “Don’t let perfect be the enemy of good.” Lange’s point is that human users are often hyper-critical of machine learning and AI, and this deep mistrust of AI outcomes can prevent organizations from realizing the benefits of AI. An AI solution may be much more accurate than a human at performing a given task, but the first time the AI makes a mistake, the tendency is for users to conclude that the solution isn’t very good and can’t be trusted.

As Guy Fraker reminds us, “Abraham Lincoln rode a 500-mile circuit on horseback in order to represent his clients. From his horse he prepared for trials, followed Supreme Court decisions and slept quite a bit. Do you know what never happened on his 1,500 miles per year riding a horse? Not once did his horse run into anything. The cars never have to be human smart to improve upon human performance – as smart as a horse will do.”

Autonomous vehicles are coming, and commercial auto insurers need to be ready. “I believe that we will see further adoption of autonomous technology, pioneered at companies like Tesla, and adopted by companies such as Nikola,” Travis says. “As we’ve seen companies like Rivian move into electric and autonomous vehicles, I believe we will see more embedding of insurance with the cost of the vehicles to offer a rounded solution to consumers.”

4. The Ridesharing Revolution

One bright spot during the pandemic was the growth of the ridesharing industry, aided by people opting out of public transportation on crowded trains, buses and streetcars. The industry also welcomed new drivers who had previously been employed in industries hard-hit by the pandemic, such as retail and hospitality.

“There’s no question that we are at the point of embracing ridesharing as an economic juggernaut,” Fraker says. “Rideshare platforms are one of the most transformational technology platforms outside of social media.” For insurers, the new ridesharing business model has been a catalyst for fundamental change.

“History will look back on ridesharing as a pivotal point in the transformation of insurance,” Fraker explains. “Throughout the history of the industry, there’s been this almost old Berlin Wall-like divider that was immovable – it might as well have been the Himalayan Mountain range – between personal lines and commercial lines. And that enormous immovable barrier got blown up by the mixed use of rideshare, where it was part commercial, part personal. The industry realized that they had to figure out how to go back and forth between personal use and commercial use.”

The ridesharing industry has created new opportunities for insurers, as well as new challenges in navigating the grey areas between commercial and personal vehicle use.

“I know that there are a lot of drivers who are using their own car with their own regular insurance without declaring to the insurance company that they’re using it for occasional ridesharing,” says Roberto Sicconi of dreyev. “And when they do that, they put themselves at serious risk because, if they get into a crash, and then the crash happens to involve some other passenger that was not supposed to be part of a family or so on, they may not get the coverage.”

“I believe Uber, Lyft and other rideshare companies offer special additional policies for drivers that cover them during the rides,” Sicconi adds. “And then you have to demonstrate that you were on a ride with somebody in the vehicle rather than approaching the place where you wanted to pick up the customer, but you were on your own. So, there are some tricky situations that I don’t think are always sorted out properly.”

See also: 3 Trends Transforming Auto Insurance

5. Reimagining the Insurance Back Office With AI

While revolutionary technologies like autonomous vehicles may steal the headlines, there is still a lot of work to be done in the insurance back office to streamline manual underwriting and placement processes, reduce operating costs and improve the policyholder experience. Commercial auto insurers are looking to technologies like AI, machine learning and natural language understanding to harness the power of their data and automate core processes like data extraction and ingestion, submission intake and triage and policy checking to improve their margins and grow their revenues. While they might not seem as futuristic as a self-driving semi-trailer truck in the center lane with no one at the wheel, these data-driven operational improvements are part of a “quiet revolution” in the industry that is every bit as visionary and transformational for commercial auto insurers on the long road to profitability.

You can find this article originally posted here on Chisel AI.

Here is Part One of this two-part series on improving the customer experience. What follows is Part Two.

AI-powered chatbots pack more power than simple rule-based chatbots. As opposed to pre-programmed “if this, then that” rule-based chatbots, AI bots use algorithms and natural language processing to develop human-sounding responses and collect data to learn from each interaction, improving over time.

Natural language processing refers to how artificial intelligence can give computers the ability to comprehend text and spoken words like humans can. NLP combines rule-based modeling of human language with complex machine-learning models. These combined technologies allow AI to understand writing and voices from various languages. AI makes it easy to translate languages, respond quickly to verbal requests and summarize large amounts of text in a quick, digestible manner.  

One advantage of AI chatbots is they enable insurers to serve customers in their preferred language—whether it’s English, French, Spanish or another language— at scale. AI chatbots use neural machine translation engines to learn languages. Machine translation refers to the set of tools that allow users to input text in one language that generates an instant translation to a different language. Google Translate is the best-known example.

An AI chatbot can even learn slang and understand different acronyms. It’s vital for bots to understand insurance acronyms and not confuse them with the incorrect phrase. For example, based on contextual data, AI chatbots can understand “AI” to mean “additional insured” instead of “artificial intelligence.”

These machine-learning capabilities allow AI chatbots to become more precise over time as the bots learn from each interaction with users. Insurtech vendors are forming partnerships with AI vendors to advance the state of the art.  

Best Practices for AI Chatbots in Insurance

Insurers can drastically reduce costs and turnaround time by adopting multilingual AI chatbots. According to a study by Juniper Research, using conversational AI chatbots for insurance will lead to cost savings of about $1.3 billion by 2023 across life, property and health insurance.

When Generali, the big Swiss insurer, installed an AI-enabled email chatbot, the bot was able to:

• Triage incoming emails
• Obtain open invoices
• Forward the emails to the correct department automatically and understand the urgency and tone of the email

As a result, Generali increased Level 1 support capacity by 40%, and it now takes under two seconds for the AI chatbot to send an email to the correct department 24/7.

In 2016, Lemonade’s AI chatbot set a world record for the fastest processed insurance claim. The chatbot received a claim for a $979 coat, checked the claim against the policy, ran 18 different anti-fraud algorithms and made the payment – all in less than three seconds. 

Customer-Feedback Mechanisms

AI chatbots clearly show great promise. However, there are important things for insurers to keep in mind before investing in AI. One key consideration is the customer-feedback mechanism.

A feedback mechanism can be a simple question the bot asks the user. Some great questions include:

• On a scale of one to 10, how would you rate our conversation?
• What did you enjoy the most about our discussion?
• What can I improve on?
• What else are you looking for?
• Is there anything else you’d like to mention about our interaction?

AI is only as good as the data it is based on. By validating the AI program early and often with real user feedback, insurers can invest in AI sustainably and avoid costly AI mistakes down the road.

See also: Chatbot, Your Time Is Now!

Type of Chatbot

The ideal chatbot solution for an insurance company depends on how much data your marketing and client-support teams can collect and analyze effectively. AI chatbots have a clear advantage in their ability to learn through each interaction and provide helpful responses to a broader set of inquiries. However, their reliance on big data and various machine learning and NLP techniques make AI chatbots a heavy lift for some carriers facing constraints in other areas of their business.

Rules-based chatbots are quick for insurance companies to implement but less flexible than their AI-enabled counterparts.

Regardless of how great your insurance chatbot is, customers still value human connection. According to a survey by HubSpot, 81% of consumers would rather interact with a live human agent than an electronic system. Insurers need strategies to persuade that group to give chatbots a chance to help them.  

Customer experience is a broad discipline encompassing multiple channels, both digital and non-digital. Striking a balance between approaches is key, and it will require some trial and error to determine when a chatbot should let a human take over to best meet your customer’s needs.  

The future is coming fast, and insurers should consider both rule-based and AI-powered chatbots.

An essay published last week by a principal research scientist at the MIT Sloan School of Management says it's time to do away with the IT department, a stalwart of corporate organizations since the dawn of the Computer Age in the 1950s.

He's not arguing for the demise of the work, of course. IT remains at the heart of much of the innovation that companies must pursue to stand out from competitors in the market. But he says it's time to integrate the functions of IT with front-line operations so a combination of business people and programmers can innovate in ways that matter most to those who matter most: the customers.

The essay makes a compelling case, while offering insights from pioneering companies that have done away with the IT department.

Joe Peppard's essay in the Wall Street Journal argues that "having an IT department is exactly what will prevent companies from being innovative, agile, customer-focused and digitally transformed."

Yes, having a separate IT department made sense when massive computers needed to be cooled with water and kept in air-conditioned rooms, but, thanks to the cloud, little computing infrastructure even needs to be kept on-premises today. Meanwhile, the value that companies -- including insurers -- provide has migrated away from data centers and toward the front lines and expert interactions with customers and prospects.

Peppard says the problem with an IT department begins with the fact that is treated as a supplier to the rest of the company and, as a result, is measured in ways that are "often irrelevant to the success of the business." The measurement are "almost always inputs — money they have spent, systems that don’t break down, or projects that come in on time and on budget. But there’s almost nothing about the contributions that technology is making to business outcomes...."

He adds that "the [current] model also assumes that it’s possible for the various corporate units to define upfront and many months in advance exactly what they will need from the IT department.... That isn’t how the world works in today’s fast-paced digital world.

"Sure, you can say you want the IT department to be faster and more flexible. But having the department in a silo makes that almost impossible."

He recommends setting up a structure "that organizes employee groups around missions," embedding tech expertise into those groups and using emerging tools such as low-code/no-code programming so that those with business expertise can at least begin the design process for software that will matter to customers and the business.

In many ways, I've been noodling on this question of what to do with the IT department ever since I started covering the computer industry for the Wall Street Journal way back in 1986. One of the first articles I wrote for the front page was on the IT backlog: Business executives griped that they'd have to spend months laying out detailed specs for a programming effort and then wait 18 months to two years for the result -- only to find that IT hadn't quite understood the need or that business conditions had changed.

In 1989, I wrote a column in the WSJ that, at least for me, served as an introduction to the cloud. I quoted someone speculating that, say, a fast-food chain would be able to buy computing power that varied based on the number of hamburgers served, rather than having to invest in all the computing infrastructure up-front. The next step came in 1996, when that visionary I quoted (the late, great Mel Bergstein) recruited me out of the WSJ to be a partner in a consulting firm he founded that was pioneering the idea of digital strategy -- we weren't challenging the viability of IT departments but were certainly driving the idea that IT should be deployed far more strategically.

But nobody ever solved that core problem I wrote about 35 years ago, despite the extraordinary steps the world has taken toward digitization. Executives still find that IT projects take far too long and miss the mark too often.

I suspect that Peppard's essay won't solve the problem, either. Companies still can't afford a glitch in their core systems, especially in a data-intensive, heavily regulated industry like insurance. And there will still need to be loads of coordination across departments and business units, so there will need to be centralized control of data models, compliance standards, look-and-feel and so on. The IT department may shrink, even considerably, but won't go away. Nor will the frustrations that come from dealing with it and with what is, after all, complicated technology.

But I do think that Peppard's essay represents real progress. I can certainly imagine tech expertise being pushed into claims, underwriting, the distribution channel, etc. so that innovation can happen on the front lines.

I think back to a model for innovation that we had at the firm Mel founded (called Diamond, now part of PwC) and that I've seen versions of from other firms in the years since. We showed three tiers of tech investment. The bottom one was the "stay in business" work -- keeping the lights on, the computers working, regulations followed. I suspect that work will stay centralized as part of an IT department for a long time. The middle tier was what I think of as "running fast just to stay in place." You're setting up, say, self-service capabilities on your website, which will cut your costs and please customers -- but your competitors are doing the same, so you won't gain any competitive advantage, at least for long. I think that middle tier work will start to migrate out toward the front lines and could perhaps even move quickly away from the IT department. But the real move needs to be for the top tier of work, which we labeled as "option-creating investments" -- the experiments with, say, telematics or blockchain that could lead to breakthroughs that would provide real advantage. That work has to be done quickly, in direct consultation with partners and customers who might benefit, and should be largely freed from a centralized IT department.

In other words, I wouldn't think about deleting IT from your org chart just yet, but Peppard's vision is something to aspire to. And I'd recommend that we all start experimenting with ways to push the tech work out of its silo and into the front lines of the business.

Cheers,

Paul