The changing nature of risk: From transfer to mitigation and avoidance

10 July 2018

The Risk Model, Transformed

When Lloyd’s emerged to introduce the world’s first marine insurance product, capital was scarce. Underwriting was based on limited parameters, such as a ship’s hull size, cargo, and journey start and end destination, and supported by rudimentary arithmetic. Many times, losses were reported months after their actual occurrence.

Today, technology is transforming the marine industry. Data can now help mitigate risks associated with a ship’s hull, cargo, and journey path. With IoT we can monitor the real-time performance of a fleet of ships down to the condition and temperature of individual containers, allowing action to be taken if damage is imminent.

The experience from the marine sector is mirrored in other industries as diverse as commercial property, manufacturing, and utilities. Data that once lagged or was non-existent has become available either near or real-time. Further, the ability to analyze data using sophisticated analytics is fundamentally changing the way risks are understood.

As systems become more connected, and our understanding of them improves, so too does our ability to model complex risk scenarios and introduce alternative solutions. For instance, the impact of a ship’s delay can now be understood beyond the vessel itself to ramifications for port operations, hinterland transportation and even manufacturing production schedules.

With increased volumes of data comes the ability to apply sophisticated analytics yielding greater insights and ever better transparency to differentiate risks. An insurer can now augment traditional rearview guideposts for risk prediction with real-time operational data to significantly enhance precision, and more importantly, move towards risk mitigation and avoidance.

Evolving New Business Models and Shifting Risk Concerns

Over the past forty years corporate valuations, once anchored in tangible assets, such as plants, property, equipment, and inventory, have transitioned to intangible ones, such as intellectual property, channel networks, data, and customer relationships. In 1975, tangible assets constituted 83% of the total market valuation of S&P 500 companies. By 2015, this percentage fell to 13%.3

In search of risk solutions that create predictable earnings, cash flows, and cost of capital, the commercial sector has scrambled to understand and protect against shifting risks, which increasingly are tied to non-physical damage, supply chain, cyber, product recall, reputation, and business interruption (all included on lists of insureds’ top concerns in recent surveys).

Along with a growing list of non-asset-based risks and financial valuations untethered from underlying physical infrastructure, we are witnessing the rapid growth of the sharing economy. Novel and inventive business models that disconnect asset ownership and usage are being created in virtually every sector - from office sharing (WeWork), global freight (Convoy), and construction (Yard Club, acquired by Caterpillar), to warehousing (Flexe), supply chain (Floow2) and the now familiar examples from transportation (Uber, Lyft) and hospitality (AirBnb).

Evolving new business models and shifting risk concerns are causing companies to look for product innovation that provide protection against a wider set of threats and extend covers to include complex and interconnected systems. With the financial impact of an event potentially far surpassing the cost of the physical damage, companies need solutions that can solve systemic risk problems to enable improvements in the loss ratio.

To model and price such risks, new data sources must be combined with advances in analytical models and machine learning. Companies will count on their insurance partners to use these insights to proactively help them to prevent business interruptions. Should an incident occur, companies will come to expect that their data will provide for more rapid and accurate incident recreation, enabling a swifter claims process, an improved customer experience and learnings that will prevent similar occurrences in the future.

Paradoxically, the technology that gives rise to insurance product innovation can also pose significant threats as new sensors and devices introduce a myriad of cyber entry points into the enterprise. As companies create products and services that incorporate IoT, cyber threats have the potential to become more prevalent and more damaging. Insurers will need to take a proactive role to ensure standards and practices for IoT security are rigorously enforced and monitored.

I. The Potential Of Iot And Data In Commercial Insurance

An Industry, Transformed

Our fundamental belief is that commercial insurance will shift from today’s prevalent risk transfer and indemnification model towards proactive loss prevention and risk avoidance.

IoT offers opportunities to impact all major value levers, from increasing revenue with new and existing products and services, to reducing cost levels, and improving the customer experience. Early moves and experimentation to this effect can be seen with re-insurers providing their balance sheet to underwrite the risk sourced by innovative start-ups, and the introduction of intermediaries4 with technology linked programs that are unencumbered by legacy processes and IT infrastructure.

As we have seen in other industries, incumbents must redefine and reinforce their value propositions with digital and analytic technologies that by their nature reduce the distance between buyers and sellers. Or, in the case of insurance, the distance between risk and capital. A recent joint-study by Bain and Google5 has highlighted the opportunity for insurers to adopt IoT, data and digital technologies to streamline internal processes, more effectively underwrite risk and minimize fraud to achieve operating savings of up to 29% of the insurer’s cost base.

Among existing processes claims is arguably where IoT will have the biggest impact. An abundance of structured, and un-structured data can be combined to provide operational insight to ease claims filing and enable rapid evaluation and disposition. Imagine a workers’ compensation claim for a worker where the digital workday has been recorded to provide a minute-by-minute transcript of the workers’ location and activities. We will know the workers’ whereabouts, whether he was walking / running or engaged in physically straining activities before and after the claim. Just as important, we will be able to provide personalized coaching, training (via low-cost, digital channels) and apply gamification methods to help the worker reduce activities that can lead to injuries. Once an incident has occurred and a claim has been filed, this trail of insights will prove helpful in aiding recovery, expediting the processing and closure of the claim and combat questionable claims.

The concept of digitizing the physical environment and using data to handle claims objectively and quickly can be applied across all insurable assets. Sectors that are the farthest along include industrial manufacturing and energy, where firms such as GE and Siemens have invested billion of dollars into IoT data platforms. Building on top of these platforms companies and insurers can effectively reduce risk and risk-related pricing, enhance efficiencies and develop new products and services that adopt IoT, data and digital technologies to reduce friction cost.

From Infrequent to Daily Interactions

IoT will change the nature of the relationship between the company and its brokers and carriers with an emphasis on frequency and relevancy.

In the current environment, clients are typically touched 3-5 times per year. These touch-points consume 30%- plus of direct written premiums between expenses and commissions. The constant flow of data and insight from IoT devices will necessitate rethinking this high cost interaction model. With IoT, touch-points will become a daily occurrence (at least). The vast majority of interactions will be digital, with information conveyed through mobile apps and Application-Programming-Interfaces (APIs), to serve policies that in most cases will be usage based. Naturally, it will be necessary to re-engineer current acquisition, retention and renewal processes for scale and automation to achieve high efficiencies and low cost. Human intervention will need to be kept minimal and focused on high-value interactions.

This presents a big opportunity for forward thinking brokers and carriers. Armed with deep contextual knowledge and insight, they can work with clients to reduce risks, thereby enable more meaningful and trusted relationships. The traditional account manager will need to take on a more consultative role, however. This will not be easy and reconfiguring client-service to a hybrid model employing consulting and relationship management with automated delivery of insights will require careful design balancing cost and client value.

Opportunities for Impact

Commercial insurance impacts all industry sectors. The influence on risk transfer will be felt initially in industries that have been early adopters of IoT. These industries include manufacturing operations, freight monitoring, production asset management, transportation, utilities, and commercial property.6 Cross-industry use cases that are prime candidates include predictive maintenance, automated inventory management, connected cars and fleet management.

We are firm believers that functions which are currently data poor, such as processes related to worker health and safety, will quickly become data-enabled once the value of IoT proof-of-concepts are established.

Examples of segments where leveraging IoT can have the greatest impact:

Preventative Maintenance and Asset Optimization

Preventative Maintenance and Asset Optimization:

An organization can achieve greater insights into the health and performance of its assets through IoT. By monitoring an asset’s health, an optimal strategy of maintenance and operations can be developed and deployed. Insurers can leverage this insight to manage business interruption exposures, avoiding unplanned and potentially expensive incidents.

Commercial Properties

Commercial Properties:

Modern buildings are outfitted with an array of sensors that monitor the performance of critical systems, ranging from HVAC, water, gas, electric and fire to access control, security and building occupancy. As older buildings are retrofitted and connected through industry standard data protocols, systems that have been targeted for use by facility managers can be augmented for risk prevention, providing a rich opportunity for insurers to prevent damage and help clients reduce their risk exposure.

The Connected Worker

The Connected Worker:

Agriculture and construction are two industries that will benefit from a safer workplace. Fatigue costs large organizations on average $80 Million per year in decreased productivity, missed work, and poor employee health.7 IoT devices, such as wearables, can monitor a worker’s level of awareness, detect postures that can lead to injury, and provide haptic feedback to workers to inform them of safer working habits. This type of digital coaching enables the identification of unsafe or unhealthy working conditions and has been shown to reduce high risk postures, such as bad bends, that lead to significant workers’ compensation claims

II. Implications Of Iot And Data To The Commercial Insurance Value Chain

A Shift in the Value Chain

We expect that IoT and data will begin to influence the very structure of how insurance is bought and sold. We see the value chain reshaped by three interlinked themes:

First, data will lead to new levels of transparency. Insureds will exert their ownership of data and seek price competitive solutions by shopping their risks in a competitive marketplace. Insurers must quickly learn to evaluate these risks and price competitively while also incorporating new risk prevention methods that ensure acceptable margins. We can easily envision a sport market for commodity risks, where insureds place their risks on a supply/demand matching platform.

With increased transparency, we will also see less subsidy and miss-pricing of higher risks that until now have been hiding in insurers’ portfolios. This will lead to companies beefing up their risk management capabilities and creating opportunities for proactive insurers that understand how to interpret and act on risk data originating from connected devices.

Implicit with increased transparency is the demise of the portfolio-based risk transfer model. We are moving from broad risk pools down to individual risks.

Second, the commercial insurance value chain will operate at higher velocity. This means that the turnaround time for producing proposals will dramatically shorten as underwriters use sophisticated tools to quickly evaluate risks and produce quotes. In some cases, especially for commoditized risks, underwriters may only have a quality assurance role to play, if any.

Reconfiguring the value chain for speed and precision will require automation and the removal of functions that do not add clear value. The opportunity for cost reduction is significant, and insurers will be forced to take painful and necessary steps to reduce costs.

The third theme revolves around the customer and the re-alignment of incentives. We expect that IoT and data will create a true financial incentive to decrease risk and increase business performance, thereby creating a win-win between the company, its broker and carrier. Moreover, commercial insurance is still a product-focused industry, and to this day, projects itself in a siloed manner to clients. Keeping up this appearance will be ineffective as sensory data from machines, buildings and fleets combine to create a comprehensive, cross-asset class view of a clients’ risks. We believe commercial insures will be able to unlock many opportunities from such scenarios in the years ahead.

As we have seen in other industries, digital technologies and data will cause a re-examination of the relative value delivered by all participants across the value chain, with a tendency to reduce friction and shorten the distance between the customer and the service or product delivered.

Similarly, in commercial insurance the distance between risk and capital will be reduced and force intermediaries to clearly define their roles. As placement, especially for simple and medium complex covers, moves towards semi-automated platforms, the middle man will need to become more information literate and leverage newfound insights to proactively take actions to contain and mitigate their clients’ risk exposure.

A New and Emerging Value Chain

The new insurance value chain will offer an efficient transactional system that provides for quicker and easier placement of risk, pricing, underwriting, policy issuance, and certificate and invoicing and claims.

Placement, underwriting and claims management hold the greatest promise for transformation. Placement of risk will be migrated towards efficient supply-demand matching platforms that consider an insured’s unique risk environment, evidenced through the digital breadcrumbs that model the physical environment.

Underwriting will be transformed as access to volumes of pertinent data and machine learning provide greater insights for risk selection and pricing.

The greatest impact is reserved for the claims process. With a wealth of data now available to virtually reconstruct events prior to and after an incident, the time spent on incident re-creation can be dramatically shortened. The result will be reduction in ambiguity and significant improvement in claims settlement speed.

Just as important as changes to existing functions, new roles will be needed. The prime of these are risk mitigation and prevention, which involve turning data into insights that can be acted upon. Successful commercial insurers and brokers will establish new revenue centers to consult with clients to effect change. These same entities will find new economic models that go beyond traditional consulting fees to risk-reward mechanisms cemented in common goals and shared outcomes.

Key Value Chain Roles in Transition

We will begin to see many job functions altered by the rapid adoption of tools that augment and enable existing employees. There will be a drastic focus on cost reduction by creating efficiencies as existing processes are data enabled.

As part of the new value chain, individual job functions will remain but with revised mandates and tools that combine artificial intelligence and automation.

The Insured

The Insured:

With a wealth of data owned by the insured, relative power can easily swing in the insureds favor as placement platforms provide an efficient mechanism for matching risks with capital. This can be a double-edged sword though, as transparency and efficiency remove some of the subsidies that until now have benefitted some. We believe insureds will come to expect an improved experience in dealing with insurers and brokers across omni-channel touch-points. They will expect higher levels of advocacy from their risk providers who in turn must leverage client specific insights to reduce and prevent risks and sustain their relevancy.

The Claim Adjuster

The Claim Adjuster:

The claims process will be transformed by new data assets that digitally recreate the environment and events that led to an incident and subsequent actions. This will reduce the amount of time required to settle a claim (a key buyer value), as well as the time and effort needed to investigate cause and effect. In some instances, it will be possible to automate the entire claims process, with claims adjusters acting as exception handlers and case managers for larger, more complex claims.

The Underwriter

The Underwriter:

The underwriter, armed with new tools, will increasingly focus attention on complex risks and new risk classes that blur the distinction between consumer and commercial. Underwriters will focus more of their attention on modeling and understanding compound risks and connected systems. Simple and medium cover risks will increasingly be automated and brought to the underwriter’s attention on an exception-only basis.

The Broker

The Broker:

The broker’s role is most at risk to be disintermediated, as the frequency of engagement between the insured and insurer increases. The broker of the future will need to be more information literate and combine their understanding of clients’ operations with insight from new information sources to improve their clients businesses and reduce their risks

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3 “Commercial insurance: innovating to understand the scope of insurability”, Swiss Re Institute, May 2017 (refer to page 2 Figure 1 of the SwissRe report)
5 “Digitalization in Insurance: The Multibillion Dollar Opportunity”, Bain Brief, 2017
6 “Winning in IoT. It’s all about the business processes,” bcg.perspectives, 2017