Tag Archives: transformation

Insurers Turn to Automation

Insurers that are heavily dependent on traditional business models have struggled over the past year with financial strain. But automation presents an opportunity to establish short-term successes to speed up recovery and long-term results that can stimulate growth by accelerating digital transformation.

Here are the ways automation can help create resiliency in insurance organizations, ensuring that operations run smoothly and effectively:

Improving Customer Service and Employee Experience

Customer expectations are at an all-time high as digital-native brands like Amazon continue to dominate and set standards that are difficult for other companies to copy. These standards don’t only appear in business-to-consumer transactions but also in business-to-business transactions that include promoting product innovation and mix. Insurers strive to deliver high-quality customer experience, but there is still a gap between what customers expect and what insurers are delivering – especially when it comes to being available at all hours and on all channels. 

See also: New Tool: Cognitive Process Automation

Typically, at an insurance enterprise, when a customer calls into the support line with a question about billing, the inquiry goes straight to a call center agent. The agent must spend time asking a myriad of repetitive follow-up questions to confirm a customer’s identity and understand the situation, then spend more time searching for a customer’s account information across multiple systems just to identify the issue. With automation, as soon as the call comes in, a software robot begins aggregating the relevant customer data for the agent. Through a combination of customer sentiment and behavior analytics, the robot then pulls actionable information into a streamlined application with quick access to next steps for the agent.

This seamless interaction means a customer has a much quicker, more personalized, positive experience, and the agent is ready with the right information to do the job efficiently and bring to the customer request to an appropriate resolution. 

It is essential that insurers invest in technology that drives a seamless digital experience at every communication channel – whether it be a chatbot, a mobile app or an interaction by phone. When an insurer is available in this capacity, it can provide customers with an easier experience and provide servicing or resolve claims at a lower operational cost. Intelligent automation links the ecosystem of traditional insurance systems with technology capabilities.

Streamlining Business Operations

In addition to the front-end benefits to the customer, automation is key to optimizing internal, time-consuming manual processes. Automation means insurance organizations can react more quickly to increasing demands from policyholders, agents and partners with innovative, customized and transparent products and pricing.

Insurance is a long-established business with tons of existing systems, including spreadsheets, PDFs, scanned documents, applications like Duck Creek and Guidewire and data from third parties such as LexisNexis. According to Celent in 2018, 45% of insurance CIOs identified heavy, disconnected and duplicative legacy systems as a key inhibitor to digital transformation. And this reality hasn’t drastically changed. According to KPMG’s 2020 CIO Survey, insurance CIOs have “improving operational efficiency” as their #1 business issue that needs to be addressed. The primary reason for lagging operational efficiency is being disconnected and multi-tech systems with non-standardized data.

See also: Keys to ‘Intelligent Automation’

Automation can be created on top of existing systems, meaning these systems can be integrated so that data and underlying processes can be much more streamlined, enabling an easier digital transformation. Once the legacy systems are integrated with automation, it’s easy to create hands-on and hands-off robots that automate repetitive tasks, reduce process costs and cycle times and free time to focus on higher-value work like pursuing new business.

Processing claims end-to-end is one high-value example of how automation can streamline operations. To begin processing a claim, an agent must collect customer information from a variety of sources, including policy administration systems, documents, third-party systems and claims processing systems. Manually looking for the right information across multiple locations – virtual or not – can be time-consuming. Once the information is collected, entering it manually into the system is a frequent source of mistakes. 

The consequences of redundant and incorrect data entry range from delays and harming the customer experience, to errors and omissions in claims information, to potential fraud and leakages – all of which are damaging to the business. Hybrid automation – the process of using a combination of unattended robots, which send cases to humans for decision making, and attended robots that sit on an employee’s workstation and trigger the employee to take a specific action to start a workflow – can take care of the entire process start to finish, eliminating many of the unnecessary mistakes while saving time and resources.

Navigating Future Disruption

This past year of unprecedented changes and hardships has CIOs and CEOs preparing for expanded digital change. Some insurers are already using automation to accelerate digital transformation and see results in their core operations, including claims, customer service and new business intake. 

The typical response to new customer needs are large, long-term investments, ranging from core system modernization to multi-channel integration, that are slow to get off the ground and drag on the time-to-value. When automation is a core technology, digital transformation can be delivered at speed, meaning faster service and faster return on investment. Modernized, automated solutions mean CIOs and senior business leaders can build the flexibility to adapt to market demands more quickly, deliver improved customer experiences and advance the business digitally transforming the legacy environment.

Different Flavors of Transformation

A client recently asked me to explain the differences between innovation, transformation and improvement and to suggest how they might drive innovation, transformation and improvement in their own business.

Although I’ve helped insurers with all three of these on multiple occasions, I’d never really taken the time to figure out the distinctions, or how the terms fit together. So I did some research and thought a bit and came up with an answer.

I certainly don’t think this is the only way of looking at the issue, but it certainly helped me once I’d figured out my version of the answer. And, having now clarified matters in my own mind, I thought it might be helpful to share.


Having hunted around, it seems there are no universally accepted definitions of innovation, transformation or improvement within a business context.

For me, business innovation is the delivery of something new with the intention of improving business outcomes. And that “something” can cover a wide range of territory, including products, services, distribution channels, processes, operating models, technology, and culture – indeed, any aspect of the insurer’s business whatsoever.  

I then find it helpful to distinguish two broad types of business innovation (and I’m indebted to the Digital Insurer’s TDI Academy for this, as it’s a distinction we teach on their ADI Program):

  • Business Transformation is the large-scale reinvention of the whole business or a material subset of the business (such as a business unit or function); whereas
  • Business Improvement is focused on smaller-scale changes, typically in only one element of the value chain or within a single team. It is more about improving today than inventing tomorrow.

There is no hard-and-fast boundary between the two, but, given the definitions I’ve just offered, the primary differentiators are:

  • The scope of the innovation; and
  • The scale of the insurer’s ambition.

Approaches to Design and Delivery

If there’s no hard-and-fast boundary between business transformation and business improvement, then why bother to distinguish them at all?

Because, based on my experience of dozens of insurance innovation programs and projects, I believe insurers should use different approaches to the two different types of innovation.

See also: It’s Time for Next Phase of Innovation

Designing and Delivering Business Transformation

I’ve shared my tried-and-tested approach to business transformation before, within the context of digital transformation:

The Sustainable Business Transformation Model from Alan Walker, LLC

Given the broad scope and ambitious scale of this type of innovation, it’s not surprising that the approach is very much rooted in the needs of the customer and in the business’s overall strategy. Building on these critical foundations, the insurer then needs to:

  • Paint a vision for what will be achieved;
  • Drill that down to a deliverable design;
  • Establish the capabilities required;
  • Create a road map to bridge the gaps;
  • Deliver what’s on the road map;
  • Review achievements, reassessing as needed;
  • Wrap the transformation with strong change management; and
  • Apply good governance throughout.

Designing and Delivering Business Improvement

So how should the (somewhat less-ambitious, narrower scope) business improvement projects be handled?

As I considered all of the insurance improvement programs and projects I’ve been involved in over the years, I recalled multiple different methodologies that I’ve used at one time or another.

These methodologies typically varied according to the different problems they were trying to solve, or the different opportunities they were looking to pursue.

But as I thought about the different approaches I realized that, despite linguistic differences, they had many characteristics in common. Indeed, it was possible to see all of them as particular flavors of an overall approach that could fruitfully be used for any business improvement project.

For obvious reasons, I call it “5-I.”

The '5-I' Business Improvement Model from Alan Walker, LLC

The 5-I model delivers, and sustains, the desired business improvement in five steps:

  • Initiate: Frame the problem to be solved, or the opportunity to be pursued, and launch the project.
  • Investigate: Analyze the problem or opportunity to understand it fully, including root causes and implications.
  • Ideate: Generate possible solutions or take advantage of the opportunity. Then analyze the alternatives and agree on which one(s) will be taken forward to delivery.
  • Implement: Deliver the solution(s) and manage the change(s) to ensure the improvement is embedded and sustainable.
  • Inspect: Review what’s been done, asking whether the insurer has solved the problem or is realizing the expected benefits. If not, iterate as needed. Otherwise, close the project.

See also: Adversity Breeds Innovation

Granted, there will be nuances between projects at the next level down, but I’m struggling to come up with a business improvement project this approach doesn’t fit.

Key to Transformation for Auto Claims

The word “transformation” is overused, and yet here in the auto insurance claims industry there is no better word for a process that is being changed so dramatically from beginning to end, and at every step in between. 

But real transformation, while claimed by many, is in reality only enabled by the exceptional few. That is because transformation occurs through a collective, inclusive effort, not a silver bullet technology. And complete transformation requires the active participation of the end-user, to ensure higher levels of acceptance and satisfaction. Transformation must be good for the business and the customer, or it will likely not take hold at all. 

Foundational to Success

Digital transformation is the essential driver behind how companies will add value and deliver services to their modern customer, a customer who expects and trusts digital interactions. AI is critical to processing and assessing all inputs and removing friction. Yet AI alone cannot deliver transformation. 

Let me explain.

We know data availability is increasing rapidly across multiple dimensions – volume, velocity and variety. In the last two years, more data was created than in the entirety of human history. This is a fraction of the data that will be available in the near future as connections continue to multiply, becoming increasingly bi-directional and informing virtually everything. Right now, there are more than 50 billion connected devices in the world, and connected cars are emerging as an important digital platform.

Artificial intelligence is the only way businesses can leverage the tremendous amounts of data available. AI synthesizes all of this data. This is positive and necessary. But AI output is often delivered to humans, reviewed offline and paused before actions occur. Companies have to eliminate this pause and disconnect in the process to transform their operations. AI decision-making must be digitally connected to operating systems or consumer interfaces or both to drive action and to create a truly elevated, digital experience.  

See also: Transforming Auto Claims Appraisals

Relevant mobile technologies, network connection management and industry-specific workflow applications are required to activate AI, automating tasks based on that data to speed up and simplify lengthy and complex processes. The auto insurance claims process is an ideal candidate for such transformation. Our industry needs to connect AI to technologies that drive action. 

Here’s an example of how a transformed auto claim experience can look to your policyholder when AI gets put into action with mobile and network technologies:

  • Pat enters his vehicle in the morning. The app on his phone activates and begins tracking his trip so that his auto insurance policy premium is calculated for only the time he is in transit, based on the policy he selected upon enrolling. 
  • On arrival at his employer’s office parking lot, Pat accidentally scrapes the side of his vehicle on a pillar. 
  • His vehicle and app automatically detect the incident and offer Pat the opportunity to submit the incident to his insurer to determine if a physical damage claim should be opened.
  • Pat decides to proceed and immediately receives a text link with instructions about how to take a few smartphone images of the damaged area and text them to his carrier. 
  • Pat is immediately notified by text that the damage is minor and that the car can be safely driven but that the repair cost likely exceeds his policy deductible by at least $500. 
  • Pat decides to file the claim and receives a text with a list of nearby repair facilities, including consumer ratings, shop certifications or specialties and availability. 
  • He taps a few links and schedules the repair, and once he arrives a pre-arranged temporary rental car will be waiting for him. 
  • Pat continues to receive status updates from his insurer until he is advised what time his vehicle will be ready for pickup or delivery, as preferred.  

Note that the steps described above begin and continue with AI-enabled decision-making and workflow management. Out of view of the policyholder, AI and digital connections are powering the parts ordering process, and the repair facility is digitally paid by the insurer within hours of the vehicle being delivered. Without these enabled technologies, a digital end-to-end experience would not be possible. But when combined with the other elements, the result is transformative, completely digital.  

Sourcing the Data That Powers AI and Drives Decisions

The relationship between the ability to reliably predict outcomes and the absolute volume of historical claims data leveraged to train the software is directly proportionate – the greater the amount of relevant data used, the better the outcome. We frequently hear from our insurance clients of all sizes that the volume of data needed to develop reliable algorithms is greater than even the largest insurers have available. CCC has processed more than $1 trillion of claims-related data, which we put to work to develop hundreds of actionable AI models. And while data relevancy is essential, another key difference in AI efficacy is the use of a combination of AI disciplines. Deep and machine learning and business rules combine to deliver the most reliably predictive, comprehensive results for faster, smarter resolutions. 

Here’s how: 

Deep learning is an AI method that uses historical data to inform which action is likely to lead to which outcome. Let’s take photo-estimating as an example. To train an AI model that can review smartphone images from a collision and predict whether a vehicle is repairable versus a total loss, the AI model needs to learn from historical data: photos of other car crashes, as well as the claims data that accompanies those photos regarding the parts, labor, cycle time and medical assistance needed for each claim. The question is: Does the AI model have enough historical data to make that prediction actionable? A few hundred images are helpful, but decades’ worth of wrecked car images and related metrics make the AI model far smarter. Another question: Can the AI model sort out the anomalies from the requisite data set? Can it learn from them?

Another key discipline is machine learning, which allows historical data to be influenced by behavioral or pattern changes that might make recent actions more likely to occur again. Let’s say you have been a Facebook visitor every day for the last five years, but more recently you’re only visiting Instagram. In this case, the majority of data would say you’re going to visit Facebook again, but recent activity would suggest Instagram is a better prediction. Why does this matter? Vehicles and parts are not static. New cars and parts are introduced continuously; if an AI solution is going to be effective, it needs to base predictions on data that can account for recent behaviors, not just historical data. 

A less sophisticated, yet foundation disciple, includes the use of rules. A rules-based approach can offer helpful predictions when historical data is not available or recent activity is not accurate enough to ensure a reliable prediction. Suppose that an inbound technical support email contains the word “urgent” in the body. A rule is triggered, and that email is forwarded to someone who can immediately act on it. These types of rules can get into extremely complex decision points, leading to hundreds of potential rules, some of which may even conflict with each other. This is why rules-based AI is an incomplete approach that can fall short in accuracy and reliability. Yet, because data and domain experience aren’t required to create rules-based AI, it is a helpful starting point that can assist companies to begin the journey of automating complex workflows such as auto insurance claims.  

See also: Auto Claims: Future May Belong to Bots

When It All Comes Together – A Reimagined Insurance Experience

When the claims experience is working in harmony as a result of automated, AI-enabled decisions and all the needed inter-company, inter-industry integrations, not only will the insurer’s customer’s experience be maximized but real hyper-personalization can be achieved, meaning that each insurer’s individual customer will enjoy an exemplary service experience in the manner and method that they expect and prefer. 

Industry transforming technology is here and ready to be combined in time to meet consumers’ evolving expectations. Insurers are in a position to connect AI, mobile and network to transform what’s possible.

Could COVID Help Life Insurance?

With vaccination programs rolling out across the globe, and cases beginning to fall exponentially, there is finally hope that the worst of COVID-19 may be drawing to a close. But while this may signal the imminent end of the pandemic itself, it is surely only the end of the beginning with regard to its long-term impact. In almost every area of life, from the political through to the economic, the transformative consequences will be felt for some time.

The world of life insurance is no exception. But while the impact of COVID-19 on many industries remains uncertain, to say the least, the big picture for the life insurance industry is a lot clearer.

Prior to the pandemic, the so-called generation gap when it comes to life insurance was a constant point of consternation for the industry. Back in the mid-20th century, life insurance policies were as common and ubiquitous as mortgages or car ownership – a standard rite of passage for younger households embarking on their journey into adulthood. This culture has almost entirely evaporated. Younger cohorts, especially the millennial generation – under new financial constraints and not necessarily catered to by traditional sales channels – had little awareness of or inclination to take out life insurance policies, and sales withered. 

Remarkably, though, the last year and a half has seen a dramatic reversal of this long-term trend. Despite a period of volatility around March and April 2020, coinciding with the initial swath of lockdowns, the MIB Life Index ended 2020 up 4% year-on-year, the highest annual growth rate on record. What’s more, this growth was driven predominantly by younger cohorts, with activity increasing in the 0-59 age range rather than 60+, in stark contrast to recent years, where any growth has been almost entirely driven by the latter group. Recent sentiment research underlines this turnaround; members of Generation Z are now significantly more likely to increase life insurance spending than other generations, with millennials following close behind.

Intriguingly, this shift started slightly before the pandemic came to America’s shores, in January 2020. Kobe Bryant’s death from a helicopter accident appears to have triggered a sharp uptick in demand for financial protection in the case of unpredictable tragedy. Then the pandemic understandably heightened awareness of mortality in generations previously unaccustomed to such perspectives. The economic hit also contributed – with many facing the prospect of losing employer group coverage.

This uptick of interest alone, however, will not be enough to bridge the generation gap in life insurance for the long haul. Consumer demand for life insurance has only ever been one piece in a larger puzzle. For some time now, the industry has been aware that re-engaging with younger market segments, while also continuing to serve its traditional customer base efficiently, will require a wholesale adaptation to more advanced technologies and digital forms of distribution. Technology and digitization – and taking full advantage of the new opportunities and business models they enable – will be key to taking long-term advantage of this renewed interest in life insurance.

It’s good news, then, that on the insurer side the pandemic has dramatically accelerated existing trends. As with many other industries, the chilling effect of lockdowns and other emergency measures on physical, face-to-face interactions has forced life insurers to dive headfirst into technology-driven approaches in underwriting and distribution methods. The transition to digital marketing, digital distribution and automated underwriting and digital policy insurance leveraging new forms of data was already inevitable before anyone had heard of COVID-19. But from early 2020, what was once a priority for future growth has become an immediate non-negotiable. New approaches to underwriting, business processes and distribution models made commercially viable by automation technology are higher up the insurance industry’s agenda than ever.

See also: 6 Megatrends Shaping Life Insurance

While nearly half of agents have reported a collapse in in-person business since the onset of the pandemic, life insurance companies across the industry have leapt headfirst into new digital technologies, tools and channels to compensate for the sharp drop in traditional methods of doing business. For example, embracing new technologies enabling real-time access to medical records and other forms of advanced data allow insurers to underwrite policies accurately even without face-to-face assessments or interactions. These advancements in the underwriting and distribution process are pivotal in future-proofing the industry, and in creating massive efficiencies at the same time.

The life insurance industry has always, by nature, been cautious in embracing technological change. But the pandemic has entirely removed the luxury of time from the equation. New technologies, new data sources and new approaches to automated underwriting that may have spent long periods in planning and testing are already live and gathering momentum. A transition to digital technology that prior to the pandemic could have spanned the next decade will now likely be complete in just a year or two.

This is no bad thing. If the industry is to take advantage of the new interest in life insurance among the young, as well as continue to service its traditional customer base in a more efficient and sustainable way, the sooner the better. The sector was already facing a challenge of modernization; COVID-19 is unlikely to change the future shape of life insurance.

What it does mean, though, is that the future is going to be here much earlier than expected. For those carriers keen to acquire first-mover advantage, the window of opportunity just became even narrower. The time to embrace new technology is now.

Insurtechs’ Role in Transformation

Given the nature of insurance, and the possibilities that data analytics and technology offer, there should be little doubt that the industry is moving toward becoming a technology industry.

It is therefore only natural that insurers are looking for ways to reinvent themselves as technology companies, running corporate-wide digital transformation projects to ensure adjustment to the changing markets and secure a competitive position in the future.

This white paper demonstrates how insurtechs are important for the development of the industry but also underlines that insurtech does not address all challenges faced when creating a future successful insurer – insurtechs are digital instruments to be used in the transformation journey, but it’s still up to the incumbent to get the real transformation done.

This paper explores how to use insurtechs to address current incumbent pain points and what to look for before entering a partnership with insurtechs.

The Insurtech Landscape Mid-2020

Given the pace of the market development, it makes little sense to provide a fully updated and detailed state-of-insurtech – it does makes sense, however, to understand the underlying nature of the insurtech landscape to examine how insurtechs are entering and affecting the insurance industry.

This understanding will provide insurers with a future outlook and enable the development of adequate strategic responses – this will also help insurers to identify if and where insurtechs can fit into insurers’ value chain.

More than 75% of total dollar investments are invested in insurtechs offering products and services within distribution, and a total of 79% of all investments are in single-line insurtechs.

Table 1: 2019 total insurtech investments
Source: Coverager 2019 insurtech investments in review

These two numbers, 75% of investments in products and services within distribution and 79% of all investments in single-line insurtechs, combined with insurtechs’ focus in the insurance value chain (see below) clearly show that insurtechs are focusing on specific areas of the total insurance value chain and not in creating new, full-fledged insurers.

The insurtechs seems to be zooming in on the areas that have the greatest business and growth potential and leaving out the less lucrative parts of the entire insurance value chain, which makes perfectly good business sense. You would only enter into industry areas with high inertia and potential for fast improvements.

Figure 1: Insurtech focus in the insurance value chain (Quarterly Insurtech Briefing January 2020)

Following the numbers from Figure 1, it appears that the structural issues impeding insurers to realize transformations at scale and speed are not addressed in particular by the insurtechs in the market.

Successful transformation of incumbent insurers requires more than a digital front end or various, isolated digital innovations – granted, it may add to the overall value provided to the customers or partners, but the underlying structural and process challenges still exist in the incumbents and still need to be redesigned for the insurer to reach the future virtual and digital state.

As shown later, some insurers are already partnering with insurtechs and benefiting from improved, isolated processes within distribution, sales, policy servicing and claims management, but very few – if any – have created a cohesive end-to-end experience for the customers and partners.

Partnering with an insurtech for a specific element of the value chain still leaves it with the incumbent insurer to realign, adjust and connect surrounding processes in an effort to create a complete customer-oriented solution.

Besides ensuring technical and operational integration, the incumbent should also carefully understand the cultural and organizational changes required when aligning and redesigning core processes.

In other words, and put provocatively, insurtechs are acting as digitally advanced middlemen or brokers – their disruption primarily lies within customer experience and service, while some leverage Internet of Things to refine pricing and improve service offering (health, home, car, travel).

Most insurtechs greatly rely on the backbone of the insurer – an important point to make and for incumbent insurers considering partnerships with insurtech to be aware about.

Successfully integrating with insurtechs

As mentioned, it does make good sense for incumbent insurers to look towards insurtechs for partnerships, as a partnership can fast-track the digital development process. Apart from being aware of the organizational changes required to make the partnership work, it is beneficial to create a gap analysis to evaluate existing competencies against competencies required to deliver on the insurer’s overall strategic direction and targets.

While looking at the elements in the value chain, and apart from identifying the gaps, noting down current pain points can detail the requirements for an insurtech partnership further.

A starting exercise can be mapping the insurer against the “three-speed” insurer model to have a point of departure in defining the gaps and requirements for an insurtech partnership, followed by identification of current pain points throughout the value chain.

The three speeds of insurers

Insurers can broadly be divided into three different categories, reflecting their current digital strategy and ability to react fast to changes in the market from both users and competitors/partners.

Table 2: Insurers in the industry can be broadly divided into three different ‘speeds’

You can fill out Table 3 below to get an idea of how fast your insurer is capable of reacting to market changes.

Both internal factors as well as external factors are evaluated, as external factors play an important role in an insurer’s commercial success and viability.

Process change refers to the ease of changing internal processes within the insurer, such as claims services, approval processes, etc. An important part of innovation in insurance is to offer a seamless and very fast experience for the users, which requires incumbent insurers to change their existing processes – this will not be a significant issue for insurtechs due to their startup nature and very quick decision processes.

Innovative incumbents acknowledge this need and change their internal procedures to accommodate this – but they are still far from the nimbleness and flexibility of the insurtechs because the innovative incumbents require the innovations to integrate with existing systems and processes.

The rationale behind product changes (agility) is similar to the process change described above but needs to be treated separately, as some products and services can be integrated at arm’s length and thus require less integration and internal adjustments to work.

Organizational agility is the insurer’s ability to react on changes, internal as well as external, and is generally an indication of how fast the organization can get projects approved and begin implementing them. It’s also an indicator for how fast the projects can be implanted once approved.

Table 3: A simple framework to assess the insurer’s current level of development and transformation speed

The organizational agility depends on the formal hierarchical structure and numbers of approval nodes each change request must pass before finally being approved and ready to implement.

Insurtechs have a flat structure with very few formal approval nodes, which means they’re able to approve and begin implementation of changes almost immediately, where laggards are at the opposite end of the spectrum, being slowed down by a large number of approval nodes and long- lasting approval processes.

The innovative insurers are placed in between, again because they’ve realized the need for agility and adjusted internal structures and processes to accommodate this somewhat.

The level of an insurer’s digital flexibility is based on how open and flexible the IT systems are, especially the customer facing systems.

The laggards are basing their development almost purely on legacy IT systems, which most often are inflexible monolithic structures, making it a long process to carry out changes, let alone introduce products and functionalities.

See also: Secret to Leadership in Insurtech Innovation

Innovative insurers have typically been through one or more digital transformation projects, making them far nimbler than laggards in terms of IT connectivity and development, but they still lag behind the insurtechs, who have full control of each and every bit in their digital control room.

It takes cutting-edge talent to drive innovation through, regardless of company and industry, and here again the insurtechs are in front, as they wouldn’t have been insurtechs if highly competent people hadn’t gotten together to create the insurer.

Innovative incumbents are partly innovative and forward-reaching because they’ve managed to hire the right key talent to develop their new digital universe, but even the best talent is bogged down by the existing organizational structures and processes.

Even laggards with exceptional talent will find it difficult to perform due to the organizational structures and systems.

Given this, it’s unlikely that they’re able to attract the right talent and in the right numbers as the right talent is focused on deliveries, which is too complex in laggard insurance companies.

The presence of talent, and the insurer’s willingness to invest, is key to determine the insurer’s level of innovation.

Laggards don’t possess the talent and cannot have an innovation strategy due to their choice on building evolutionary on existing IT systems, where innovative incumbents very much have an innovation strategy, as this is the basis for their future development.

The delivery on the innovation strategy is still not as fast as with the insurtechs for the same reasons.

Mapping current pain points

A quick analysis of the insurer’s current speed and flexibility, combined with the identification of current pain points, sets the basis for understanding what kind of insurtech would add the most value in a partnership.

Pain points are generally specific processes or procedures that cause customers – or the organization – difficulties in getting their job done, whether it is buying a policy from the insurer, filing a claim or encountering bureaucratic red tape stopping marketing or sales processes required to keep – or establish – a competitive market position.

A fast and easy way to identify the pain points throughout the organization is to use the value chain and for each element to write down what is causing delays, inflexibility, challenges or downright customer issues.

Figure 2: Examples of mapping pain points to the elements in the insurance value chain

It is often a good idea to identify the pain points with colleagues to get a more accurate and unbiased view of the pains throughout the organization – done alone, the exercise can be biased toward specific areas that may not be representative for the organization.

These two small company analyses — the speed of the insurer and current pain points — provide a great starting point for understanding how insurtechs can help in the transformation of the insurer to a virtual and digital insurer. The next step is to search the marketplace for insurtech companies that offer products and services that match the insurer’s planned transformation journey.

Benefits of partnering with insurtechs

It should already now be clear that partnering with insurtechs can make very good sense for the insurer to speed up and improve the digital transformation of the incumbent. There are at least four distinct advantages for insurers partnering with insurtechs.

Figure 3: Four major benefits for insurers by partnering with insurtechs

Business development

An obvious advantage of partnering with a tech- savvy professional is the opportunities it creates for new ways of selling existing products and introducing new products to the market.

However, as previously discussed, many insurtechs are building products and services that focus on optimizing existing business processes, including operational efficiency and claims costs savings (direct as well as indirect through reduction of operational expenses).

Business development can therefore be both in terms of increasing revenue through new sales channels or new products and in terms of improving business processes and hence reduce operating and claims costs.

Organizational advancement

It’s important again to underline that successful integration of an insurtech partner requires significant adjustments of the insurer’s organization to fully cater to new processes and products that are introduced through the partnership.

This is, of course, especially true when the insurtech’s product is focused on internal process development, where the full participation of the organization is required.

When done correctly, these organizational advancements will lead to a changed organization with a broader understanding and acceptance of new and more efficient ways of working.

Creating a future state of business

The organizational changes pave the way for creating a more advanced organization, capable of dealing with complex partnerships going forward.

This will not only benefit potential future insurtechs but also improve the way the incumbent insurers are handling their partnerships – the learnings from the insurtech partnership enable the insurer to revisit existing agreements with fresh eyes and new ideas on how to optimize for the future.

The insurtech partnership helps direct the attention on a future state, and a successful integration will instill a “can-do” attitude in the organization.

Working with insurtechs creates a source of continuous learning and organization development, enabling the insurer to stay competitive.

Supporting a new breed of companies

Apart from direct business and organizational benefits, partnering with insurtechs sends a strong message from the insurer to the market, a message of being at the forefront of the industry, which increases the insurer’s ability to attract talent, partners and customers.

Furthermore, the insurtech partnership actively supports the development of the next generation of insurers and partners, thereby supporting the development of the industry long into the future – the insurer leaves its mark on the industry.

Will all insurtechs do?

There are several areas the incumbent insurer should be aware of before venturing into a partnership with an insurtech.

The insurtech must be a real new technology service/product provider, and partnering with it should demonstrate a clear business leap for the insurer, as opposed to an incremental change.

Incremental changes and improvements are required and should be part of any company’s improvement programs, but to reap the full benefits, the insurtech must offer a truly innovative leap for the insurer.

Partnering with the insurtech should match the company’s current strategic direction – or actively be part of a new strategic direction set by the management. It makes little sense to spend time, money and organizational effort to partner with an insurtech if the partnership will not take the incumbent insurer a great step toward the set strategic targets.

Following the discussion on organizational learning and culture, it’s an extreme benefit if there’s a people/culture match even before the partnership is agreed upon.

How to integrate: four basic ways

It’s imperative to understand that this is two very different worlds: an agile and very modern small-business environment and the more bureaucratic and institutionalized environment of the incumbent insurer. At some point, these must match to make the partnership a success, and positive vibes between the partners beforehand will ease this process.

There are different ways of considering structuring the partnership between the insurer and the insurtech, all of which have different advantages and disadvantages to consider – and to be aware of when the partnership hits the insurer’s organization.

Figure 4: Four different ways insurers can integrate or partner with insurtechs

Arm’s length

Partnering with an insurtech and managing the relationship at arm’s length makes it little more than an external distribution partner or an outsourced claims management function. It is very easy for the insurer to administer, as there will be minimal disturbance and interruption of the daily operations, processes and organization.

The arm’s length will have very limited transformation effect on the insurer.

Satellite integration

A high level of systems integration with little organizational integration is typical for insurtechs that connects to the insurer via APIs or using the insurer’s microservices for a specific set of transactions.

In this scenario, there will be little organizational red tape, but some IT challenges can be expected as the IT unit must work and integrate with the insurtech.


Insurtech partnerships with little systems integration and high levels of organizational integration typically rely on the technology from the insurtech and require a high level of cooperation and coordination between the insurtech and the insurer – advanced use of artificial intelligence for underwriting or fraud detection could be examples of this, where the insurer in many cases only needs to export simple data sets for the insurtech’s solution to work with.

This can have quite a few organizational challenges as the incumbent organization can get the “not invented here” syndrome and feel the insurtech is coming and interfering with the daily work.


Integrating the insurtech into the insurer will most likely be the partnership model with the biggest return on investment, but at the same time this model poses the greatest challenges, as both systems and organizations must be included and aligned with each other.

It’s safe to say the most significant risk is a clash of cultures between a well-established, well-regulated, experienced incumbent insurer and a newly founded, agile, dynamic and “free-of-rules” insurtech.

See also: Planning for the Unknown Unknowns

Performance indicators – the cornerstone of success

The organizational and cultural strain caused by introducing external parties to the organization – or simply caused by digital change initiatives – can be somewhat reduced by creating a set of clearly articulated targets and goals for the company, the units, the teams and the individuals.

To be successful, the targets and goals must be connected, so the teams and units will be depending on each other to achieve them. This will initially force collaboration that, over time, if managed, will reduce the cultural tensions – working toward the same target is a strong motivator.

A fast way of setting up a framework for target and goal setting is to use the principles from the balanced scorecard, illustrated below.

Figure 5: The balanced scorecard high-level structure Source: Balanced Scorecard Institute

One of the major strengths of the balanced scorecard is that targets are set for the organization as a whole and then cascaded down to the business units, teams and individuals. This provides an overview of how each goal and target is supporting the organization in achieving the end targets.

Given the insurer already has a set of financial performance targets, the balanced scorecard is used to set underlying goals for the units working with the digital transformation and insurtech partnerships, all aiming at supporting the insurer in reaching the overall targets.

This approach can further be used to create business cases for investments and calculate return on investments, because of the specificity of the targets and goals required to create a successful balanced scorecard.

When setting the goals in the scorecard, it can be defined how investments help move the performance indicators toward the goals and therefore illustrate the value of the investment.

Final thoughts

Insurtechs are not the only answer to transforming incumbent insurers into virtual and digital insurers, but they may be able to play a very important role for the insurer in achieving the virtual vision.

When embarking on a continuous transformation journey, it is vital for insurers to keep the overall picture of the organization, its interdependencies, culture and modus operandi in mind.

For insurers to become agile, virtually and digitally competent organizations, they must ensure proper adjustment and development of the underlying key systems, which include organizational structure, management processes and culture.

Merely partnering with insurtechs or other companies does not make these challenges disappear, though – and conquering these challenges are key for future and sustainable success.