As customers press insurers for the best possible rates -- especially in the wake of COVID-19 -- companies must map their position against competitors to be able to offer optimal prices. The market offers several online tools and platforms to compare general insurance quotes based upon the details that prospective customers provide. However, for insurers that wish to compare their quotes with competing products in the market, not just in terms of price but in terms of attributes such as coverage and benefits, these platforms and tools are insufficient.

A 2015 survey by Earnix of North American insurers engaged in personal lines, almost every company surveyed (93%) performs rate structure and rate competitive analysis. Other common types of competitive analysis include product features (79%), coverages and contracts (70%), financial metrics (58%) and underwriting guidelines (56%).  

To perform such multifold comparisons, insurers require access to a business intelligence solution that is interactive and allows users to analyze across different consumer segments and product/policy features. Such a business intelligence (BI) tool should not only be capable of extracting the quote information from various raters/agents/online-platforms/competitors but also consolidate this information so insurers can compare other metrics, by:

• Providing a clear understanding of the standing of client vs. competitor quote, by dollar amount. 
• Generating insights to develop predictive models that can assist in increasing the conversion rates of policies.
• Focusing on the binding and issue rates, to measure success.
• Assisting in cross-selling, marketing and targeting of customers from other lines of business.

This article provides a framework for developing a quote comparison BI solution and contains metrics for assessing competitiveness across multiple lines of business.

DISCLAIMER: Because insurance consumers often purchase home and auto insurance at the same time, while building a quote comparison BI solution it is essential to include the competitiveness of both lines together by combining multiple line of business reports into one. This entails setting up specific data warehousing processes in the background, which are needed to power up the visualizations in the dashboard/report output.  

Key Metrics to Use in This Rating Methodology

An insurer trying to compare the pricing of its competitors needs to establish a set of metrics to rank different quotes for a given consumer profile, created by analyzing past policy purchases and consumer details data collected by brokers.  

One of the several challenges is that the competitiveness information received for quotes belongs to a single business line. This information is sometimes categorized and not in absolute numbers. In most cases, a carrier gets the following values directly: its premium, low/median/high carrier premiums and rank for a quote. Thus, there is a problem with joining auto and the home quotes to form a combined quote.

While a carrier can determine its own combined premium (auto premium + home premium), it cannot do the same for the low/median/high carrier premium info. For instance, one does not know whether the carrier that quoted the lowest auto premium is the same carrier that quoted the lowest home premium. In fact, the combined low premium (set to low auto + low home) is, in most cases, going to be lower than the actual combined low premium. The opposite is true for combined high premium info; the estimate will uniformly be higher than the true high combined premium. The combined median should be higher than the actual combined median just as often as it is lower, so the overall median combined premium should be roughly in line with the actual combined medians.

The carrier performing the rate comparison can use different approaches to determine the best estimate of all the competitiveness measures used in the views of a single line of business. Some of the metrics used in this approach are:

• Ranks based on the premium dollar value quoted for both auto/home.
• Categories based on the ranks where the insurer is No. 1 in a category, and rank sorting among the top few ranks.
• Number of carriers quoted for that policy. 
• Difference in premium dollar value quoted for both auto/home and the low/median/average/high of all the premiums quoted.
• The average rank based on premium dollar value quoted for each line of business.
• Percentage of quotes issued. Issuing is the act of completing a quote and binding a policy (generating a policy number). The issue percentage (issue rate/close rate) is the percentage of quotes in which a policy is issued at the end.

See also: Best AI Tech for P&C Personal Lines

Ranking Insurance Quotes

The ranks given to competitors do not have the information about the number of competitors quoting for a given consumer persona (or a consumer). P&C carriers can adapt a new ranking methodology that identifies the most robust metric that combines rank with the number of carriers quoting for a given consumer persona/profile. For example, consider a scenario where a customer gets three auto insurance quotes from his independent agent. Here, to be ranked second isn’t as impressive as being ranked second out of 10 quotes. The following three rules can be used by carriers when determining ranks in their dashboards:

Expected win rate: Expected proportion of Rank 1 quotes.

Rank scale metric: This is essentially distance from “expected win rate.”

LOB filters constraint rule: Consider an insurance carrier offering home and auto and wanting to be able to offer them alone or in combination. The BI solution for price and rank comparison should provide filters for visualizing such combinations.

Analysis and comparisons

Geography-Level Analysis 

One can showcase metrics like numbers of quotes and conversion rates, etc. Analysts have access to line of business and geography-level filters like state and county, urban vs rural, etc.

Rank Level Analysis

Here one can show product performance based on ranks for different lines of business for metrics like quote vs. pre-quote.

Line of Business Analysis

Each line of business has specific attributes -- for example, driver age and vehicle age for auto insurance -- so one needs line-of-business-level views for auto and home and a combined graph.  

Competitive Market Analysis 

This involves relative quote ranking to understand the insurer position concerning competitors, analysis around quote distance from average market price and segmentation analysis to understand which insurers are incredibly expensive.

Price Elasticity Analysis 

This focuses on price sensitivity and customer profile. Segmentation analysis helps understand the pace at which the rates can increase or decrease to accept the change. Similarly, different studies can be carried out for the sales and marketing team to increase the retention of profitable customer segments.

Price Optimization 

Price optimization is more of a prescriptive analytics approach. A scenario-based analysis can help check price sensitivity by market segments and build a reusable platform for carrying out state and countrywide optimization analysis.

Quote & Coverage Optimization and Customer Segmentation 

An insurer may not offer the best price but may still bind the policy because of better coverages, or the insurer may have the best price but not win the business. These are the scenarios that a carrier needs explicitly to look into as they will help the carrier while quoting new customers.

Location-Based Analysis

Location has a significant effect on premiums. Differences in competition, state and local rules and cost of living account for this. Insurers take into consideration this information when they decide on the premium dollar value. For example, in a region with higher car theft rates, one may pay a higher premium than a place where car theft rates are low.

See also: Foundational Tech for Personal Lines

Conclusion:

With COVID 19, pricing has become more crucial than ever as it can become a great source of competitive advantage. A useful quote comparison tool that encompasses various metrics of comparisons and different data elements can lead to better customer acquisition and retention. The visualizations provide an effective way to stay on top of customers' expectations and price right to keep your organization ahead of competitors. Deploying data analytics to integrate home and auto and customer personas can help deliver the right products and the correct prices to existing and prospective customers.

However, to kick off this transition, it is crucial for insurers to carefully collate a list of metrics to compare, rank the insurance quotes to take into account the number of competitors and then perform the needed analysis. The best way to determine this is through a comprehensive, systematic audit of the current quote comparison process. A carefully planned audit will help insurers to: 

• Identify gaps in the current quote comparison process. 
• Identify the right personas and the right metrics.
• Prioritize the customer population who are more likely to expand the wallet share and purchase a policy.
• Build a single source of truth of quote information for effective pricing decisions

Leadership is a necessity in times of comfort and crisis. But now is the time for the insurance industry to lead by subsidizing the cost and distribution of a specific necessity: disposable face masks. Now is the time for insurers to be true to their respective brands by respecting the urgency of the present, so they may respond to the challenges of COVID-19 by presenting the public with ample supplies of personal protective equipment (PPE).

Leadership of this kind is a lifesaving measure, which also offers immeasurable savings. The alternative is wrong as a matter of morals and money, because when an act does not make sense, when an act violates common sense, the cost comes in the form of many dollars and cents; billions of dollars in medical bills for millions of patients nationwide.

Were insurers to subsidize one of the least expensive but most effective ways to stop the spread of COVID-19, were insurers to advance the issue of public health by promoting this issue on the outside of every face mask, were insurers to show their faces to the public, the reaction by the public would be huge.

An insurer’s logo would be a mobile advertisement. Truth in advertising would no longer be a contradiction in terms. Not when it would be impossible to deny what people could see: PPE in action.

According to Vitali Servutas and Brent Dillie of AmeriShield:

“Compliance governs the insurance industry as much as it inspires the industriousness of our commitment to public health and personal safety. By complying with the rules of the CDC and the Berry Amendment, we give hospitals, businesses and consumers a safe, affordable and convenient means of protection against COVID-19. Disposable face masks are essential to winning this fight, which is why insurers should support or subsidize the use of these masks for everyone.”

I agree with this statement because the words speak to a third “P,” patriotism. 

Helping Americans by increasing jobs for Americans is good for all Americans. This policy is wise, too, because it highlights the value of oversight and quality control. Put another way, what works well for consumers is a policy that works to expand wellness.

Insurers have every reason to support this policy, given the nature of the pandemic and the pandemic’s toll on the nature of how we live now; of how we live to survive, for now.

We need protection, yes, but we also need to know we share the same goal: that we are in this fight together, that we will hang together, that we are and will be stronger together.

See also: Insurance CEOs Spec Out a Post-COVID World

Insurers have the resources to achieve great things. If they summon the will to do this one thing, protect the public by providing the public with disposable face masks, then insurers will achieve greatness. 

History will record these things, just as people now living will tell future generations about the good works that make insurers institutions of greatness.

The public welcomes this moment.

Today, health plans (also referred to as payers) are busier than ever. They strive to deliver efficiency, great customer and stakeholder experiences and improve care outcomes. To do this, they need to use more data, and they have much data at their disposal. But what are they missing?

They can be missing key patient information; that is, they don’t see the whole picture. The insurance industry is no stranger to data gathering, coding, tagging, analyzing. In addition to a long history with data, in the recent decade or two the industry has seriously upped its game in terms of converting legacy data to newer usable forms and has upgraded systems to establish true master data management infrastructure (whether in-sourced or in/out-sourced). We have even seen a flurry of third-party data use and the occasional implementation of new ways to digitize unstructured data. All of this is here to stay, which is good for data purveyors, health plan analysts and application developers and for the business of cost management and reimbursement. Providers and patients alike will benefit.

But the challenge remains: Health plans can’t keep up with everything all the time. And they cannot use all of the data as thoroughly as they want to. 

I advise health plans to take stock of their needs and assess whether current data sources will get you where you need to go. If not, additional patient level data — identified or de-identified — from a new outside source could very well be in order. 

Let’s review some of the cases where a health plan could tap into some of the available ecosystems to solve key challenges.

Data Efforts Are Getting Budget Dollars

In 2016/17, it was estimated that the life and health insurance industry spent over $3.5 billion on marketing and advertising activities. (Estimate is compiled from more than one source and may include some commission payments). 

On top of this, according to Novarica, Gartner and other watchers, the industry plans to spend hundreds of millions of dollars a year through the 2020s on data and analytics talent, technical infrastructure that supports AI and machine learning, advancements in digital capabilities and modeling, as well as improving content and communication management systems. Throughout, every functional department of a health plan will seek data-driven understanding and confidence. 

Sample Payer buckets illustrated below: 

Large Payers (Top 10): In-house data management leaders and large-scale analytics teams at large payers often can be funded to focus on select hot topics of the day, and sometimes they build things themselves. The opportunity for larger payers is to acquire an assortment of sample datasets in the size and with necessary permissions so they can focus on what they are good at: the analytics, evaluation of new product designs, improvement to sales plans, sales enablement and sales effectiveness, negotiating network contracts (think value-based care) and delivery of care.

Next 100 Payers: While these payers have smaller in-house tech and analytics teams, they can still have resources in terms of staff and dollars to spend on services or data. They might find it very useful for a fixed amount of time to engage third-party data sources so they don’t have to commit to hire permanent staff. I have seen many engage analytics expertise to go with it, or buy/license just the data.

The rest of the market: As we move to smaller, regional or independent health plans, often I see that they have small in-house teams dedicated to data management and small teams dedicated to analytics. (A team might be as small as two or three persons.) It is not uncommon that they outsource part of their data management and data analytics capabilities. They tend to have more updated technology platforms and can easily acquire third-party data on demand, plugging it in quickly, to complement their curated internal data sets.

See also: Overcoming Human Biases via Data

Use Cases Abound

In general, richer patient-level data can help health plans address needs in two big categories: market segmentation and risk management. Below are market trends that drive needs in these categories, with an opinion as to where the opportunity lies for helping plans address them. Please share your thoughts with me in the comments section below.

Good people, friends and former colleagues, are losing their jobs as big insurance companies lay off staff. The sliced tether to the mothership has some considering making the jump to insurtech. As a co-founder in the insurtech space with a corporate background, I’ve been getting a lot of calls, and answering the same set of questions: What is the startup scene like, who is hiring, how to get started?

These are logical questions. I even have some decent answers.

These are also the wrong questions. They’ll help you find a job, but they won’t help you understand if you’re going to be excited to get out of bed in the morning or whether an entrepreneurial job slowly crushes you into desiccated powder.

The right question isn’t about logistics – it’s about the internal transition you’ll need to make, and whether you want to live that change.

The right question is: Who do I need to become to thrive in insurtech? (Or really, any corporate to entrepreneurial transition.) 

By thrive, I don’t mean start a unicorn. If we knew the steps to do that, 75%-plus of venture capital funds would not fail to make a profit for their investors. I also don’t mean wantrapreneuring – turning not doing into a career. Wantrapreneuring is skating from meetup to meetup, asking for lots of advice about what to do (then pushing back with a strong opinion of how it should be done, all the while not… doing).

I mean, doing the work. Finding an idea. Talking to customers. Convincing a co-founder or two and a team to join you. Or joining the team. Designing the product. Checking the font on every piece of customer communication. Figuring out why your freaking payroll vendor’s system doesn’t just WORK. 

And enjoying it. Coming into yourself in this space. Feeling like every challenge stretches you in a new direction. All the while handling the emotional extremes (which I guarantee are rawer and realer than corporate).

So, having had a corporate career before becoming an entrepreneur, here’s my read on the person you’ll need to become:

A shipper, not a soother

You know all those meetings to get opinions on a project before you actually start it? Aimed a little at understanding what your colleagues know, and a lot at tamping down later aggressive politics from people who feel left out? 

Just stop. 

Draft something, share it with your teammates, tear it up and make it better with their feedback and SHIP IT! 

The scales tip the other way here – the issue isn’t that you might offend by putting something on paper, it’s that you’ll never get to your destination if you don’t complete anything. (See wantrapreneur, above).

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

I promise you it’s leftover corporate-induced anxiety that’s preventing you from shipping. And you 100% need to find a way to force through it in the entrepreneurial environment. So ship the pitch deck, the blog post, the story, the code. Relentlessly focus on your own output. 

(Also, if you don’t write it down, or type it, or draw it, or record it, it doesn’t count. In your head is not done. So do it.)

A no-seeker, not a yes-orchestrator

You know the pre-meetings? The ones you do with your boss’s seven peers to get their input and objections before the big leadership meeting? Your goal is to avoid a no from the big boss, so at least you can keep moving. 

That’s not a model for a startup. 

Of course you should get lots of feedback (mostly from customers), and of course you should take your partners’ politics into account. 

However, the biggest gift in startup life is a quick no. 

The biggest gift in startup life is a quick no. (I said it again – this one took me too long to learn.)

And it’s amazing how many people won’t have the decency or understanding to give it to you. A maybe is not a yes. A maybe does nothing but eat up runway. When you’re small, you’re surviving on a shoestring and updrafts of hope. You need to find all-in, strong-yes partners. 

And if you’re working hard for the yes that’s not coming, these aren’t your people. Sorry. 

A lightning rod, not a moderator

In corporate life, being someone with a “strong personality” will show up in your performance review. “Tone it down,” they say. “Watch the humor,” they say, until you realize you’ve risen in the ranks by sanding down every corner that makes you, well, you. Your personality, your opinions and your willingness to argue something from the heart are the cost of fitting in. 

In the startup world, nobody funds boring. Nobody joins boring. Nobody takes a chance on boring. Average gets you nowhere. Inoffensive is a lack of conviction. 

Be prepared to own your ideas, your journey, your very self and argue them strongly. Don’t play to the crowd. Better to irritate a few people if it means pulling the ones who can help you into your slipstream.

A doer, not a delegator

Early stage, there’s just too much work and nobody to do it. You can’t set up half your payroll system, design just the principles of a user experience or draft an outline of a letter to a customer – these aren’t partially done – they are an absolute waste of time precisely because they are incomplete, and therefore unusable. 

You can’t delegate completion when there’s nobody to delegate to. Do your work all the way to the end. Let go of the perfection of corporate life and the 87 rounds of reviews, and content yourself with a customer letter you think you’d understand and with a quick proofreading. 

Oh, and delegate complete tasks, not fragments. You need a team that can also finish their work.

See also: Step 1 to Your After-COVID Future

Transition means change

I don’t buy the arguments that people are either successful in corporate environments or in entrepreneurial environments. That’s accepting a world in which none of us can learn and grow, and in which we’ll never succeed at anything we didn’t try in our 20s. It’s nothing but a package of hubris and negativity all mixed up together. 

It is true, though, that corporate and entrepreneurial environments test us in different ways. If you have a corporate job and you want to work at or start a startup, can you find a job or can you start a company? Of course you can, given time and resources. 

But can you thrive? You need to be willing to change.

Becoming an entrepreneur is just that, a becoming.

Entrepreneurship strips away our masks, for founders and for team members, both. The fate of the business is in your hands. Your work stands for itself. You stand up for yourself. 

So, don’t overweight your thinking to whether you can find a job in the entrepreneurial world. Think about who you’ll need to become to thrive in that space. Does your heart sing with delight when you think about becoming that person? 

You, and the people you will work with, deserve that.

In just about any role you may fill in your business, there are a consistent handful of skills necessary to succeed. Chances are, you have a natural gift for some of them. Likely, this gift is what attracts you to any particular role in the first place. However, many of the skills you need must be developed, nurtured and maintained much more intentionally.

How do you get to “mastery?”

There are many theories as to how you master any particular skill. You’ve likely heard of Malcolm Gladwell’s 10,000-hour rule. I’m a huge fan of Gladwell, but I struggle buying into this rule in a literal sense. If there are 2,000 work hours in a year, simple math tells us it takes five years of full-time work to master a skill. Multiply that by the number of skills required for a role, and it sounds overwhelming to me. But who am I to question?

Maybe the issue here is understanding the definition of what it means to “master” a skill. Does mastery mean you are world-class? Should skills be categorized in some way to help determine the effort necessary for mastery? For example, it’s probably a much different path to mastering the violin at a world-class level than it is to merely stand out from your peers with your presentation skills.

This subject’s details and intricacies are WAY beyond my pay grade, but there is a path to acquiring new skills I completely buy into. As you think about any particular skill, we can all be placed into one of four categories:

1. unconsciously incompetent
2. consciously incompetent
3. consciously competent
4. unconsciously competent

We all must

1. identify the skills necessary for our success;
2. be honest about which category/stage of competence we fall into;
3. focus on what it will take to move us to the next stage; and
4. spend intentional and consistent time on the effort.

Take inventory

Stop for a moment and list the three skills most important in your role. Yes, I know it takes more than three, but let’s leverage Pareto’s Principle and focus on the most important.

If you are a producer, some skills to consider would be listening, presenting, questioning, learning (technical knowledge and business acumen), writing, storytelling and handling objections.

If you are a leader, skills you may choose to focus on include communication, creativity, vision and purpose, motivation, planning, problem-solving, organization, time management, delegation, empathy and strategic thinking.

If you are a marketer, the skills that help you excel at what you do may include knowledge of your target audience, storytelling, creativity, writing, analytics and communication.

Okay, now that you have identified your critical skills, let’s figure out in which stage your current skill levels fall.

Unconscious incompetence

At this stage, we don’t know what we don’t know. Not only do we lack the ability to perform the skill, but we also may not even be aware of (or simply be in denial of) the skill’s importance.

Talk about a blind spot in your performance! How dangerous is it to be oblivious to being incompetent at something for which you have no appreciation or awareness of its importance?!

You may not even be able to evaluate yourself for skills in this stage effectively. Because you don’t know what you don’t know, there may be skills you need you aren’t aware of or don’t see as important.

Find someone who does what you do who seems to be at the top of their game and run your identified list of skills past them to see what they feel you may be missing. Better yet, run your list past several people to get a well-rounded list.

See also: How to Outperform on Innovation

One critical step you can’t look past in this stage is to remain open-minded and buy into the importance of skills you were previously unaware of or considered less than important. The most significant factor in how quickly you progress from this stage is creating the motivation to learn the new skill.

Conscious incompetence

This may be the most frustrating stage. In this stage, you are painfully aware of the skills you need and the intricacies of each, but you also know you kind of suck at them. To push through this stage, be prepared for significant frustration; you will make A LOT of mistakes.

The key in this area is to properly define success. Success won’t yet be defined in successfully performing the skill (that is what moves you to the next stage); it will merely be in getting in the practice necessary to start overcoming your incompetence.

Define success each week based on the time spent improving each skill. Maybe even define success based on the number of mistakes made – I’m serious.

Conscious competence

This is the stage where the hard work starts to pay off in measurable results. You now know how to do something and do it well. However, despite the tangible and positive results, it still takes a concerted amount of concentration to produce those results.

The key to moving through this stage is to break your skill down into a defined process and repeat it over and over and over again.

Unconscious competence

Now, you are reaching the promised land, my friend. You get here due to your commitment to the skill and the repetitive, sometimes mind-numbingly monotonous execution of the process.

By the time you get to this stage, you have had so much intentional practice that the skill becomes “second nature” and can be performed easily, almost without thinking about it. When you get to this stage, others will look at you with envy and assume you are just “naturally gifted.”

You can choose to let them believe that. Or you may choose to share the lessons you’ve learned and help set them on a similar path you have followed. 😏

Resolve to improve

We should never wait for a date on the calendar to start our path to improvement. However, we conveniently have one quickly approaching.

I do question whether it takes 10,000 hours. Maybe it does to truly master certain skills at a world-class level. However, I don’t know that world-class status is necessary for most of us.

It’s a bit like the two campers who come across a bear. While one camper stops to put on his running shoes, the other asks, “You don’t think you can outrun a bear, do you?” To which the other replied, “I don’t have to. I simply have to outrun you.”

See also: Advice to Early-Stage Startups on Pricing

Don’t become overwhelmed by the idea of becoming world-class. Just focus on performing your critical skills at a higher level than a majority of your competition and keep improving on those skills over time. This will give you all the dominance you need.

You can find this article originally published here.

External attacks on companies result in the most expensive cyber insurance losses, but employee mistakes and technical problems are the most frequent generator of claims by number, according to a new report from Allianz Global Corporate & Specialty, Managing The Impact Of Increasing Interconnectivity – Trends In Cyber Risk. The study analyzes 1,736 cyber-related insurance claims valued at $770 million involving AGCS and other insurers from 2015 to 2020.

The number of cyber insurance claims AGCS has been notified of has steadily risen over the last few years, up from 77 in 2016, when cyber was a relatively new line of insurance, to 809 in 2019. In 2020, AGCS has already seen 770 claims in the first three quarters. This steady increase in claims has been driven, in part, by the growth of the global cyber insurance market, which is currently estimated to be $7 billion, according to Munich Re. 

AGCS started offering cyber insurance in 2013 and, in 2019, generated more than EUR 100 million in gross written premium in this segment. There has been a 70%-plus increase in the average cost of cybercrime to an organization over five years to $13 million and a 60%-plus increase in the average number of security breaches.

Losses resulting from external incidents, such as distributed denial of service (DDoS) attacks or phishing and malware/ransomware campaigns, account for the majority of the value of claims analyzed (85%), according to the report, followed by malicious internal actions (9%) – which are infrequent but can be costly. Accidental internal incidents, such as employee errors while undertaking daily responsibilities, IT or platform outages, systems and software migration problems or loss of data, account for over half of cyber claims analyzed by number (54%), but, often, the financial impact of these is limited compared with cybercrime. However, losses can quickly escalate in the case of more serious incidents.

The cyber risk environment is not expected to become any easier in the future. Businesses and insurers are facing a number of challenges, such as the prospect of more expensive business interruptions, the rising frequency of ransomware incidents, more costly consequences of larger data breaches given more robust regulation and litigation, and the impact from the playing out of political differences in cyber space through state-sponsored attacks. 

The huge rise in remote working due to the coronavirus pandemic is also an issue. Displaced workforces create opportunities for cyber criminals to gain access to networks and sensitive information. Malware and ransomware incidents are already reported to have increased by more than a third since the start of 2020, while coronavirus-themed online scams and phishing campaigns about the pandemic continue. At the same time, the potential impact from human error or technical failure incidents may also be heightened. 

While exposures are rising, the COVID-19 outbreak cannot yet be said to be a direct cause of cyber-related claims. AGCS has seen the first few cyber claims that can be indirectly attributed to the COVID-19 landscape, including ransomware attacks that can be linked to the shift to more remote working. However, it’s too early to confirm a broader trend.

See also: The Missing Tool for Cyber Resilience

Ransomware threats surge

Already high in frequency, ransomware incidents are becoming more damaging, increasingly targeting large companies with sophisticated attacks and hefty extortion demands. There were nearly half a million ransomware incidents reported globally last year, costing organizations at least $6.3 billion in ransom demands alone. Total costs associated with dealing with these incidents are estimated to be well in excess of $100 billion.

Business interruption and digital supply chain vulnerability growing

Business interruption (BI) following a cyber incident has become a major concern for business. Analysis of cyber claims by AGCS shows that BI is the main cost driver in the majority of cases. Whether ransomware, human error or a technical fault, the loss of critical systems or data can bring an organization to its knees in today’s digitalized economy. 

Dependency on digital supply chains – both for the delivery of services and the supply of goods brings numerous benefits. Shared technology-based platforms enable data to be exchanged between parties, automate administrative tasks and transport products on demand. However, such platforms can potentially create a chain reaction ensuring a BI cascades through a whole sector. If a platform is unavailable due to a technical glitch or cyber event, it could bring large BI losses for multiple companies that all rely and share the same system.

Data breaches and state-sponsored attacks

The cost of dealing with a large data breach is rising as IT systems and cyber events become more complex, and with the growth in cloud and third-party services. Data privacy regulation, which has recently been tightened in many countries, is also a key factor driving cost, as are growing third-party liability and the prospect of class action litigation. So-called mega data breaches (involving more than one million records) are more frequent and expensive, now costing $50 million on average, up 20% over 2019.

In addition, the impact of the increasing involvement of nation states in cyber-attacks is a growing concern. Major events like elections and COVID-19 present significant opportunities. During 2020, Google said it has had to block over 11,000 government-sponsored potential cyber-attacks per quarter. Recent years have seen critical infrastructure, such as ports and terminals and oil and gas installations hit by cyber-attacks and ransomware campaigns.

Prepare, practice and prevent

Preparation and training of employees can significantly reduce the consequences of a cyber event, especially in phishing and business email compromise schemes, which can often involve human error. It can also help mitigate ransomware attacks, although maintaining secure backups can limit damage. Cross-sector exchange and cooperation among companies is also key when it comes to defying highly commercially organized cybercrime, developing joint security standards and improving cyber resilience. 

See also: Essential Steps for Cyber Insurance

The COVID-19 landscape brings new challenges. With home-working widespread, security around access and authentication points is critical, but organizations should also ensure there is sufficient network capacity as this can have a significant impact on lost income if there is an outage. 

For more key takeaways from the report, please visit this page.

Who Is Liable When a Driverless Car Crashes? Paul Carroll, Editor-in-Chief of ITL Now that truly autonomous vehicles are starting to appear on roads, the insurance industry will be called on to perform its usual role as an enabler of innovation: Insurers will quantify the risks and likely cover much of it. But how should insurers think about the liability for AVs? Will legislatures specify who is responsible for which problems? Will regulators? Will the courts? What principles will guide the decision makers? Where will liability fall? Using history as a guide, it’s possible to make reasonable guesses at some of the answers... continue reading > The Future of Blockchain Series Episode 1: Usage in Personal Lines Blockchain has incredible potential to impact traditional business functions and inspire new innovative opportunities Learn More SIX THINGS OnStar: Next Step for OEM Partnerships by Harry Huberty Insurers hope to create a new way to collect driving data that’s easier for the driver than installing a device or downloading an app. Read More COVID-19 Is No Black Swan by Hélène Galy There were clear warnings about COVID from credible institutions. The real issue is how we are going to deal with "grey rhinos." Read More ESG: Doing Well by Doing Good by Stephen Applebaum Insurance is at the forefront of the environmental, social and governance movement, which may usher in a Second Age of Enlightenment. Read More P&C Claims: 4 Themes for the Future by Mark Breading The extraordinary events of 2020 have accelerated four themes: automating operations; AI for insight; augmenting experts; and new ecosystems. Read More Advice to Early-Stage Startups on Pricing by Ebony Hargro and Jeff Goldberg Your pricing is a marketing tool that announces how you want potential clients to think of your offering. Read More How AI Transforms Risk Engineering by Jack Liu “AI could contribute to the global economy by 2030, more than the current output of China and India combined.” Read More GET INVOLVED Write for Us Our authors are what set Insurance Thought Leadership apart. Get Started Partner with Us We’d love to talk to you about how we can improve your marketing ROI. Learn More SUBSCRIBE TO SIX THINGS

In the past years, we’ve seen a steadily growing interest in distributed ledgers and smart contracts. The financial industry has already been largely disrupted by these innovations. Although insurance has relied on conventional methods for decades, let’s explore the potential of smart contracts in the insurance industry, their limitations and the legal implications. 

In very simple terms, a smart contract is a software program that automatically enforces the agreement terms when certain, predefined conditions are met. In other words, a smart contract acts as a virtual intermediary that executes transactions between two parties. 

Ultimately, the insurance industry’s main challenge is a lack of trust and transparency between actors. According to Accenture, only 29% of customers trust insurers. This lack of trust is mutual. Fraudsters commonly make false claims in the hopes of receiving payouts, forcing insurers to put extra resources into the validation of every claim. With smart contracts in place, the trust problem can be at least partially eliminated while lowering administrative costs. 

The Potential of Smart Contracts

Traditionally, the insurance industry relies on a trusted intermediary to execute the transaction. The involvement of a third party makes the process slower and more expensive. It’s not uncommon even for uncontested claims require months to be processed. 

With a smart contract, no human interference is required. First, this helps mitigate the risk of manipulation by the mediator and increases transparency. Given that smart contracts are stored on a blockchain, both parties can see logged transactions. Second, it dramatically speeds up claim processing. Third, it lowers administrative costs for the insurer. As a consequence, companies can lower premiums, increasing market share. Fourth, neither insurer nor customer can "lose" agreement information, as policies are securely stored on the blockchain. 

The Limitations of Smart Contracts 

Smart contracts do have limitations. Currently, smart contracts can provide value only for the most primitive types of insurance cases. In very simple terms, smart contracts can operate only based on a conditional pattern of "if X, then Y." 

Smart contracts become viable only when their conditions can be wholly transcribed into programming code. Unfortunately, this is a rather rare scenario, as a significant portion of today’s contracts are filled with nuances. 

For example, industry-specific concepts like "good faith" or "reasonableness" can’t potentially be expressed by the simple rules that smart contracts are currently based on. It would take an innumerable amount of code and resources to describe all possible contingencies and complex scenarios. 

Moreover, as insurance is a very conservative industry, many would hesitate to trust technology instead of a conventional third party. With smart contracts, we are not really eliminating the intermediary; we are just getting rid of the human factor and substituting computer code. While the code embedded in a smart contract has very little risk of being hacked, the code itself can be flawed. This is why smart contract security audit has now become a commonly outsourced service. 

See also: Where Blockchain Shines Right Now

Legal Implications 

With growing attention to blockchain and smart contracts, the first adopters of the technology have faced certain legal barriers. In 2019, the European Insurance and Occupational Pensions Authority set up Insurtech Task Force, which analyzes smart contracts in the legal context. 

The formulation of a solid legal framework will most likely take at least a few years. Currently, the widespread adoption of smart contracts is either risky or impossible, depending on the jurisdiction. For example, some experts argue that, under current U.S. contract law, smart contracts are perfectly enforceable. However, such conclusions are largely based on the exploitation of ambiguities regarding the use of electronic signatures. 

Smart contracts will most likely introduce new challenges in the legal landscape. The main value of a smart contract can be attributed to automated performance that can’t be altered. In insurance, this automation can complicate things. For example, if a party claims that there was no enforceable contract or that terms were not fulfilled, under the traditional approach the party could simply withhold payment, while the other party would open a dispute. With a smart contract in place, the funds would still be transferred, forcing one party to file a lawsuit to alter the transfer. Moreover, understanding smart contracts will require significant new skills for legal professionals. 

However, such roadblocks should be considered short-term. The potential for smart contracts in insurance is undeniably significant. Given the current limitations of the technology, we will most likely see smart contracts used first for simpler insurance processes like underwriting and payouts. For smart contracts to scale, we will not only need dramatic technological improvements but also significant changes in the legal landscape.

"Vintage" is typically used to describe items that are at least 20 years old. There is no doubt that vintage clothes and cars have their charms. But vintage tech? Not quite so charming.

Twenty years ago, we'd just lived through a couple of years worth of Y2K hype. The iPhone didn't exist. The cloud? Still in the sky.... Client-server architecture was the state of the art 20-plus years ago, and laptops were just starting to replace desktop computers. Since then, we've seen a surge by smartphones, Google, Bluetooth and 5G to name but a few. We've also moved to more distributed computing environments, virtualization, software-as-a-service and mobile-first platforms.

Many legacy platform providers have repeatedly overhauled their platforms to keep pace with changes in technology and to integrate various acquisitions along the way. But legacy platforms that have evolved over longer periods can be bloated and far less efficient and cost-effective than more modern technologies.

Most of the companies that provide software platforms that currently power the industry were born in the 20th century, and the most recent Gartner Magic Quadrants (MQs) for core insurance platforms in life and P&C provides some interesting numbers:

• The average age of the top 11 companies listed in the MQ for life insurance policy administration systems in North America is 34.5 years old -- and none of these companies were founded in the 2000s.
• The average age of the top 10 companies listed in the MQ for P&C core platforms, North America, is 26.8 years old, with just three companies founded in the first decade of the 2000s.

This is not to say that these companies or technologies aren't the right platforms for insurance carriers, but, when it comes to evaluating new technologies for digital transformation, there is a strong case to be made for focusing on digital-native solutions.

With that in mind, here are some considerations to help guide your search:

#1 -- Business Model

Understanding how a potential insurtech partner sells its software can be instructive. Is it sold as an annual subscription or an enterprise license? Modern technology solutions are typically cloud- and subscription-based. Advantages include lower total cost of ownership, scalability/flexibility and security. Plus, software is automatically updated, including new features and fixes.

Consulting services required for deployment are another important factor to take into account. Is there a separate services engagement? How does the new technology integrate with existing platforms, e.g. is it API-driven or hard-wired? Is the new solution partner-friendly or intent on "going it alone"? What is the average timeline for projects of similar scope?

See also: 2021’s Key Technology Trends

Enterprise licenses, on-premises deployment, armies of consultants on-site for months, patch Tuesday...these are relics that predate today's modern technology. Moreover, legacy technologies can be monolithic and inflexible, so integrating partner technologies is difficult, time-consuming and expensive.

#2 -- Delivery

Flexibility is the name of the game, and there are a few things to consider, especially as we navigate the global coronavirus pandemic. The ability to remotely integrate and deploy new technologies is critical until a vaccine is widely available and adopted, and most insurance carriers aren't in a position to wait and see. Likewise, the ability to get to market quickly with new features is extremely important. Competitive pressures are coming from multiple fronts, and the insurance carriers that make it easiest for consumers to buy are the ones that will win.

You should also be on the lookout for flexible deployment options to ensure you are only deploying -- and paying for -- what you plan to use. It is not uncommon for legacy software packages to include lots of features you don't need along with the ones you do.

The best-case scenario is to find an insurtech partner that has the solutions you know you need today with the option of adding functionality as your needs evolve. This includes the ability to add existing platform features and to seamlessly integrate partner technologies as needed to build out the best solution for your business.

#3 -- User- and Data-Centricity

Netflix doesn't come with a three-inch-thick training manual or hours of "how-to" videos, and neither should your insurtech solution. Onboarding new users should take no more than a few hours; anything that takes longer, or that requires a specialized trainer, should be a big red flag.

Simply delivering a digital equivalent of analog processes doesn't take full advantage of the digital channel. Building a user-centric experience starts by re-imagining how users engage and collecting data that can be used to continuously improve the user experience.

Although data is the lifeblood of the insurance industry, actually putting existing data to work has been very difficult. Legacy platforms were not built to be data-centric, and pulling data from these systems is typically very difficult. But data needs to be at the center of any digital transformation initiative.

Netflix knows what people are watching and uses this data to develop more and stronger content for these audiences. Similarly, the insurance industry can use data to inform market and product development.

Other Red Flags

Another technology red flag that you should consider is offshore development. Insurance and other financial services businesses have specific security, privacy, regulatory and compliance needs based on geography. Partners that are developing solutions for your geography -- in your geographic region -- not only understand the requirements but are also bound by them.

Lastly, you should be able to get a solid demo that speaks to your company's specific needs in a timely manner. Vendors that need a lot of time to build a demo for you are likely working with inflexible technology. Just think: If they are having a hard time moving quickly with their own software, how are you going to? Modern technology solutions tend to be modular, so it's easier and faster to build demos -- and, ultimately, to deploy solutions.

Conclusion

In 2016, Klaus Schwab, founder and executive chairman of the World Economic Forum, introduced the idea that we're entering the Fourth Industrial Revolution. The pace of change and the sheer scope of disruption are having a profound impact across industries:

"The First Industrial Revolution used water and steam power to mechanize production. The Second used electric power to create mass production. The Third used electronics and information technology to automate production. Now a Fourth Industrial Revolution is building on the Third, the digital revolution that has been occurring since the middle of the last century.... There are three reasons why today's transformations represent not merely a prolongation of the Third Industrial Revolution but rather the arrival of a Fourth and distinct one: velocity, scope and systems impact."

See also: Technology Cannot Replace Brokers

Legacy technologies and approaches to modernization have a very short shelf-life these days. Extending dated solutions or replacing them is a business-critical decision that will affect your ability to innovate and compete today and into the future. A digital-native, data-centric foundation is critical to modernizing and future-proofing insurance operations.

Enjoy a glass of vintage wine from time to time, but don't be fooled by vintage technology -- it simply cannot have the transformative impact that the insurance industry needs to modernize and compete in the digital age.

Now that truly autonomous vehicles (AVs) are starting to appear on roads, the insurance industry will be called on to perform its usual role as an enabler of innovation: Insurers will quantify the risks and likely cover much of it.

But how should insurers think about the liability for AVs? Will legislatures specify who is responsible for which problems? Will regulators? Will the courts? What principles will guide the decision makers? Where will liability fall?

Using history as a guide, it's possible to make reasonable guesses at some of the answers.

An interesting analysis in Fortune argues that the courts will set the rules, applying long-standing principles to try to sort through the issues in the new environment.

The process will thus be messy, and some of the arguments made in court will initially be idiosyncratic. The article notes that, in the 1930s and 1940s, people who were hit by hired taxis sometimes sued the passengers rather than the driver or the driver's employer. That approach never got traction in the courts and seems silly today, but you can be sure that some similarly odd-sounding theories will be tried in AV cases before being discarded.

The article argues that clear principles will gradually emerge. One is obvious: that the manufacturer will be responsible for a clear error, the software equivalent of having a tire fall off a car. But the two other standards were more subtle:

--A court will ask whether the AV performed better than a competent, average driver. That question may not apply just to the circumstances of the accident and the specific system or component that may have been involved in causing a collision but may also be a general question about the performance of the AV versus a human driver. The U.S. National Highway Traffic Safety Administration made that sort of general assessment of safety when it cleared Tesla's Autopilot system of responsibility for a fatal crash in 2016. The temptation, of course, will be to compare an AV with a perfect driver -- aren't computers supposed to be free of error? Instead, the NHTSA is taking the position that anything that raises the average competence is a societal good. And a comparison to an average driver would be good news for the manufacturers of AVs and for those that insure them.

--The court will also ask whether an AV performed better than an AV did previously in a similar situation. A key promise of AVs is that they are always learning, and not just from an individual car's experience but from what has happened to every car in the fleet. So, courts will hold manufacturers responsible for not making the same mistake twice.

The potential revenue for insurers from AVs is enormous. A recent report from Accenture and the Stevens Institute of Technology estimates that, even as AVs slash premium for personal auto coverage, product liability will be one of three new revenue streams that will generate $81 billion in premium between now and 2025. (The other two opportunities are in the new cyber risks that come along with AVs and in the potential liabilities associated with the infrastructure that will support AVs.)

The law will take shape slowly. It always does. There will be surprises along the way. There always are. But the size of the product liability opportunity, plus the beginnings of answers on legal principles, suggests that insurers should start working now to be prepared as the opportunity unfolds.

Stay safe.

Paul

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

OnStar: Next Step for OEM Partnerships

Insurers hope to create a new way to collect driving data that’s easier for the driver than installing a device or downloading an app.

COVID-19 Is No Black Swan

There were clear warnings about COVID from credible institutions. The real issue is how we are going to deal with "grey rhinos."

ESG: Doing Well by Doing Good

Insurance is at the forefront of the environmental, social and governance movement, which may usher in a Second Age of Enlightenment.

P&C Claims: 4 Themes for the Future

The extraordinary events of 2020 have accelerated four themes: automating operations; AI for insight; augmenting experts; and new ecosystems.

Advice to Early-Stage Startups on Pricing

Your pricing is a marketing tool that announces how you want potential clients to think of your offering.

How AI Transforms Risk Engineering

“AI could contribute to the global economy by 2030, more than the current output of China and India combined.”