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6 Ethical Challenges for Marketing

Everyone knows that marketing now plays a key role in the success of an insurance business. And this is down not just to trends in distribution and brand, but to digital links with underwriting as well. Moving from the periphery into the heart of a business has consequences, though.

Being in the lens of regulatory scrutiny is one of them.

See also: The 6 Principles of Persuasion  

Insurance firms in the U.K. are currently weighing new regulations that introduce the concept of a “significant harm function.” This is defined as a role that might involve a risk of significant harm to the firm or its customers. Some firms will complain about how broadly it’s been worded. Others will understand that they’re expected to work it out for themselves. So what “risks of significant harm” could marketing create for a firm?

Here are six for boards to consider.

  1. Marketing is collating a great deal of the data that is now influencing the underwriting of customer risk. As underwriting encompasses an ever growing range of factors (a thousand factors for motor risks is not unusual), the veracity of such data grows in importance. This active pre-qualifying of risk weaves marketing into the outcomes generated by underwriting and in doing so, changes its “harm” profile.
  2. Some of the digital techniques that marketers are adopting to segment consumers introduce a significant risk of biased decisions. Research is raising questions about the fair and equal treatment of consumers from algorithmic decisions. Actively addressing these risks is part of the marketer’s responsibilities.
  3. The days of communicating with consumers on a one-to-many basis are ending. All that data now allows personalized marketing, on an almost one-to-one basis. And it’s forever changing and adapting, following the flow of consumer behavior. How, then, do you monitor this? The signing-off of a campaign becomes impossible. It comes down to key marketing personnel recognizing and responding to a more sophisticated set of responsibilities.
  4. There is now a digitalized marketplace that sees marketers using chatbots to simulate conversations with consumers could see ethical consequences. How those chatbots are trained to engage with consumers introduces mis-selling risks that could scale exponentially unless appropriately overseen. Responding to such exposures will require marketers to learn new skills.
  5. Another choice facing insurance marketers is whether to adopt nurturing techniques that are becoming common in other business sectors undergoing digitization. These techniques use data and personalized marketing to move consumers into a context that would usually trigger a purchase response. This would see firms move from using behavioral knowledge to understand consumers, to using it to manufacture sales opportunities.
  6. As marketers increasingly take on the role of “the customer voice” within a firm, and as that firm seeks to engage more personally with customers, and as the balance between risk transfer and risk management within some insurance propositions changes, so does trust in the firm’s reputation come under tension. There’s a serious conflict of interest among all this, which the board, having responsibility for the firm’s reputation, needs to be sure marketers are managing effectively.

So what are the implications of marketing being designated as a significant harm function? More oversight, for sure, but isn’t that just commensurate with those widening responsibilities? A small price, perhaps, for marketing to be able to sit at the top table with finance and underwriting.

See also: 4 Marketing Lessons for Insurtechs  

What marketers can bring to that table is customer insight.

Yet because that insight comes from new techniques for analyzing those vast lakes of big data, it introduces what could be called “slingshot risks,” ones that a little algorithmic decision making can send out far and wide across a business, producing exponential impacts. It’s that capacity for exponential harm that, I think, makes marketing a real candidate as a significant harm function.

Marketing is entering a new era of accountability

20 Likely Changes in Ethics on Claims

Insurance is changing in ways that have profound implications for claims. Some claims practices will become redundant. Questions only occasionally raised before will now become common. New skills will have to be learned.

It’s all very exciting, but also a little daunting. Clearly, the way we think about claims will change, but, at the same time, certain constants will remain: settling claims honestly and fairly, for example.

So what are the changes that have implications for the ethics of insurance claims? I want to look at 20 changes that I think will be significant in terms of the ethical challenges facing claims people.

The “Ask It Never” Policy

As insurers turn from asking questions of the policyholder about the risk to be insured and instead obtain that information through big data, the time of “no questions at all” will approach. What will happen to claims then? If no questions are asked, then non-disclosure becomes obsolete, as does the whole idea of material facts. What will be left for the claims team to review or decide upon?

The Personalized Policy

A personalized policy will, by its very nature, mean that a claim made upon it will result in an increase in premium. As the public comes to increasingly sense this, how will it influence the way in which claimants approach their claim? Should claims people warn potential claimants that their claim will result in an increased premium? Some claimants will self-fund small, valid claims, although those spending patterns will then be picked up by insurers, which could move the premium anyway. Claims may well become more confrontational, as policyholders sold on the idea of personalization find the consequences unpalatable. What can claims people do to maintain trust in such circumstances?

See also: Most Controversial Claims Innovation  

Optimizing Claims Decisions

The trend toward claims settlements being optimized according to what a claimant may be prepared to accept in settlement fundamentally changes key concepts in insurance. What would be a fair claims settlement in such circumstances? And how would “fair” be determined, and by whom? Claims optimization pushes the claims specialist to the margins, although not out of the process altogether, for optimized settlements will raise questions. Someone may be hard up, but not stupid: They will want to know the basis upon which the settlement they’ve been offered has been calculated, and claims people will have to do the explaining.

Correlation and Causation

Insurers are using big data to make decisions about individual claims and claimants. Yet big data analysis relies on identifying significant correlated patterns of loss, while individual claims rely on identifying the causation of a loss. That difference is important, for correlation and causation are not the same. You can’t replace a “one to one” technique like causation with a “one to many” technique like correlation. It would be akin to saying that because your claim is like all those others (which were turned down), then we’re going to turn down your claim, too. Hardly a recipe for fairness. So as the tools of artificial intelligence are increasingly applied to claims processes, the extent to which the decisions being made remain fair will have to be closely monitored, both in terms of inputs and outcomes. How will this be done?

Reasonable Expectations

As data streams all around us (both policyholder and insurer), our ability to understand more about what is happening around us increases. This raises the question of the extent to which a claimant could have reasonable been expected to have been aware of something. If big data knows something, should individual policyholders be expected to know it too? How will insurers start to judge whether a claimant took sufficient notice of something that subsequently influenced the claim?

The Sensor Balance

As homes, offices and factories become covered in sensors, telling you all sorts of information about the property that you were only vaguely aware of before, so then will increase the number of decisions you’ll be called upon to make. There could be some maintenance required to your roof or drains, and unless it’s done soon, then your insurance could be affected. Or perhaps some machinery has been running for longer than usual, in order to meet some new orders, but the sensors are telling you to shut it down for servicing. That knowledge is being recorded and stored, along with the decisions you take in relation to it. All ready then for your insurer to tap into, should there be a claim. Insurers will now have the information to apply those traditional policy clauses relating to maintenance with a new vigor. How will this play out?

The 3 Second Repudiation

The 3 second claims settlement made news for Lemonade, but so will a 3 second claims repudiation. After all, giving people what they want as quickly as possible is a quite different experience to giving people what they don’t want as quickly as possible. How will such repudiation situations be managed, and how might claimants react to an almost instant dismissal of their claim?

A Smart Contract Just for You

Big data, smart contracts and personalized policies that ask no questions of the policyholder all point to a level of individualization that will baffle the typical claimant. A loss covered last time might not be covered next time. A neighbor’s loss may be covered in a quite different way to yours. How do you explain such situations to a claimant who’s knowledge of ‘insurtech’ is zero? If everything is so variable, then might communication turn out to be the claims person’s key skill?

The Automation of Fairness

As claims processes become increasingly automated, insurers will have to take care not to lose sight of their obligations in terms of the fairness of the decisions being made. Some insurers struggle with this even in today’s relatively straightforward workflow processes, so how they will cope with something like artificial intelligence is a concern. Experience points to this being harder as systems become more complex. A lot will depend on the extent to which those in oversight roles bring challenge and critical thinking to the implementation of such projects.


As claims processes become increasingly automated, should the claimant have the right to be told about this? There’s talk of news written by artificial intelligence ‘bots’ soon having to be flagged as ‘artificial news’. Might the same soon apply to individual decisions on things like claims? If so, then from a European perspective, a claimant’s ‘right to know’ might soon become a more complicated request to fulfill.

Upholding Supplier Standards

The consensus is that a typical claim function’s supply chain network will continue to grow for some time. And bringing in all of these exciting and new capabilities is fine, so long as everyone is singing the same tune. Insurers have to abide by the ethics of insurance claims, such as covered in rules for fairness, honesty and integrity. So how can a claims director convince her board of fellow directors that their firm’s ethical obligations are being met every bit as confidently as in more analogue times? Has her due diligence taken account of not just the intelligence and energy of those providers of artificial intelligence solutions, but their integrity as well? It’s a challenge best met earlier on.

Instantaneous Claims

That breed of policies described as ‘mobile, micro and moment’ are all about instant cover for just what you want, when you want it, for as long as you want it, and arranged with a few clicks on your phone. Turn those conveniences around and you have the potential for the instantaneous claim, perhaps only moments after inception – “I bought cover for a bike, got on it, went outside and crashed it”. Such claims have usually been looked upon with suspicion by claims people, on the basis that such a quick loss could not be fortuitous. Yet if you provide cover in this way, why shouldn’t some claims happen in much the same way? This is a change of mindset needed throughout an organization, not just in underwriting.

Managing Complexity

As more cogs, and more complicated cogs, are added to the overall claims process, the greater the challenge it becomes for them to deliver on the promises that were made at the planning stage. This is an existing problem for claims people in the UK, who have acknowledged that the multiplying layers of many claims systems aren’t delivering the expected results. The answer will not come from artificial intelligence working it out for itself: all AI needs to be trained on historical data. So claims people need to understand complexity and how to manage it.

Challenging the Decision

Research by one leading insurer in the UK market found that policyholders are less likely to trust an automated decision than one involving a human. So as claims become more automated, insurers could face an increasing number of challenges from individual claimants, asking how the decision on their claim was reached. How will they explain an output from an increasingly ‘black box’ process? They may be tempted to rely on generalized responses, but that isn’t going to work when the claimant appeals to an adjudication service like the UK’s Financial Ombudsman Service (FOS). Organisations like FOS should be working now on how they can get inside that automation and assess the fairness of the outcomes it has been designed to produce. Will they perhaps look to accredit the overall automation, or rely on case by case use of techniques like fairness data mining. Another factor that insurers need to take into account will be claimants turning to the EU’s General Data Protection Regulation and enforcing their right to access the data upon which the decision on their claim was made. Insurers will need to prepare for this, both in terms of the volume of such requests and the complexity of responding to them. Again, the ability of claims people to communicate complex things will become a key skill.

Provenance of Data

As insurers bring more and more data into their claims processes, especially unstructured data drawn from sources like social media, they will need to be prepared to demonstrate the provenance of that data. In other words, they need to be able answer questions like “where did you get that piece of data from that seems to have been a big influence on my claims decision?” Or “that piece of data is wrong so you need to change your decision.” If you utilize data outside of the context in which it was first disclosed, then the error rate shoots up. Just because a piece of data resides within a system doesn’t establish it as a fact.

Significance in Algorithms

Pulling all sorts of data together is one thing, but the value that claims people draw from all that data comes from the algorithms that weigh up its significance. At what levels the various measures of significance are set will be hugely important for the outcomes that claimants experience. These introduce options that require judgements and such judgements need to overtly account of ethical values like fairness and respect.

See also: How AI Will Transform Insurance Claims  

Segmentation of Claimants

As claims processes become more automated, so claims people are presented with the opportunity to segment the experience of the various claimant types they engage with. Many insurers currently use software to assess claimants at the ‘first notification of loss’ stage and vary the type of experience they receive. At the moment, this is being used to address claims fraud, but it is unlikely to end there. Artificial intelligence coupled with audio and text analysis will allow insurers to segment non-fraud claimants for all sorts of purposes. The challenge for claims people is just how acceptable some of those purposes might be. For example, what if claimants are segmented according to the amount they are prepared to accept as a claims settlement? All of these new technology platforms introduce options, but just because you have the option to do something doesn’t mean that it’s a good thing.

Warnings Ahead

New ways of communicating with policyholders offer up the possibility of advance warnings being given of storms, floods and the like. That brings many benefits to both insurer and policyholder, but it also raises the prospect of those warnings having conditions attached. Rather than advice, they could include requirements linked to continuation of certain elements of cover. If the policyholder doesn’t (for whatever reason) respond to those communications, this then introduces possible conflict zones for subsequent claims.

The Convenience of Clicking

The ease with which cover can be incepted using mobile devices is a great convenience to policyholders at the outset of a policy, but it could turn into a great inconvenience when making a claim. Research shows that we invariably do not read the terms and conditions presented to us when buying a mobile based product or service: it’s just too easy to click accept, especially when the fine print looks even finer on a small screen. So claims people need to be prepared for many more people than at present not knowing about the cover they’ve signed up to, beyond what is indicated by a few well designed icons on a screen.

The Language of Claims

A subtle change of language has emerged in claims circles in recent years. The service element of what’s on offer is being stressed more than the insurance element. While it’s great to see insurers now paying attention to risk management in their personal lines portfolios, this shouldn’t be at the cost of what is at the heart of an insurance product, which is risk transfer. The danger is that this slow and subtle change will not be picked up by customers until they find out when trying to claim that what they’ve bought is largely a service and not insurance.

To conclude. It’s a great time to be in insurance, and I would say even more so in respect of claims, for that is where all the promises inherent in the insurance purchase are fulfilled. Those who recognize the ethics of insurance claims and rise to the challenges outlined above will be those who are trusted in the digital market.

Most Controversial Claims Innovation

Pushing at boundaries and challenging traditional notions is what innovation is all about. Rethinking something that people have taken for granted for too long can open opportunities for enhancing service, increasing efficiencies and generating revenue.

Take claims. The idea that the claim settlement should reflect the insured loss has held sway for a great many years. Is it time for innovators to knock this one off its pedestal?

It looks like that time has come, for insurers in the U.S. are starting to turn to claims optimization.

To explain this, I should start with the perhaps more familiar concept of price optimization. The price version has the insurer setting the premium for insuring a risk according to what the policyholder is prepared to pay, rather than the level of risk that the policy is presenting. It involves using big data to work out the price at which particular types of customer will start to look for alternative quotes, and then progressively raising the premium to just below that amount.

See also: Innovation Challenge for Commercial Lines  

A leading figure in the U.K. insurance market recently described price optimization to me as “recognizing the true lifetime value of the customer and reflecting that in a better price.” It’s a nice quote, so long as you’re the insurer on the receiving end of that “lifetime value” and that “better price” and not the customer paying for them.

I’ve yet to hear how that description fits in with the regulator’s interest in fair outcomes for customers. It would struggle to do so, for reasons I explain in this paper I wrote for the U.K.’s Chartered Insurance Institute last year. In short, the nature of insurance makes price optimization highly questionable on ethical grounds. It’s hardly surprising that a recent PwC survey found that 72% of insurance CEOs think it will be harder to sustain trust in a digitized market.

With claims optimization, insurers would seem to be abandoning all remaining hope of sustaining trust in a digitized market. Claims optimization involves using big data to establish the amount that a particular claimant would be prepared to accept as settlement of the claim. So if all those algorithms pinpointed the claimant as someone in financially tight circumstances, then the settlement offered to that claimant would be optimized to reflect a greater and more immediate need for cash. This would involve tweaking the comparative speed of a cash settlement versus a replacement service and setting relative offers to achieve the optimized position.

This still falls neatly within that description of optimization as “recognizing the true lifetime value of the customer and reflecting that in a better price.” Indeed, an insurer happy to optimize on price would hardly need to bat an eyelid at optimizing that other value determinant: claims expenditure. After all, the insurer would say, if a claimant is prepared to accept that lower settlement, why shouldn’t the insurer offer it?

Let’s be quite clear: Claims optimization is an exploitation of the unequal balance of information and economic power between a consumer and an insurer. It is unprofessional, and it is unethical.

Might this view perhaps point to me being a naysayer on innovation? Not at all – I have a postgraduate degree from one of the earliest courses in the U.K. on the study of scientific and technological innovation. That course taught me to recognize the multi-sided nature of innovation and to see that it is not some nature force of business evolution, but a mix of social, economic, philosophical and technological drivers.

See also: The Great AI Race in Insurance Innovation  

Despite what vendors of “big data solutions” say about optimization, it is not a natural next step for underwriting and claims. It is home to a number of quite radical assumptions about what insurance is there to do and how it should do it. It would be nice to see some of those assumptions brought out into the open and debated, but, unless Andrew Bailey at the FCA follows through on some of his hesitations about price optimization, then I fear such a debate is unlikely.

I have heard some chief executives at leading insurers wonder whether price optimization was the right thing to do. If, as it would appear, they no longer have any such qualms on the pricing side, then it is but a small step to their being equally relaxed about using it on  the claims side. In that case, I look forward to listening to them explain their reasoning for doing so on a public forum like, say, the BBC Radio’s Today program.

Which Rules Should Insurtech Break?

There’s a lot of attention being given at the moment to the startup firms that are entering the insurance market in the hope of grabbing attention and business by disrupting the established ways of doing things. And some of these insurtech startups are indeed introducing new and exciting ideas to the market. Disruptive thinking has its upside, and customers will benefit from it. Does it have a downside as well, though?

There’s a view that, to be successful, disruptors need to “delight in breaking rules, but not rules that matter.” This view can lend startups a certain piratical air, yet it can also cause them to see the rules that get in their way as the rules that don’t matter. That’s why we’ve seen some high profile insurtech startups crashing into regulatory brick walls: Zenefits is a classic example of this.

Now,  I’m not saying that startups shouldn’t hit problems, even regulatory ones, but what I am saying is that they should at least get the basics right, even if the basics are themselves disruptive to the work of disruptors. The U.K.’s Information Commissioner made this clear to the insurance industry in 2015 when he pointed out that “big data is not a game played by different rules.”

See also: An Eruption in Disruptive InsurTech?  

I’m also not asking for insurtech startups to occupy the high moral ground, but I am saying that they cannot reinvent “doing business” in ways that sidestep the ethical values that consumers expect firms to uphold. Nailing business values like “innovative” and “disruptive” to your piratical mast won’t stop inconvenient winds like “honesty” and “fairness” from pushing your exciting voyage toward the hard rocks of reality.

It is with terms such as honesty and fairness that customers often describe what a “good financial services firm” feels like. Yet insurtech start-ups are often being urged to disrupt customer expectations, seeing them as a quaint left-over from an old way of doing things. The future is instead said to lie in insurance providers getting closer to their customers in all sorts of ways. Yet isn’t business success more reliant on customers wanting to get closer to firms? It’s the latter that leads to the former, not the other way around.

The danger is that disruptors’ natural and essential super-confidence in themselves is translated into overconfidence in the ethical correctness of their decisions and judgments. And there’s then the tendency for them to believe that other people think the same way as they do. Both are fairly normal traits that we all exhibit in some form or other in our everyday lives. I certainly do, and my daughters have pulled me up short with one or two of the decisions I’ve made.

See also: The State of Ethics in Insurance  

And that sort of challenge, that sort of “knowing you but through different eyes” is vital for insurtech startups. While insurance needs disruptive startups, they in turn need disruptors of group think, of the wrong sorts of overconfidence. As the folklore of startups fills with tales of disruptors being told they’re not being overconfident enough in their business plans, let’s put out a marker of hope for 2017, that it will see tales of disruptors being told they’re not being ethical enough in their business plans, that they’re not doing enough to earn the trust of consumers. It’s very possible, if the market and those advising them want it.

The Rise of Panopticon Regulation?

A radical shift is underway in how insurance markets are going to be regulated in the UK. The shift will transform the relationship between insurers, regulators and the public.

“Big data” promises a more personalized, customer-centric way of doing business. Yet, as insurers gain access to unprecedented levels of information about the lives of consumers, there could be problems with privacy.

This ability to track everyday lives begins to resemble an idea put forward by the 18th century reformer Jeremy Bentham. He envisaged a prison designed in the form of a ring, with a central tower from which prisoners could be monitored at all times, but in which those monitoring remained unseen. He called it the Panopticon. The idea underpinning Bentham’s design was that the monitoring would be so constant, yet so unknowing, that the prisoners would adopt more conforming behaviors.

Let’s think of a modern day panopticon, the ring filled not with prisoners but with millions of consumers, and a central tower full of firms gathering data about us. Data about our everyday activities would stream into that central tower, to be turned by the firms there into personalized products and services. A “digital panopticon.”

Insurers are one such class of firm taking up position in that central tower. Underwriting and claims people would analyze all that consumer data, looking for patterns of behavior that signal a good or bad risk, an honest or dishonest claimant.

Then there’s the UK regulator, the Financial Conduct Authority (FCA), talking about a new era of regulation based on a combination of data, technology and behavioral science. The FCA illustrated this new era in a recent review of the pay-day loan sector, drawing in vast amounts of loan data from firms and analyzing it to produce new rules on lending and servicing practice.

Insurance could be next on the FCA’s list. Might the FCA start drawing in vast amounts of insurer data to analyze it for signs of consumer detriment? If so, does this mean the regulator is now constructing an observation tower of its own inside that “digital panopticon,” one that sits within the insurance market’s own tower? Are we seeing the emergence of “panoptic regulation”?

Such a “tower within a tower” could be a game-changing move. It could bring about a radical change in market attitudes toward ethics, fairness and culture. After all, the key idea behind the panopticon was for it to bring out better, more universal behavior, on the basis that what you were doing at any time might be under observation. Is the real future of regulation then simply the power derived from being in that innermost tower, using data to watch over a firm that could be yours, to watch over a person who could be you?

And if firms use predictive analytics to anticipate policyholder behavior, then could the regulator use its own predictive analytics to identify emerging patterns of misconduct? A regulator able to address misconduct before it became widespread would be powerful as well as controversial.

This could bring about a revolution in trust, for might consumer concerns about their personal data fall away, knowing that regulators are able to see everything insurers are doing with it?

The original panopticon proved too radical for the time and was never built. Yet something very similar is taking shape in the digital insurance market. The key question is: Is the insurance market and its regulators ready for the consequences that will flow from this?

To explore the concept of panoptic regulation in more detail, read this paper I wrote for the Chartered Insurance Institute earlier this year.