Regular contributor Syed Danish Ali examines the intersection of technology with a critical industry he knows well: insurance, which provides 9 percent of the global GDP.
The Tao Business Model for Insuretech
The Tao Business Model for Insuretech
In 21st century disruption, we are seeing the emergence of a new business model, which I term “the Tao business model” (referred to here variously as “Tao,” “the Tao,” or simply “we.”) The Tao model has many paradigm shifts that distinguish it from standard capitalist business model. We will discuss them in detail here. Although the Tao applies to many startups and generally to 21st century disruption, we will focus here on insurance startups, known here as “insuretechs,” to elucidate the Tao business model in just one of its specific contexts. Embodying the Tao in this write-up as well, this write-up serves just a guide rather than as a definitive verdict to a topic, or a definite cause−effect write-up with specifically assigned clear conclusions and authoritative opinions.
There is no attempt here to "pigeonhole" the great philosophical wisdom of the Tao and use it to glorify technology or insuretech. There is no attempt here to create divisions or to imply that “we insuretech are better than current insurers, and we are wiser than them.” To do so would be to create another division as source for conflict, and we have enough of them already. The future of insuretech is most likely to be a collaboration and an ecosystem rather than a pure disruption. This collaboration will build upon the strengths of both insuretech and insurers and mitigate their weaknesses to make a winning combination. This harmony is more important than disguising greed under wise Tao. This write-up is just like a friendly conversation which accepts many inherent contradictions and aims to show the way only rather than spoon-feeding. It’s an attempt to see similarities between the ideal and the real, the spiritual with the material without making any party better off or worse off.
In a nutshell, the contents of this report can be encapsulated as follows:
- A brief primer on Tao philosophy
- The Tao business model
- Peering into peer-to-peer and social impact
- Automated machine intelligence; let humans be humans
- The leader who does nothing
- Exponential innovation: the finger pointing to the moon
- Challenges to the Tao model
- Future outlook of our collective samsara
- Final words: tying the 6 knots.
1. A Brief Primer on Tao Philosophy
Tao philosophy is very ancient and prevalent in the Far East. In modern times, it has caught the imagination of the West as a spiritual cure to the coping with the ills of modern western capitalist life. This trend of western materialism merging with eastern spirituality is not accidental but deeply sociological.
The Future shock; “Future Shock” concept has been derived by the futurist Alvin Toffler and means perpetual state of anxiety and anguish in psychological states of individuals and sociological states of whole societies due to “too much change in too short a period of time”. Fourth industrial revolution is bringing vehement changes to all spectrums of our lives and it arouses fears of ‘surveillance’ dystopian societies with mass unemployment due to automation, all pervasive surveillance, and end of privacy, unique individual thought and end of what it means to be a free human. Eastern spirituality shocks the future shock by embracing change, letting go of desire to control change, creating future through our products and technology, and emphasizing relentless pursuit of ethics so that technology can be used for the social good instead of against it.
New risks, products and liabilities are emerging and are becoming antiquated before they can even ossify. Constant revolutionizing of technology constantly keeps our social relations in everlasting uncertainty. Pre-emptive action and pro-active in the nick-of-time involvement is now perhaps the only way for us to go about dealing with the rapid fast-moving present and future.
There are various tenets of Tao philosophy which are being converted into business model to change our practical realities now. Some tenets that are relevant are described here.
Learn from the people
Plan with the people
Begin with what they have
Build on what they know
Of the best leaders
When the task is accomplished
The people all remark
We have done it ourselves
Taoist sage, Lao-tzu.
Taoist ethics are very fluid, vast and open to subjective interpretation but generally emphasize wu wei (effortless action), "naturalness," simplicity, spontaneity, and the Three Treasures of compassion, frugality, and humility. There is social focus to do no harm to others, work for the benefit of nature and living beings and emphasis that every individual has his/her own way to knowing the truth and there is no objective ideal dogma to strive towards.
Less and less do you need to force things,
until finally you arrive at non-action.
When nothing is done,
nothing is left undone.
The concept is to have no-mindedness in your actions and thoughts. It does not literally mean giving up mental faculties but rather that emptying the mind allows us to be intuitive and to flow naturally in our actions. It is in such attuned states that the doer disappears; Lao Tzu says, by not striving after power, a man becomes powerful, if straining and reaching for power, he never has enough. If we are always trying to do and force things to go our way, we lose sight of their true nature and soon discover that our overzealous endeavors only get in the way, and nothing is accomplished, or it leaves even more to be done. To “do nothing” means to allow the world to unfold as it will, without seeking to manipulate or control its dawning emergence.
Bruce Lee in Enter the Dragon says “It’s like a finger pointing a way to the moon. Do not concentrate on the finger or you will miss all of the heavenly glory”.
Finger pointing to the moon is a really beautiful eastern metaphor for teaching us how to lead our lives. The moon is the heavenly glory of skillful ideas and proper way of life and the finger is the teacher. The teacher is not just someone who really influenced you like Bruce Lee, but your own feelings and life itself as well. The skillful way of leading a life is not dependent on one person or one experience but it is a gateway to knowing our true nature which is infinitely more beautiful and cosmic. But if we fixate and cling to the finger, to that persona, to that person, to an event in our life, we will miss the true beauty of exploration into our psyche’s unconscious.
There is also something profoundly sociological in this ‘finger’. We rely on borrowed wisdom and the prevailing thoughts of our culture and times without actually knowing it to be true for ourselves. Whether it is education, how to lead a family, how to work, what is law, what is society, the borrowed wisdom is the finger that leads us to fixate on the immediate instead of the moon of infinite possibilities of the complex interconnected whole of reality.
2. The Tao Business Model
Here we show how Tao philosophy resembles key aspects of upcoming insuretechs. There are various features that are discussed here:
- Peering into Peer-to-peer and social impact
- Automation Machine Intelligence; let humans be more humans
- The leader who does nothing
- Exponential innovation: the finger pointing to the moon
2.1. Peering into Peer-To-Peer and Social Impact
The peer-to-peer business model is quite simply for the community and by the community. The insurer is just someone who brings the pool together and administers it and takes just an up-front margin fees and the rest belongs to the policyholders who are the real owners of the business. Any underwriting surplus is donated to charities or given back to the policyholders.
This removes a historic friction of the traditional capitalist business model. The traditional capitalist model favors shareholders above all other stakeholders. It comprehends that shareholders are the ones who have provided the capital and have taken the risk of starting and running the business so any profits belong to the shareholders. In this way, as Lemonade insuretech says again and again, the insurance system and the structure itself is pitted to bring out the worst in the people; the insurer will avoid paying out claims since it will decrease his profit and the customer will react likewise by distrusting the insurer. Peer to peer business model removes this grand fiction by saying that it’s your money and not ours. The giving back to customers any remaining premium or donating it to charity further reinforces this perception that you don’t lose control over your money after paying the premium. It gives back control to customers who are accustomed to learned helplessness from the mighty insurers. As apparent, the Tao ethics of not harming and improving social reality for others are quite explicit here.
Aside from Lemonade’s distribution of underwriting surplus, there are stronger networks of peer to peer insurance like Guvera and Friendsurance. Here, many groups of peer having social affinity are made and each group is responsible for its own performance. Any left-over premium is paid back to the pool. Friends and family member invites the new member or the insurer suggests the most relevant pool to join based on features like risk profile and location.
Thus, a lot of crowd wisdom is utilized in this as the insurer ‘Learns from the people, Plans with the people, Begins with what they have And Builds on what they know’.
Instead of an actuary maximizing profit for the shareholders, sitting isolated from ground realities, lacking skin in the game, and have far less access to awareness (i.e., data) of people relative to their peers, this peer to peer empowers the crowd and taps in into their wisdom (instead of wisdom from books) which is far better. There are also no unfair pricing practices here like rating based on gender, pricing optimization which charges you higher if you are less likely to shift to another insurer and vice versa. The giant insurer cannot know you more than your peers, it’s as simple as that.
To make the process further seamless, agile, robust, invisible and as easy as a child playing, blockchain technology is used with smart contracts that execute itself when the conditions meet. This new P2P insurance model is doing away with traditional premium payment using instead a digital wallet where every member puts in their premium in an escrow-type account only to be used if a claim is made. In this model, none of the members carry an exposure greater than the amount they put into their digital wallets. If no claims are made all digital wallets keep their money. All payments in this model are done using bitcoin further reducing transaction costs. Teambrella claims to be the first insurer using this model based on bitcoin.
This is applying “shoshin” into practice which means the childlike state of having a beginner’s mind (the cup is empty) that is not pre-occupied by erudition that occupies (or fill’s the cup) of the advanced person. The attitude is open-ness, eagerness, curiosity like a child has.
Seamless mobile app, radically simple products and communications, automatic claims handling, policy generated quickly, AI chatbots, automated machine intelligence for fast analytics all further helps insuretech to apply shoshin, spontaneity through reduced times automation and simplicity into practice.
2.2. Automated Machine Intelligence; Let Humans Be Humans
There is of course a broader context to automation where almost every field is suspect to and no one is free from this fear of AI apocalypse. There’s also a brighter side of automation where it will allow humans to explore ‘play’ instead of work only. For a comprehensive coverage, see this article on futurism.com
Despite the hype and glory associated with quantitative modelers like data scientists, actuaries, quants, and many others, they face a conundrum which automated machine intelligence sets out to solve. The conundrum is the gap between their training and what they should be doing compared to what they actually do. The bleak reality is most of time gets taken by monkey work (work that any monkey can do instead of an intellectually trained and competent human being) like repetitive tasks, number crunching, sorting out data, cleansing data, understanding it, documenting the models and applying repetitive programming (being spreadsheet mechanics too) and good memory to remain in touch with all of that mathematics. What should they be doing is being creative, producing actionable insights, talking with other stakeholders to bring about concrete data-driven results, analyzing and coming up with new ‘polymath’ solutions to existing problems.
Automated machine intelligence (AML) takes care to reduce this huge gap. Instead of hiring a team of 200 data scientists, a single or few data scientists using AML can utilize fast modeling of multiple models at the same time because most of the work of machine learning is already automated by AML like exploratory data analysis, feature transformations, algorithm selection, hyper parameter tuning and model diagnostics. There are a number of platforms available like DataRobot, IBNR Robot, Nutonian, TPOT, Auto-Sklearn, Auto-Weka, Machine-JS, Big ML, Trifacta, and Pure Predictive and so on.
Through this way AML frees up data scientists to be more human and less cyborg-Vulcan-human calculators. Machines are delegated to what they do best (repetitive tasks, modeling) and humans are delegated to what they do best (being creative, producing actionable insights to drive business objectives, creating new solutions and communicating them).  AML allows simplicity, flexibility, and the data scientist becomes like water (we can hear in our minds Bruce Lee saying be like water now.)
2.3. The Leader Who Does Nothing
The leader is just a guide in the Tao business model and an administrator here and does not imposes any central authoritarian constructs upon the pool but only shows the path. The community is free to discover their own path over time as the leader has left no footprints over time like a bird in the sky.
Thus, the insuretech allows the unique personality of the customer to come out on the surface rather than imposing the same or similar products to everyone. There is high level of personalization. Big data through mobile data, conversational data, wearables, IoT devices etc allows access to data unthinkable before. This data has to be tapped in to peer inside the mind of the consumers to give them what they want and eliminate pain points. Over time, we expect to see IoT devices insuring themselves over times of high risk that will usher in machine-to-machine on-demand insurance.
But hyper personalization does not mean we aggravate information determinism. Information determinism is where algorithms exacerbate initial tendencies of the customer and lead to people living in their own bubbles. For economics, first we assumed ‘rationality’ which means that a rational actor will weigh all the pros and cons and decide the optimal route. Behavioral economics then told us ‘bounded rationality’ where maximization of utility is not the objective like in rationality; but that contradicting interests are adequately managed like protecting environment instead of profit maximization. Bounded rationality tells us that we do the best we can with our limited time, view, information and conflicting interests.
Now our view is that we have started seeing ‘bubble rationality’ in postmodern societies. Bubble rationality is where each individual lives in a bubble of her own, which is internally self-consistent but radically different/extreme from other bubbles and very hard to integrate with other people. More economic inequality leading to its cousin of cultural polarization, populism, economic crises, robots and internet and mobile phones causing information determinism means that stratification is breaking down into very fluid categories especially for the millennials. As with big data, there is data to back almost any idea, more pseudo-data-driven propaganda can appear more objective like wolf in a sheep’s clothing.
Hence, this is our motto and our haiku now to “Balance the bubble rationality and global consciousness in a harmonious whole”. Together with our community, we aim to build a hive mind of individual universes who connectedly build a coherent whole; a cosmos a multiverse of opportunities and better lives lived.
We are not alone; the wider society is waking up to the fourth industrial revolution brought about by AI. It is an emerging phenomenon quickly sweeping over decades of inertia and habits. We want to create the future, instead of being made irrelevant by it. This fourth industrial revolution is poised to reward those who have first mover advantages like previous revolutions had rewarded the previous innovators. Insuretechs want to take advantage of this emerging revolution before it starts becoming the standard established way of doing things.
Existing insurers use only proxy modeling to price risks which can be unfair to the customers. Proxy modeling, like seeing the age, gender, locality, credit score is a remnant of the past when statistics had to be applied onto small datasets to underwrite risks. The most important factor in determining morbidity and mortality is lifestyle of the person, just like the most important factor in determining motor insurance is driving behavior. Insurers exclusively focus 100% on proxy modeling which makes it unfair to the customers; a young person might be sicker than an old person; a young person might drive better than a middle aged person and so on. These proxy factors are largely fixed and beyond the control of the customer.
But of course proxy modeling is not entirely useless. It is useful here to categorize proxy factors as consisting of risk factors and marketing factors. Many risk factors are valid like higher age means higher mortality risk in life insurance but many are discriminatory as well which leads to protracted lobbying by human rights to not allow discrimination based on those factors like charging young drivers higher motor insurance premium rates, charging female pensioners more than male pensioners, deciding premium based on your credit rating and zip codes which can be discriminatory to low earning racial families. The marketing factors are even more controversial termed pricing optimization recently. This is where one person has lower price elasticity and hence will not shift to another insurer if premium and so increase it by X. Another person, of similar risk profile can have higher price elasticity and will lapse the policy even if premium is increased by 20 percent of X so charge 10 percent of X instead of X. Regulators in developed countries have started clamping down upon these pricing optimization policies and stated that price should be differentiated based upon legal risk factors and not upon marketing factors like price elasticity.
There must be still power given back to customers like even if the age is high, show your healthy lifestyle for discount on your life insurance premium. Hence, blending big data with proxy modeling that is legally allowed is the key to moderation and is the ‘Middle Path’ to better pricing.
Modern big data and data science allows us to creatively blend proxy modeling with big data generated from various sources to arrive at fairer and more risk-optimized prices and control is given back to the customer through discounts for healthy living. Of course, this personalization does not mean the very concept of insurance through pooling a population is eradicated.
2.4. Exponential Innovation: The Finger Pointing To the Moon
Insurers have failed to tap into the high end customers as well as those at the bottom of the pyramid. No insurer is interested in creating new markets and they are continuing fighting over share of the current market’s pie. They aim for incremental improvement which is not exponential enough to create new sustainable markets.
Legacy, corporate bureaucracy, culture and dynamics means that the insurers will continue lagging behind in innovation because they are risk-averse, do not develop top talent and skills, focus on current sales and routine work as most important and are not willing to embrace the cultural change that fintech and insuretech promises. There is huge resistance to change and a wish to turn back the clock.
All teachings of the past, from mystics to scientific are to be taken as a guide, a working hypothesis instead of stone writings that must be followed literally at all costs. That does not mean that the Tao is obsessed with the new and does away with the old; in fact it recognizes that while most of our scientific achievements have been taken in modern times, the ancient sages have priceless and way superior self-awareness and ethical know how on philosophy, sociology, and psychology than we have.
Traditional investment, finance, actuarial modelers employ techniques that are out-of-date and inappropriate for the demands of today for data and modeling. A range of cognitive biases like herd mentality (this is what everyone is doing so why do anything different, someone higher in the hierarchy is doing this so why bother), risk averseness, ambiguity averseness and confirmation bias where we do only what we know already instead of admitting ignorance and taking the leaps to become comfortable with the unknown.  The Tao does not take a follower mentality that everyone is doing ancient modeling so we have to do it too and that the market is not ready; we will make the market ready and innovate in terms of data, modeling, products and strategy making.
At the same time, we recognize that all models and projections are ultimately a small replica (finger) of the complex reality (the moon’s heavenly glory) and is no substitute for timely management. We realize that reality will always be different than our expectations and projections. The aim hence, is not to become a better forecaster but a better evolver. We must integrate our quantitative modeling with qualitative profiling and behavioral analysis of psychology of the customers. This means a) having a close eye on emerging and futuristic trends, risks and opportunities, b) augmenting quantitative modeling with qualitative judgments c) using behavioral and sociological analysis to limit cognitive biases in ourselves as well as to keep the customers motivated and engaged. At its heart, the failure of the current insurance systems is a failure of imagination; in what could become instead of what is only being currently done. We want to inspire people, systems, and practitioners and spark their imaginations to bring in more creative solutions to our problems. The social scientist and philosopher should not worry over being useless; she should aim to change the world in collaboration with others instead of only interpreting it. As much as we focus on the outer external world and its external changes, the real change is to know ourselves and change within.
We must aim to avoid the "fratboy" culture that plagues many tech startups. Startups usually revolve around a huge personality with ruthless pace and minimum regards to institution building, capacity building and proper structures like HR structure. This is not a problem in initial times when a startup is still a startup, but once when scale is achieved, this culture become a huge barrier to sustainability. Scandals of Uber and many other startups in Silicon Valley highlight this problem prominently. We believe that to make customers happy, we have to first keep our employees happy. There will be a lot of fast pace in the startups but we must aim to build an institution with proper structures and check-and-balances as well. Continuous learning has to be in our bones as well as Work life balance, healthy lifestyle etc. for our employees. Having high skills and IQ is no excuse for being emotionally immature and unethical. We do not aim to become evil geniuses with high skills but zero ethics. Big data needs bigger ethics!
We are preparing for the “Singularity” through advancing in our technology and products. Singularity has been devised by Ray Kurzweil who is Google’s director of engineering and a well-known futurist with high accuracy record of 86% out of 147 total predictions that he has made since the 1990s.  Singularity is that point in time when AI will lead to machines that are smarter than humans. Ray predicts the singularity to occur by 2045.
At the same time, it’s important for us to reiterate that we are not muddled up in brain fog to envision reality that exists only in science fiction; we have to keep one feet on the ground and one on the sky; one on the present and one on the future; we are not optimistic or realistic; we are pragmatist in that we ourselves are the cultivators of our own souls; we believe in creating the future by improving upon our present It is also important to realize that when everything is changing, what is not changing? Human nature, customer service, lower prices, the need for human connections, the need for a creative outlet for our labor, to feel socially accepted and member of a society and be useful, to come true to your promise, to push the frontier of technology, these will remain the same. Our goals are ambitious because if we aim for the sky at least we can reach the clouds. Regarding actual financial performance and returns, we want to under promise and over deliver.
The Tao recognizes that incremental innovation is mostly just a farce to appear progressive without changing the underlying realities. That is why it perceives incremental innovation as an opponent of exponential innovation. That does not mean that the value of everyday improvement is not realized because "drop by drop still becomes a sea." What is aimed for is the continuous daily work to exponentially innovate and continue reinventing yourselves instead of resting on laurels or complacency. We will continue investing in Research and Development (R & D). More importantly, we believe in R & D and its value in everyday life. We must not be the typical company VPs here who shun research as theoretical and useless and researchers as outcasts. We do not want to become the typical VPs that once we succeed in creating our own markets, that we start defending the status quo itself. The man/woman of knowledge must now be more than a paid wage earner. He/she must ethically change the society otherwise others will. As Plato said that “One of the disadvantages of not participating in politics is that you end up being governed by your inferiors.”
Innovative products, marketing gimmicks, strong social media presence and distribution strategy must also set us apart from the others. New situations in the long-term future will also present its unique set of opportunities and challenges and allow us new solutions to address them. Space travel insurance, love insurance, drone insurance; the sky is the limit to the future and the imagination that it will make a reality. We can’t wait to have our own 3D office and to travel in hyper loop and self-driving electric cars and use block chain and crypto currencies!
Aside from using better tools, we want to utilize a more proactive mentality as well. The traditional reactive approach to modeling has a number of limitations including that time is of the essence for new and emerging products and emerging risks/liabilities/products which are too many and too pervasive; like drone insurance, driverless cars insurance, telematics, cyber insurance, impact of genetic engineering and antibiotic resistance, personalized medicine, 3D printing, growing epidemics, impact of crypto currencies, impact of new generation millennial and disruptive fintech‘, impact of rapidly changing weather, impact of crowd sourcing and collective wisdom like prediction markets and others. Changing market conditions are also there; permanent lower prices of oil, increase in alternative investments like impact investing, rise in Islamic finance like Islamic insurance or takaful and so on.
If we keep waiting until credible data emerges, we will forever remain behind and less influential than others as changes are very rapidly oscillating and it seems that there will always be new emerging products and landscapes. New risks, products and liabilities are emerging and are becoming antiquated before they can even ossify. Constant revolutionizing of technology constantly keeps our social relations in everlasting uncertainty. Pre-emptive action and pro-active in the nick-of-time involvement is now perhaps the only way for us to go about dealing with the rapid fast moving present and future. The STEEP framework for emerging risk analysis is useful for us where the acronym STEEP means Social, Technological, Economic, Environment and Political. 
It is emphasized that emerging risks do not suddenly appear from nowhere and that there are always possible leading indicators, even though they may be rare and difficult to comprehend. Emerging risks are the contextual product of an evolutionary process these take time to develop and reveal themselves.
Hence the Tao business model features in summary are:
- Simplicity, naturelesness through transparency; allow humans to become more humans and machines more machines; bring in play and childishness;
- Tao is adaptable; no fixed dogma, it is fluid; everything is changing nothing is fixed.
- Spontaneity through reduced times automation, simplicity
- Our work and actions must benefit society
- Effortless action; leader acts as the invisible guide and the communities say that we have done it ourselves; global consciousness
- Personalization; everyone is unique and has his/her own way of Tao.
3. Challenges to The Tao Model
Challenges to the Tao model are many and described in context here for insuretech only. The challenges are then further divided into specific challenges for insuretech and generic challenges that faces all technology.
The specific challenges for insuretech are:
- Lack of domain knowledge in insurance. Insurance is different from other businesses but techies and VC undermine the domain specific knowledge required for insurance. The singular focus on ‘growth hacking’ and scaling up is not without its risks.
- Lack of experience especially in times of black swan events like natural catastrophes and man-made catastrophes like terrorism, mass shootings, huge fire in hotel or shopping mall etc.
- Insuretech have done a lot of hyper building and bashing insurers; the higher the commitments, the higher the backlash in case of some scandal or non-fulfillment of expectations.
- Toxic culture inherited by Silicon Valley’s ruthlessness and insane work ethic; uber is a glaring example of this. If employers get ruined from burnouts then how can they sustain their pace? Danger of labor rights evaporating into the darkness.
- Cyber hacking ruins the fledging startup
- Protection gaps; the products are simple but coverage is non-comprehensive as well. We need more insurance not less of it
- Lack of adequate capital protection and deep pockets. Startups don’t even have 1% of the capitals that huge insurers have.
- Lack of structure which means they cannot avail the benefits of having a robust structure. Other vital functions ignored like insurance skills, risk management, HR, institution building etc.
- Lack of access to formal funding which is insufficiently filled by Venture Capitalists. Formal funding is too risk averse to give loans and invest in startups.
- Contagion risk for the insuretech movement. If one big name in insuretech fails like let’s say lemonade, then countless other insuretech will be harmed as well from this huge shock.
- Lack of regulatory clearance. Regulators can ignore some aspects but only catch up and then term it illegal or ban it outright or introduces fines; this happened in price optimization in insurance. China has banned ICO of cryptocurrencies because of its potential for money laundering. Such regulatory backlash can have severe consequences. 
- And so on.
The generic challenges for insuretech and indeed the wider technological forces at work are:
- We don’t replace labor rights and end up exploiting them like freelancers are exploited;
- Terror of automation; require broader social action like universal basic income. Only small highly skilled tech guys working 24/7 and the rest 99.99% of humanity left to rot in ‘Mad Max’ type of dystopia.
- Social scare; we end up creating poor and trillionaires;
- AI takes over like Elon Musk says that we can bring genie out of the bottle but have no control once it’s out of the bottle.
- Changing ideology alone without improving materialist aspects is doomed to disillusionment. (Zizek). We can use all the eastern spirituality terms to cover up the hideous materialistic ambitions beneath it (consumerism, endless greed, inequality, commodification, turning every notion from ‘sacred to profane’ as Marx puts it) but it won’t change the reality. This would be nothing new; wars are fought for oil but under the covers of freedom and other noble words; nationalists talk about dying for countries but never about killing for countries and so on.
Algorithms are increasingly determining how we think and this is relevant not just for policy makers, but for everyone else in general as well. Amidst all these rapid changes, it seems our focus on ethics is becoming less and less. Advertising and consumer analytics is so advanced in getting into our unconscious psyche that it feels that it has become psychological warfare without regards to national boundaries. The information and innovation overload has made us more passive and docile and less independent in our thinking. In a nutshell, big data needs bigger ethics.
But even beyond diplomacy and cyber wars, there are profound sociological implications of big data as well. The Vault 7 wikileaks showed that CIA has previously unthinkable arsenal of hacking tools and that nothing is safe from being monitored. The hackings on global scale especially shows the vulnerabilities of Android and OS systems and that smart cars and smart tvs of Samsung were able capable of being hacked using zero day exploits. 1984 novel of George Orwell rings an alarm bell in us as to where we are going as a society and the increasingly pervasive surveillance of ‘big brother’. Making humans redundant, dumber, more passive, docile and obedient (Michel Foucault’s panoptican system rings a bell?). Publication relations firms strive to ‘manufacture consent’ (Noam Chomsky) and control our minds through trumped persuasion, playing on our cognitive biases and collective irrationality (James Garvey in the book ‘The Persuaders’).
Now imagine giving them arsenal of big data and alogrithms. It will be like giving nuclear bombs to propagandists. We have to attempt to do away with public relations and propaganda instead of letting technology go in their hands to increase their control on our thoughts even more. Marx was accurate in his realization that the ‘bourgeoisie’ cannot exist without constantly revolutionizing the means of productions. By constant revolution in technology, ‘all that is solid melts into the air’, we are left with perpetual anxiety in keeping up with the pace of technology, all the while it continues to be used by the few to dominate the others.
Kitsungi says that imperfect experience is still to be cherished. Both philosophers Rikyu and Basho remind us not be dazzled by extraordinary but relish in the ordinary. Our quest for perfection through technology and other means can also be our undoing. We can eliminate pain points but create more pain too; simple rejecting older ideals for the sake of rejection is not a good practice; so is the practice of not being content with the present. The Japan of his era had grown image-conscious and money-focused. Riky? promoted an alternative set of values which he termed wabi-sabi — a compound word combining wabi, or simplicity, with sabi, an appreciation of the imperfect. Across fields ranging from architecture to interior design, philosophy to literature, Riky? awakened in the Japanese a taste for the pared down and the authentic, for the undecorated and the humble.
Because in Zen philosophy, everything is impermanent, imperfect and incomplete, objects which are themselves marked by time and haphazard marks can, suggested Riky?, embody a distinct wisdom and promote it in their users.
In an age that worships youth, perfection and the new, the art of Kintsugi retains a particular wisdom – as applicable to our own lives as it is to a broken tea cup. The care and love expended on the shattered pots should lend us the confidence to respect what is damaged and scarred, vulnerable and imperfect – starting with ourselves and those around us.
So are we creating insuretech to create better insurance but missing out on Kintsugi of experience, domain skills, and ability to handle natural catastrophes of traditional insurers?
4. Future Outlook of Our Collective Samsara
Samsara translates as wandering, a Ronin warrior without a master, and conversely, nirvana translates as liberation from samsara cycle of aimless wandering. Very few human individuals have ever been able to achieve enlightenment and in groups and masses, humans degenerate into the worst of all creatures, capable of the worst violence towards its own species from wars, weapons, poverty, and exploitation to oppression of the highest orders towards nature and other species.
Human nature will remain the same despite the technology, unless of course we make brain-computer interfaces that makes our IQ 10,000 (a score of between 90 to 110 is termed average IQ human and above 130 is termed gifted. Einstien and Stephan hawking have 160 IQ; Softbank is trying to do exactly this by 2030; ; there’s also neural lace of Elon Musk and many others ). These fundamental similarities are what we have to tap to cure our collective suffering and increase our happiness like customer service, lower prices, the need for human connections, the need for a creative outlet for our labor and play, to feel socially accepted and member of a society and be useful, to come true to your promise, to push the frontier of technology etc. and so on.
It is important to clarify the rapid changes instead of becoming mystified by them. We are currently living at the intersection of Risk Society and Knowledge Society. Knowledge Society is where knowledge has now superseded both capital and labor as the factor of productions employed by the society. Like investing capital leads to greater capital, knowledge production is becoming self-sufficient too. It is a utility, a public good, a private good and ultimately a commodity now in today‘s society but the distinct feature is that it is changing the nature of commodities itself.
As for Risk Society, Ulrich Beck defines Risk Society as: “a systematic way of dealing with hazards and insecurities induced and introduced by modernisation itself.” (Beck, U. 1992)
Financial contagions such as the financial crisis of 2008, EU crisis over Greece sovereign debt, impact of shale oil in recent years especially 2014 to present over oil producing economies particularly Russia as well as environmental crisis likes global warming, Chernobyl melting of nuclear reactor etc. are living and breathing proof of the risk society. Cyber hacking and terrorism from armed radical groups are also part of the manufactured risks of the risk society.
It is not just man-made events but natural disasters too are ever on the increase worldwide. Munich Re study shows that over the past few decades, loss events related to weather increased by 5 times in North America, by 4 times in Asia, 2.5 times in Africa and 2 times in Europe respectively. Munich Re data also shows that large proportion of these losses occurs due to climate change.
Living at the intersection of knowledge and risk society presents the paradox where we have more opportunities to apply and gain from knowledge and skills but that we are simultaneously more vulnerable and fragile to increasing crises and compounding of manufactured risks which risks us losing our civilization. However, this is not surprising for complexity science which formulates a powerful idea for such experiences. We live at the edge of the chaos ‘where we are both strong and fragile at the same time. This duality is important when trying to forecast what the future holds for us.
Broadly, there are two scenarios for forecasting what the future holds for us.  First is the optimistic scenario and second is the pessimistic scenario. In the first (utopia) optimistic scenario there are a number of projections like:
- Automation will lead us humans to play and be more creative and achieve our higher potential rather than wasting our whole lives on redundant work
- Universal basic income will eliminate absolute poverty and economic insecurity; this will in turn fuel entrepreneurship.
- 3D printing, IoT, robotics will mow down costs leading to post-capitalist era where there is plenty for everyone and no scarcity. Humans will be able to live to advance humanity, not their own selfish interests and not there just to survive.
- Environment will be redeemed through sustainable renewable energy like solar and geothermal. Mars will be colonized as well as moon. Scientific breakthroughs will allow us unprecedented understanding and mastery of our external environment.
- Genetic engineering like CRISPR, nano-technology etc. will eliminate diseases. We might even become immortal or have significantly higher life spans (if you think this is crazy see Aubrey De Gray’s work).
- And so on; you get the idea.
Likewise in the second pessimistic (dystopia) scenario, there are a number of projections like:
- Iron fist of algorithms and Artificial Intelligence upon us rendering us helpless and eliminating us humans just like what Elon Musk, Stephan Hawking and others warn us about
- Space mining of trillions worth of minerals, owning robots and algorithms by the extreme few like tech giants while making all the remaining unemployed leading to fanatical inequality and polarity; trillionaires and extreme poverty living simultaneously
- Autocratic governments eliminating freedom, choice, democracy, free will through technology and using it to brain wash us (if you think this is far off; see subliminal advertising; Orwell, China’s plan for the future social rating of its citizens and so on).
- And so on, you get the idea.
Basing my assumptions on complexity science, I would like to suggest a third scenario of escalation. In this third scenario we are likely to face increasing opportunities as well as increasing challenges at the same time (come to think of it; just because there is Star Trek technology doesn’t mean that Star Trek faces no problems; just because X-men are mutants and there is superman and justice league doesn’t mean that they face no opponents and no challenges):
- Technology will make us super-powerful but cyber hacking will leave us fragile in that it can create chaos anytime
- We will have better technology to weather natural catastrophes, but global warming will further increase natural catastrophes too
- Our weapons will become far more powerful than ever; but so will our medicines
- Our conflicts will become more pervasive like space warfare (US General says America is 3 years away from potentially have operational space force, Vladimir Putin saying that country that leads in AI will become ruler of the world) our appeals for peace and prosperity and chances of universal brotherhood will increase as well.
- We will eliminate most of our current diseases, but new ones will surface up like new diseases from tampering with genetics of human babies, animals, natural environments and so on
- Applying it specifically to business, we will redefine risks and business and eliminate most of current risks, like human driving errors, current diseases, 3D printing mowing down property/buildings prices but new risks will emerge and new insurance and business will arise then to handle these new risks.
- And so on.
So the question for which there is no answer is that can we escape the banalities and samsara of human society and become as innocent as a child? Only few individuals have achieved enlightenment but can we as a group, and as a society and species become enlightened?
5. Final Words: Tying the 6 Knots.
We should attempt to creatively synthesize the many pluralistic approaches as well as focus more on synergistic interpretation of findings of these pluralistic researches.
We can recognize that though we cannot precisely predict black swans but forecasting emerging liabilities and their ratemaking can be a professional-character building experience in itself where we train to be better evolvers rather than better predictors alone.
We can highlight that while recognizing facts (in form of quantitative analysis), it seems as if we only tend to scratch its surface as data, on its own, highlights results; whereas there are plenty of processes that culminate in data generation as well as modeling methodology in the first place. There is an incredible depth once when we start looking beyond the facts into fact-making itself; and this is where expert judgment and qualitative profiling can prove invaluable to guide the modeling exercise.
Agile Risk culture is foremost for any modeling exercise because complex systems like financial and insurance sector are not solely run by quantitative numbers, but by the underlying human psychology as well. It is up to the risk culture to not antagonize in binary opposites like complex/simple, good/bad etc., but to reach the middle ground to converge communication and mentalities between different stakeholders.
- We suffer too profoundly even from small data glitches.
- Better than many complicated equations are few statements that give clarity to shareholders
- The experience of all deep datasets is slow. They must wait long until they know what has fallen into their depths. Machine learning can lower that waiting time.
- Generally, there is either over-reliance on data and models or negligible reliance on them. We have to be familiar with the golden mean that resides between two vices. So here our data and modeling orientation should be in between the extremes of reliance on only opinions and only data and models.
- Unless one considers intention—philosophy, cognitive system, behavioral bias, etc.—used in building data, models and expert’s analysis, and implications, one can be missing the big picture already.
- Provide historical data to limit the amount of work required for attaining a context for the data but data should be adjusted to reflect current conditions, not historical circumstances.
- Focus on developing a ratemaking plan, not numerical premium and projections only.
- Know your context.
- Beware of qualitative shifts
- Know how the model results will be used
- Do not anthropomorphize models. Anthropomorphism is the tendency to characterize animals, objects, and abstract concepts as possessing human-like traits, emotions, and intentions. Models are not reality or real human social behavior. At best models are idols; at worst a distraction and cause for herding.
In conclusion, it is hoped that this review was able to lead to a better understanding of the inherent realities and trends in defining the Tao business model that is made for the future and compels us to view this exercise holistically so as to bear more fruitful results. It is also meant to contribute fruitfully to the current existing dialogue on futurism and discussions on business models for the future.
 Kairos Doulas; Kairosdo Dec 2014: The Tao does nothing, and nothing is left undone. Available at: http://www.kairosdoulas.com/the-tao-does-nothing-and-nothing-is-left-undone/
 University of London International Blog: Syed Danish Ali; Jan 28, 2016: The Philosopher-Actor Bruce Lee. Available at: https://londoninternational-blog.com/2016/01/28/the-philosopher-actor-bruce-lee/
 The Digital Insurer; Hugh Terry; Digital Insurance in Action section. Available at: https://www.the-digital-insurer.com/dia/guevara-peer-to-peer-car-insurance/
 Suzuki, Shunryu (1970). Zen Mind, Beginner's Mind
 Kdnuggets. Hamel Husain & Nick Handel; Automated Machine Learning; A paradigm shift that accelerates data scientist productivity; Available at: https://www.kdnuggets.com/2017/07/automated-machine-learning-paradigm-shift.html
 Aarshay Jain; May 5, 2016. 19 Data science tools for people who aren’t so good at programming. Available at: https://www.analyticsvidhya.com/blog/2016/05/19-data-science-tools-for-people-dont-understand-coding/
 DataRobot; Nov 22, 2017; Colin Priest : Let your data scientists be human. Available at: https://www.datarobot.com/blog/let-data-scientists-human/
 Phil Papers: Syed Danish Ali; Philosophical & Sociological Inquires in Material Aspects of the Human Life namely Risk, Finance and Insurance. Available at: https://philpapers.org/archive/ALIPS.pdf
 In fact, see this amazing cognitive bias cheat sheet, by Buster Benson, here: https://betterhumans.coach.me/cognitive-bias-cheat-sheet-55a472476b18
 Futurism.com; Dom Galeon and Christianna Reedy; October 5,2017. Kurzweil claims that the singularity will happen by 2045. Available at: https://futurism.com/kurzweil-claims-that-the-singularity-will-happen-by-2045/
 Casualty Actuarial Society Working Papers: June 2016; Syed Danish Ali: Ratemaking for Emerging Liabilities in Property & Casualty Insurance: Practical Tools and Enriching Imagination : Available at: http://www.casact.org/research/wp/papers/working-paper-Ali3-2017-08.pdf
 Futurism.com; Kirstin Houser; Sep 11, 2017; According to Chinese official, china’s ban on ICOs is temporary; Available at: https://futurism.com/according-to-chinese-official-chinas-ban-on-initial-coin-offerings-is-only-temporary/
 See Zizek: Cabinet Magazine; 2001; From western Marxism to western Buddhism Available at: http://www.cabinetmagazine.org/issues/2/western.php
 Noreen Joslyn; Familyeducation.com. Available at: https://www.familyeducation.com/school/signs-giftedness/gifted-person-average-iq
 Titli Basu; Listovative: Top 12 people with highest IQ in the world: Available at: http://listovative.com/top-12-people-highest-iq-world/
 Futurism.com. Dom Galeon; Oct 27, 2017. SoftBank CEO promises super artificial intelligences with IQ of 10,000 in 30 years; Available at: https://futurism.com/softbank-ceo-promises-super-artificial-intelligences-with-iq-of-10000-in-30-years/
 Futurism.com; Dom Galeon and Christianna Reedy; October 5,2017. Kurzweil claims that the singularity will happen by 2045. Available at: https://futurism.com/kurzweil-claims-that-the-singularity-will-happen-by-2045/
 Wired.com; Cade Metz; Mar 31, 2017; Elon Musk isn’t the only one trying to computerize your brain. Available at: https://www.wired.com/2017/03/elon-musks-neural-lace-really-look-like/
 Drucker, P. (1993),?The Rise of the Knowledge Society?, Harvard Business Review
 Beck, U. (1992). Risk Society, Towards a New Modernity. London: Sage Publications. pg 260.
 Mortimer, S; Munich Re, (2012), Reinsurers should price in rise in natural disasters-Munich Re, Reuters.
 Mills, Allan: Society of Actuaries (2010): Complexity Science: an introduction and invitation for actuaries.
 William E Halal. Elsevier Technological Forecasting & Social Change 80 (2013) 1635–1643; Forecasting the Technology Revolution: Results and learning from the TechCast Project; Available at: https://www.cepal.org/ilpes/noticias/paginas/4/53544/Forecasting_Technology_Revolution_Result_TechCast_Project.pdf
 Journal of Futures Studies, December 2016, 21(2): 83–96 ; William Halal, Jonathan Kolber, Owen Davies; Forecasts of AI and Future Jobs in 2030: Muddling Through Likely, with Two Alternative Scenarios Available at: http://jfsdigital.org/wp-content/uploads/2017/01/JFS212Final%EF%BC%88%E5%B7%B2%E6%8B%96%E7%A7%BB%EF%BC%89-6.pdf
 FT.com; Hugo Cox, Feb 2017; Aubrey De Grey: scientist who says humans can live for 1,000 years. Available at https://www.ft.com/content/238cc916-e935-11e6-967b-c88452263daf
 Futurism.com; Brad Jones; Nov 14,2017; Air Force General says the US could have an operational Space Force in Three years. Available at: https://futurism.com/air-force-general-us-operational-space-force-three-years/
 Futurism.com; Patrick Caughill; Sep 2, 2017; Vladimir Putin: Country that leads in AI Development Will be the ruler of the world. Available at: https://futurism.com/vladimir-putin-country-that-leads-in-ai-development-will-be-the-ruler-of-the-world/
 Mills, Allan: Society of Actuaries (2010): Complexity Science: an introduction and invitation for actuaries
 Data Science Central; June 20, 2016: Syed Danish Ali: Modeling Meditations. Available at: https://www.datasciencecentral.com/profiles/blogs/modeling-meditations
 Data Science Central; June 20, 2016: Syed Danish Ali: Inspiring Imagination in data science qualitative profiling. Available at: https://www.datasciencecentral.com/profiles/blogs/inspiring-imagination-in-data-science-qualitative-profiling
 Werther, SOA 2013. Recognizing When Black Swans Aren’t: Holistically Training Management to Better Recognize, Assess and Respond to Emerging Extreme Events
 Wilmott, P. & Derman, E, 2009. The Financial Modelers’ Manifesto
All Public Comments
© 2013-2017 TechCast Global Inc Printed By: Dec 10, 2018 For personal use only