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Without causing any particular media attention, Verily, Alphabet’s company focusing on health, has just launched its insurance company, Coefficient Insurance. Thanks to the data collected over years through Google, Coefficient Insurance is able to assess our risk better than any other insurance company. Currently, the insurance company will focus on a niche sector: insurance policies that protect employers against employees health costs volatility. However, the plan is to expand to the whole insurance sector and offer B2C insurance policy to the whole Google customer base (i.e.: the whole world). According to Verily executives, the company can start to monitor its customers through their phones and influence them towards a healthier lifestyle. Obviously, this business model for the hub economy is not new. Indeed, there are a lot of digital hubs that plan to expand into the healthcare / insurance sector. Alexa (Amazon) and DeepMind (Alphabet) both concluded contracts with the national health service of the UK. Apple signed a partnership with Aetna, and together developed an App that uses Apple Watches’ data to assess insurance customers’ lifestyles and adjust the insurance premia. Lastly, at the end of 2019, Facebook launched Preventive Health aiming at educating its users about the importance of healthcare prevention (e.g.: undergo regular checks).
Facebook, through Coefficient Insurance, claims to reduce the load on the health care system by giving users an in-depth analysis of their lifestyle. Nevertheless, Facebook often has an ulterior motive. One has to be naïve to believe that such a system would favor the weak and the sick. There will be positive effects, such as the promotion of a healthy lifestyle or digital tracking. The latter is especially important now with COVID and Alphabet can play a big role. However, there is a big question in my mind: do we really want that our health data have an impact on our insurance policy pricing?
The situation is worsened by current antitrust and privacy laws. Antitrust regulations have not proven effective in the digital economy. For instance, antitrust authorities could not deny Fitbit acquisition by Google. Especially now that Google is entering the insurance business this acquisition is worrisome. Privacy laws are also inadequate. Employees, pressured by their employers, accept to be monitored through their companies’ computers. This problem already existed before Google entered the insurance business. However, now companies are offered very intense surveillance system in order to reduce their employees’ health costs.
The insurance sector is only a part of a bigger problem. Indeed, politicians have a hard time to redistribute the enormous power of connected digital hubs. With positive network effect, it is a new market equilibrium that the power gets increasingly concentrated in ecosystem hubs. The latter increases popular resentment towards the elite and favors conspiracy theories. Politicians, instead of facing the problem and protect the weakest in the society, hope in a self-regulating system (Adam Smith invisible hand). As suggested in the article “Managing our hub economy” “All actors in the economy—but particularly the hub firms themselves—should work to sustain the entire ecosystem and observe new principles, for both strategic and ethical reasons. Otherwise, we are all in serious trouble.” I believe this can happen if customers and investors pressure the hub giants forcing them to follow a more ethical behavior, as ROI will always be dominant.

References
Iansiti, M., & Lakhani, K. R. 2018. Managing our hub economy. Harvard Business Review, 96(1), 17-17.
https://corporatesolutions.swissre.com/insights/news/coefficient-employer-stop-loss.html#:~:text=Verily%2C%20an%20Alphabet%20company%2C%20is,novel%20insurance%20and%20payment%20models.

Apple partners with Aetna to launch health app leveraging Apple Watch data

https://www.theverge.com/2019/11/1/20943318/google-fitbit-acquisition-fitness-tracker-announcement

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In 2019, the Apple Card was launched with the aim to deliver higher control, transparency, and privacy standards to its consumers. Similar to Revolut, Apple Card has no fees, daily cash back, and seamless integration in Apple’s mobile devices. Moreover, its main differentiation point is a new level of privacy, security and transparency to credit cards, allowing consumers to quickly and easily analyze their spending patterns and calculate how much they could save in interest charges by paying off different portions of their balances. Goldman Sachs is the official issuer of the card and is responsible for underwriting, customer service, the underlying platform, and regulatory compliance. The slogan for Apple Card is “created by Apple, not a bank”. Nevertheless, this can be misleading as Goldman Sachs decides who gets credits, bears the risk of lending, and collects unpaid debts. Thus, when a recession hits and default rates rise, the Apple Card’s marketing could make it difficult for the bank to chase down debtors, given the potential damage to Apple’s brand and reputation for customer service. At Apple’s request, Goldman also removed late fees and agreed to not sell customer data. It also adopted the tech giant’s signature font for cardholders’ monthly statements.
Having set privacy as top priority of this product, the biggest concern arising from this partnership is the data handling process and its privacy policies. Apple is updating its privacy policy for Apple Card to enable sharing more anonymized data with Goldman Sachs. In the App, when signing in, there is a clear “opt-in / opt-out option”. Choosing the opt-in option, the data sharing is enabled. On the one hand, Goldman Sachs will receive all personal information that Apple owns on that customer. Apple believes that in this way Goldman Sachs will be able to offer credit to people who may be automatically be rejected under the “old way of doing things”. On the other hand, Apple will also get data regarding internal transactions. The data is always aggregate and anonymized. Otherwise, the customer can choose the opt-out and no data will be shared among the two partners.
The amount of data Goldman Sachs will be able to have before making a credit decision will be enormous and can play against or in favor of the customer. Nevertheless, an average co-branded card offer (e.g.: airline card or retailer card) is controlled entirely by the financial services side of the partnership (basically the credit card companies decide what data they get and how). Apple Card, if respects its promises, with the new arrangement outlined in the privacy policy does not share any data point with the opt-out option. There is almost no financial product that offers this option, especially credit cards. I worked in a bank and I can confirm that most cards take all of the above information and much more in their approval process.
Will Apple Card respect its promise?

https://www.goldmansachs.com/our-firm/history/moments/2019-apple-card.html
https://markets.businessinsider.com/news/stocks/goldman-sachs-assigns-apple-card-credit-limits-collects-debts-2020-1-1028823960

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The rapid growth of Bitcoin’s popularity over the last decade has sparked an intense discussion among different stakeholders. The investment community is interested in Bitcoin as it represents a potentially lucrative speculative asset. Policymakers want to better understand the potential implications of the issuance of a central bank digital currency. Data scientists are fascinated by the innovative algorithm, the computing power, the proof-of-work mechanism, and the use of blockchain as a decentralized ledger in order to possibly become miners and make a profit.

In 2008, Satoshi Nakamoto, the founder of Bitcoin, defined Bitcoin as: “A purely peer-to-peer version of electronic cash [which] would allow online payments to be sent directly from one party to another without going through a financial institution.” Thus, Bitcoin is introduced by its creator as a virtual currency. However, the question remains: can Bitcoin be defined as a currency and ultimately substitute traditional money?

Firstly, the textbook definition of money is analyzed. Secondly, Mises money regression theorem is reported and discussed.

Money is defined as anything that is generally accepted in payment for goods, service, or in the repayment for debts. It has three main characteristics: (1) medium of exchange, (2) store of value, and (3) unit of account. Starting with the first characteristic of money, a medium of change (1) must be widely accepted, easily standardized, divisible and easy to carry, and doesn’t have to deteriorate quickly. Bitcoin is not widely accepted and it does deteriorate quickly. (2) A store of value is used to save purchasing power over time. Bitcoin is a very risky and thus a volatile asset which cannot be used as a store of value. Lastly, (3) money must be used to measure all the transactions within an economy (i.e.: it is used as a reference point of the price of all the goods and services offered). Given Bitcoin’s volatility, the latter cannot be done with Bitcoins. Thus, none of the textbook points of money definition is respected by Bitcoin (Investopedia, 2020).

In order to evaluate Bitcoin for its money-like functions and features, we can also apply Mises’ regression theorem and focus mainly on its function as a means of exchange. The latter states that: “It is true that he who considers acquiring or giving away money is, of course, first of all interested in its future purchasing power and the future structure of prices. But he can not form a judgment about the future purchasing power of money otherwise than by looking at its configuration in the immediate past.” (Mises, 1912). The world’s most successful currencies have entered the definition of money throughout a process that has lasted centuries. Indeed, by applying the theorem on these currencies, it is possible to trace back their original value in the barter system. Accordingly, in order to be able to evaluate Bitcoin’s demand through its monetary features (i.e.: mainly its function as a means of exchange), it is necessary to move back to its value as an asset. The value of Bitcoin as a cryptocurrency, and the main driver for its demand, is its network. In fact, “As the number of participants increases so does the number of possible exchanges among the participants and the value of the network services” (Pagnotta & Buraschi, 2018). In a peer-to-peer network, as in the case of Bitcoin, the confidence of one agent in the network justifies his use of Bitcoin as a currency. Indeed, the agent relies on others’ adoption of the currency and on his expectations on others’ adoption of the currency (Mises, 1912). Thus, we can deduct that the value of the crypto-currency depends on the value of its network of users. This notion is called Metcalfe’s Law: “The key measure of value for cryptocurrencies is the network of people who use them” (MIT, 2018). The latter is also mentioned in the article “Competition in the Age of Online Giant” as one of the three principles of digitalization and network theory of the emergence of economic hubs. Bitcoins are already accepted for house purchases in Spain and to pay taxes in Switzerland. The latter opens a promising root for Bitcoin.

To conclude and summarize, considering the state of art I believe Bitcoins cannot substitute our monetary system. Nevertheless, they display several characteristics of an emergent economic hub and in the near future have a high chance of being a real disrupter of our economic system as a whole.

Iansiti, M., & Lakhani, K. R. 2018. Managing our hub economy. Harvard Business Review, 96(1), 17-17.

Investopedia (2020). Money definition. Retrieved from https://www.investopedia.com/terms/m/money.asp

Pagnotta, E., & Buraschi, A. (2018). An equilibrium valuation of bitcoin and decentralized network assets. Available at SSRN 3142022.

Metcalfe, M. (2013). Metcalfe’s Law After 40 Years of Ethernet. Computer, 46(12):26–31.

Mises, L. (1912). Human Action, Theory of Money and Credit. Mises Institute. Retrieved from https://mises.org/library/human-action-0/html/p/605

MIT, (2018). How Network Theory Predicts the Value of Bitcoin. MIT Techonology Review. Retrieved from https://www.technologyreview.com/s/610614/hownetwork-theory-predicts-the-value-of-bitcoin/

Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System.

Nakamoto, S. (2010). Bitcoin Does NOT Violate Mises’ Regression Theorem. Satoshi Nakamoto Institute. Retrieved from https://satoshi.nakamotoinstitute.org/posts/bitcointalk/428/#selection-9.4-9.54