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Tech Book of the Month
  • Tech Book of the Month
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August 2023 - Capital Returns by Edward Chancellor

We dive into an investing book that covers the capital cycle. In summary, the best time to invest in a sector is actually when capital is leaving or has left.

Tech Themes

  1. Amazon. Marathon understands that the world moves in cycles. During the internet bubble of the late 1990s the company refused to invest in a lot of speculative internet companies. “At the time, we were unable to justify the valuations of any of these companies, nor identify any which could safely say would still be going strong in years to come.” In August of 2007, however, several years after the internet bubble burst, they noticed Amazon again. Amazon’s stock had rebounded well from the lows of 2001 and was roughly flat from its May 1999 valuation. Sales had grown 10x since 1999 and while they recognized it had a tarnished reputation from the internet bubble, it was actually a very good business with a negative working capital cycle. On top of this, the reason the stock hadn’t performed well in the past few years was because they were investing in two new long-term growth levers, Amazon Web Services and Fulfillment by Amazon. I’m sure Marathon underestimated the potential for these businesses but we can look back now and know how exceptional and genius these margin lowering investments were at the time.

  2. Semis. Nothing paints a more clear picture of cyclicality than semiconductors. Now we can debate whether AI and Nvidia have moved us permanently out of a cycle but up until 2023, Semiconductors was considered cyclical. As Marathon notes: “Driven by Moore’s law, the semiconductor sector has achieved sustained and dramatic performance increases over the last 30years, greatly benefiting productivity and the overall economy. Unfortunately, investors have not done so well. Since inception in 1994, the Philadelphia Semiconductor Index has underperformed the Nasdaq by around 200 percentage point, and exhibited greater volatility…In good times, prices pick up, companies increase capacity, and new entrants appear, generally from different parts of Asia (Japan in the 1970s, Korea in 1980s, Taiwan in the mid1990s, and China more recently). Excess capital entering at cyclical peaks has led to relatively poor aggregate industry returns.” As Fabricated Knowledge points out the 1980s had two brutal Semiconductor cycles. First, in 1981, the industry experienced severe overcapacity, leading to declining prices while inflation ravaged through many businesses. Then in 1985, the US semiconductor business declined significantly. “1985 was a traumatic moment for Intel and the semiconductor industry. Intel had one of the largest layoffs in its history. National Semi had a 17% decrease in revenue but moved from an operating profit of $59 million to an operating loss of -$117 million. Even Texas Instruments had a brutal period of layoffs, as revenue shrank 14% and profits went negative”. The culprit was Japanese imports. Low-end chips had declined significantly in price, as Japan flexed its labor cost advantage. All of the domestic US chip manufacturers complained (National Semiconductor, Texas Instruments, Micron, and Intel), leading to the 1986 US-Japan Semiconductor Agreement, effectively capping Japanese market share at 20%. Now, this was a time when semiconductor manufacturing wasn’t easy, but easier than today, because it focused mainly on more commoditized memories. 1985 is an interesting example of the capital cycle compounding when geographic expansion overlaps with product overcapacity (as we had in the US). Marathon actually preferred Analog Devices, when it published its thesis in February 2013, highlighting the complex production process of analog chips (physical) vs. digital, the complex engineering required to build analog chips, and the low-cost nature of the product. “These factors - a differentiated product and company specific “sticky” intellectual capital - reduce market contestability….Pricing power is further aided by the fact that an analog semiconductor chip typically plays a very important role in a product for example, the air-bag crash sensor) but represents a very small proportion of the cost of materials. The average selling price for Linear Technology’s products is under $2.” Analog Devices would acquire Linear in 2017 for $14.8B, a nice coda to Marathon’s Analog/Linear dual pitch.

  3. Why do we have cycles? If everyone is playing the same business game and aware that markets come and go, why do we have cycles at all. Wouldn’t efficient markets pull us away from getting too hyped when the market is up and too sour when the market is down? Wrong. Chancellor gives a number of reasons why we have a capital cycle: Overconfidence, Competition Neglect, Inside View, Extrapolation, Skewed Incentives, Prisoner’s Dilemma, and Limits to Arbitrage. Overconfidence is somewhat straightforward - managers and investors look at companies and believe they are infallible. When times are booming, managers will want to participate in the boom, increasing investment to match “demand.” In these decisions, they often don’t consider what their competitors are doing, but rather focus on themselves. Competition neglect takes hold as managers enjoy watching their stock tick up and their face be splattered across “Best CEO in America” lists. Inside View is a bit more nuanced, but Michael Mauboussin and Daniel Kahneman have written extensively on it. As Kahneman laid out in Thinking, Fast & Slow: “A remarkable aspect of your mental life is that you are rarely stumped … The normal state of your mind is that you have intuitive feelings and opinions about almost everything that comes your way. You like or dislike people long before you know much about them; you trust or distrust strangers without knowing why; you feel that an enterprise is bound to succeed without analyzing it.” When you take the inside view, you rely exclusively on your own experience, rather than other similar situations. Instead, you should take the outside view and assume your problem/opportunity/case is not unique. Extrapolation is an extremely common driver of cycles, and can be seen all across the investing world after the recent COVID peak. Peloton, for example, massively over-ordered inventory extrapolating out pandemic related demand trends. Skewed incentives can include near-term EPS targets (encourages buybacks, M&A), market share preservation (encourages overinvestment), low cost of capital (buy something with cheap debt), analyst expectations, and champion bias (you’ve decided to do something and its no longer attractive, but you do it anyway because you got people excited about it). The Prisoner’s Dilemma is also a form of market share preservation/expansion, when your competitor may be acting much more aggressively and you have to decide whether its worth the fight. Limits to Arbitrage is almost an extension of career risk, in that, when everyone owns an overvalued market, you may actually hurt your firm by actively withholding even if it makes investment sense. That’s why many firms need to maintain a low tracking error against indexes, which can naturally result in concentrations in the same stocks.

Business Themes

The-Capital-Cycle.jpg
  1. Capital Cycle. The capital cycle has four stages: 1. New entrants attracted by prospect of high returns: investor optimistic 2. Rising competition causes returns to fall below cost of capital: share price underperforms 3. Business investment declines, industry consolidation, firms exit: investors pessimistic 4. Improving supply side causes returns to rise above the cost of capital: share price outperforms. The capital cycle reveals how competitive forces and investment behavior create predictable patterns in industries over time. Picture it as a self-reinforcing loop where success breeds excess, and pain eventually leads to gain. Stage 1: The Siren Song - High returns in an industry attract capital like moths to a flame. Investors, seeing strong profits and growth, eagerly fund expansions and new entrants. Optimism reigns and valuations soar as everyone wants a piece of the apparent opportunity. Stage 2: Reality Bites - As new capacity comes online, competition intensifies. Prices fall as supply outpaces demand. Returns dip below the cost of capital, but capacity keeps coming – many projects started in good times are hard to stop. Share prices begin to reflect the deteriorating reality. Stage 3: The Great Cleansing - Pain finally drives action. Capital expenditure is slashed. Weaker players exit or get acquired. The industry consolidates as survivors battle for market share. Investors, now scarred, want nothing to do with the sector. Capacity starts to rationalize. Stage 4: Phoenix Rising - The supply-side healing during the downturn slowly improves industry economics. With fewer competitors and more disciplined capacity, returns rise above the cost of capital. Share prices recover as improved profitability becomes evident. But this very success plants the seeds for the next cycle. The genius of understanding this pattern is that it's perpetual - human nature and institutional incentives ensure it repeats. The key is recognizing which stage an industry is in, and having the courage to be contrarian when others are either too optimistic or too pessimistic.

  2. 7 signs of a bubble. Nothing gets people going more than Swedish Banking in the 2008-09 financial crisis. Marathon called out its Seven Deadly Sins of banking in November 2009, utilizing Handelsbanken as a positive reference, highlighting how they avoided the many pitfalls that laid waste to their peers. 1. Imprudent Asset-Liability mismatches on the balance sheet. If this sounds familiar, its because its the exact sin that took down Silicon Valley Bank earlier this year. As Greg Brown lays out here: “Like many banks, SVB’s liabilities were largely in the form of demand deposits; as such, these liabilities tend to be short term and far less sensitive to interest rate movement. By contrast, SVB’s assets took the form of more long-term bonds, such as U.S. Treasury securities and mortgage-backed securities. These assets tend to have a much longer maturity – the majority of SVB’s assets matured in 10 years or more – and as a result their prices are much more sensitive to interest rate changes. The mismatch, then, should be obvious: SVB was taking in cash via short-term demand deposits and investing these funds in longer-term financial instruments.” 2. Supporting asset-liability mismatches by clients. Here, Chancellor calls out foreign currency lending, whereby certain European banks would offer mortgages to Hungarians in swiss francs, to buy houses in Hungary. Not only were these banks taking on currency risk, they were exposing their customers to it and many didn’t hedge the risk out appropriately. 3. Lending to “Can’t Pay, Won’t Pay” types. The financial crisis was filled with banks lending to subprime borrowers. 4. Reaching for growth in unfamiliar areas. As Marathon calls out, “A number of European banks have lost billions investing in US subprime CDOs, having foolishly relied on “experts” who told them these were riskless AAA rated credits.” 5. Engaging in off-balance sheet lending. Many European banks maintained "Structured Investment Vehicles” that were off-balance sheet funds holding CDOs and MBSs. At one point, it got so bad that Citigroup tried the friendship approach: “The news comes as a group of banks in the U.S. led by Citigroup Inc. are working to set up a $100 billion fund aimed at preventing SIVs from dumping assets in a fire sale that could trigger a wider fallout.” These SIVs held substantial risk but were relatively unknown to many investors. 6. Getting sucked into virtuous/vicious cycle dynamics. As many European banks looked for expansion, they turned to lending into the Baltic states. As more lenders got comfortable lending, GDP began to grow meaningfully, which attracted more aggressive lending. More banks got suckered into lending in the area to not miss out on the growth, not realizing that the growth was almost entirely debt fueled. 7. Relying on the rearview mirror. Marathon points out how risk models tend to fail when the recent past has been glamorous. “In its 2007 annual report, Merrill Lunch reported a total risk exposure - based on ‘a 95 percent confidence interval and a one day holding period’ - of $157m. A year later, the Thundering Herd stumbled into a $30B loss!”

  3. Investing Countercyclically. Björn Wahlroos exemplified exceptional capital allocation skills as CEO of Sampo, a Finnish financial services group. His most notable moves included perfectly timing the sale of Nokia shares before their collapse, transforming Sampo's property & casualty insurance business into the highly profitable "If" venture, selling the company's Finnish retail banking business to Danske Bank at peak valuations just before the 2008 financial crisis, and then using that capital to build a significant stake in Nordea at deeply discounted prices. He also showed remarkable foresight by reducing equity exposure before the 2008 crisis and deploying capital into distressed commercial credit, generating €1.5 billion in gains. Several other CEOs have demonstrated similar capital allocation prowess. Henry Singleton at Teledyne was legendary for his counter-cyclical approach to capital allocation. He issued shares when valuations were high in the 1960s to fund acquisitions, then spent the 1970s and early 1980s buying back over 90% of Teledyne's shares at much lower prices, generating exceptional returns for shareholders. As we saw in Cable Cowboy, John Malone at TCI (later Liberty Media) was masterful at using financial engineering and tax-efficient structures to build value. He pioneered the use of spin-offs, tracking stocks, and complex deal structures to maximize shareholder returns while minimizing tax impacts. Tom Murphy at Capital Cities demonstrated exceptional discipline in acquiring media assets only when prices were attractive. His most famous move was purchasing ABC in 1985, then selling the combined company to Disney a decade later for a massive profit. Warren Buffett at Berkshire Hathaway has shown remarkable skill in capital allocation across multiple decades, particularly in knowing when to hold cash and when to deploy it aggressively during times of market stress, such as during the 2008 financial crisis when he made highly profitable investments in companies like Goldman Sachs and Bank of America. Jamie Dimon at JPMorgan Chase has also proven to be an astute capital allocator, particularly during crises. He guided JPMorgan through the 2008 financial crisis while acquiring Bear Stearns and Washington Mutual at fire-sale prices, significantly strengthening the bank's competitive position. D. Scott Patterson has shown excellent capital allocation skills at FirstService. He began leading FirstService following the spin-off of Colliers in 2015, and has compounded EBITDA in the high teens via strategic property management acquistions coupled with large platforms like First OnSite and recently Roofing Corp of America. Another great capital allocator is Brad Jacobs. He has a storied career building rollups like United Waste Systems (acquired by Waste Services for $2.5B), United Rentals (now a $56B public company), XPO logistics which he separated into three public companies (XPO, GXO, RXO), and now QXO, his latest endeavor into the building products space. These leaders share common traits with Wahlroos: patience during bull markets, aggression during downturns, and the discipline to ignore market sentiment in favor of fundamental value. They demonstrate that superior capital allocation, while rare, can create enormous shareholder value over time.

    Dig Deeper

  • Handelsbanken: A Budgetless Banking Pioneer

  • ECB has created 'toxic environment' for banking, says Sampo & UPM chairman Bjorn Wahlroos

  • Edward Chancellor part 1: ‘intelligent contrarians’ should follow the capital cycle

  • Charlie Munger: Investing in Semiconductor Industry 2023

  • Amazon founder and CEO Jeff Bezos delivers graduation speech at Princeton University

tags: Amazon, Jeff Bezos, National Semiconductor, Intel, Moore's Law, Texas Instruments, Micron, Analog Devices, Michael Mauboussin, Daniel Kahneman, Peloton, Handelsbanken, Bjorn Wahlroos, Sampo, Henry Singleton, Teledyne, John Malone, D. Scott Patterson, Jamie Dimon, Tom Murphy, Warren Buffett, Brad Jacobs
categories: Non-Fiction
 

March 2021 - Payments Systems in the U.S. by Carol Coye Benson, Scott Loftesness, and Russ Jones

This month we dive into the fintech space for the first time! Glenbrook Partners is a famous payments consulting company. This classic book describes the history and current state of the many financial systems we use every day. While the book is a bit dated and reads like a textbook, it throws in some great real-world observations and provides a great foundation for any payments novice!

Tech Themes

  1. Mapping Open-Loop and Closed-Loop Networks. The major credit and debit card providers (Visa, Mastercard, American Express, China UnionPay, and Discover) all compete for the same spots in customer wallets but have unique and differing backgrounds and mechanics. The first credit card on the scene was the BankAmericard in the late 1950’s. As it took off, Bank of America started licensing the technology all across the US and created National BankAmericard Inc. (NBI) to facilitate its card program. NBI merged with its international counterpart (IBANCO) to form Visa in the mid-1970’s. Another group of California banks had created the Interbank Card Association (ICA) to compete with Visa and in 1979 renamed itself Mastercard. Both organizations remained owned by the banks until their IPO’s in 2006 (Mastercard) and 2008 (Visa). Both of these companies are known as open-loop networks, that is they work with any bank and require banks to sign up customers and merchants. As the bank points out, “This structure allows the two end parties to transact with each other without having direct relationships with each other’s banks.” This convenient feature of open-loop payments systems means that they can scale incredibly quickly. Any time a bank signs up a new customer or merchant, they immediately have access to the network of all other banks on the Mastercard / Visa network. In contrast to open-loop systems, American Express and Discover operate largely closed-loop systems, where they enroll each merchant and customer individually. Because of this onerous task of finding and signing up every single consumer/merchant, Amex and Discover cannot scale to nearly the size of Visa/Mastercard. However, there is no bank intermediation and the networks get total access to all transaction data, making them a go-to solution for things like loyalty programs, where a merchant may want to leverage data to target specific brand benefits at a customer. Open-loop systems like Apple Pay (its tied to your bank account) and closed-loop systems like Starbuck’s purchasing app (funds are pre-loaded and can only be redeemed at Starbucks) can be found everywhere. Even Snowflake, the data warehouse provider and subject of last month’s TBOTM is a closed-loop payments network. Customers buy Snowflake credits up-front, which can only be used to redeem Snowflake compute services. In contrast, AWS and other cloud’s are beginning to offer more open-loop style networks, where AWS credits can be redeemed against non-AWS software. Side note - these credit systems and odd-pricing structures deliberately mislead customers and obfuscate actual costs, allowing the cloud companies to better control gross margins and revenue growth. It’s fascinating to view the world through this open-loop / closed-loop dynamic.

  2. New Kids on the Block - What are Stripe, Adyen, and Marqeta? Stripe recently raised at a minuscule valuation of $95B, making it the highest valued private startup (ever?!). Marqeta, its API/card-issuing counterpart, is prepping a 2021 IPO that may value it at $10B. Adyen, a Dutch public company is worth close to $60B (Visa is worth $440B for comparison). Stripe and Marqeta are API-based payment service providers, which allow businesses to easily accept online payments and issue debit and credit cards for a variety of use cases. Adyen is a merchant account provider, which means it actually maintains the merchant account used to run a company’s business - this often comes with enormous scale benefits and reduced costs, which is why large customers like Nike have opted for Adyen. This merchant account clearing process can take quite a while which is why Stripe is focused on SMB’s - a business can sign up as a Stripe customer and almost immediately begin accepting online payments on the internet. Stripe and Marqeta’s API’s allow a seamless integration into payment checkout flows. On top of this basic but highly now simplified use case, Stripe and Marqeta (and Adyen) allow companies to issue debit and credit cards for all sorts of use cases. This is creating an absolute BOOM in fintech, as companies seek to try new and innovative ways of issuing credit/debit cards - such as expense management, banking-as-a-service, and buy-now-pay-later. Why is this now such a big thing when Stripe, Adyen, and Marqeta were all created before 2011? In 2016, Visa launched its first developer API’s which allowed companies like Stripe, Adyen, and Marqeta to become licensed Visa card issuers - now any merchant could issue their own branded Visa card. That is why Andreessen Horowitz’s fintech partner Angela Strange proclaimed: “Every company will be a fintech company.” (this is also clearly some VC marketing)! Mastercard followed suit in 2019, launching its open API called the Mastercard Innovation Engine. The big networks decided to support innovation - Visa is an investor in Stripe and Marqeta, AmEx is an investor in Stripe, and Mastercard is an investor in Marqeta. Surprisingly, no network providers are investors in Adyen. Fintech innovation has always seen that the upstarts re-write the incumbents (Visa and Mastercard are bigger than the banks with much better business models) - will the same happen here?

  3. Building a High Availability System. Do Mastercard and Visa have the highest availability needs of any system? Obviously, people are angry when Slack or Google Cloud goes down, but think about how many people are affected when Visa or Mastercard goes down? In 2018, a UK hardware failure prompted a five-hour outage at Visa: “Disgruntled customers at supermarkets, petrol stations and abroad vented their frustrations on social media when there was little information from the financial services firm. Bank transactions were also hit.” High availability is a measure of system uptime: “Availability is often expressed as a percentage indicating how much uptime is expected from a particular system or component in a given period of time, where a value of 100% would indicate that the system never fails. For instance, a system that guarantees 99% of availability in a period of one year can have up to 3.65 days of downtime (1%).” According to Statista, Visa handles ~185B transactions per year (a cool 6,000 per second), while UnionPay comes in second with 131B and Mastercard in third with 108B. For the last twelve months end June 30, 2020, Visa processed $8.7T in payments volume which means that the average transaction was ~$47. At 6,000 transactions per second, Visa loses $282,000 in payment volume every second it’s down. Mastercard and Visa have always been historically very cagey about disclosing data center operations (the only article I could find is from 2013) though they control their own operations much like other technology giants. “One of the keys to the [Visa] network's performance, Quinlan says, is capacity. And Visa has lots of it. Its two data centers--which are mirror images of each other and can operate interchangeably--are configured to process as many as 30,000 simultaneous transactions, or nearly three times as much as they've ever been asked to handle. Inside the pods, 376 servers, 277 switches, 85 routers, and 42 firewalls--all connected by 3,000 miles of cable--hum around the clock, enabling transactions around the globe in near real-time and keeping Visa's business running.” The data infrastructure challenges that payments systems are subjected to are massive and yet they all seem to perform very well. I’d love to learn more about how they do it!

Business Themes

interchange_fee.jpg
Interchange.png
  1. What is interchange and why does it exist? BigCommerce has a great simple definition for interchange: “Interchange fees are transaction fees that the merchant's bank account must pay whenever a customer uses a credit/debit card to make a purchase from their store. The fees are paid to the card-issuing bank to cover handling costs, fraud and bad debt costs and the risk involved in approving the payment.” What is crazy about interchange is that it is not the banks, but the networks (Mastercard, Visa, China UnionPay) that set interchange rates. On top of that, the networks set the rates but receive no revenue from interchange itself. As the book points out: “Since the card netork’s issuing customers are the recipients of interchange fees, the level of interchange that a network sets is an important element in the network’s competitive position. A higher level of interchange on one network’s card products naturally makes that network’s card products more attractive to card issuers.” The incentives here are wild - the card issuers (banks) want higher interchange because they receive the interchange from the merchant’s bank in a transaction, the card networks want more card issuing customers and offering higher interchange rates better positions them in competitive battles. The merchant is left worse off by higher interchange rates, as the merchant bank almost always passes this fee on to the merchant itself ($100 received via credit card turns out to only be $97 when it gets to their bank account because of fees). Visa and Mastercard have different interchange rates for every type of transaction and acceptance method - making it a complicated nightmare to actually understand their fees. The networks and their issuers may claim that increased interchange fees allow banks to invest more in fraud protection, risk management, and handling costs, but there is no way to verify this claim. This has caused a crazy war between merchants, the card networks, and the card issuers.

  2. Why is Jamie Dimon so pissed about fintechs? In a recent interview, Jamie Dimon, CEO of JP Morgan Chase, recently called fintechs “examples of unfair competition.” Dimon is angry about the famous (or infamous) Durbin Amendment, which was a last-minute addition included in the landmark Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010. The Durbin amendment attempted to cap the interchange amount that could be charged by banks and tier the interchange rates based on the assets of the bank. In theory, capping the rates would mean that merchants paid less in fees, and the merchant would pass these lower fees onto the consumer by giving them lower prices thus spurring demand. The tiering would mean banks with >$10B in assets under management would make less in interchange fees, leveling the playing field for smaller banks and credit unions. “The regulated [bank with >$10B in assets] debit fee is 0.05% + $0.21, while the unregulated is 1.60% + $0.05. Before the Durbin Amendment the fee was 1.190% + $0.10.” While this did lower debit card interchange, a few unintended consequences resulted: 1. Regulators expected that banks would make substantially less revenue, however, they failed to recognize that banks might increase other fees to offset this lost revenue stream: “Banks have cut back on offering rewards for their debit cards. Banks have also started charging more for their checking accounts or they require a larger monthly balance.” In addition, many smaller banks couldn’t recoup the lost revenue amount, leading to many bankruptcies and consolidation. 2. Because a flat rate fee was introduced regardless of transaction size, smaller merchants were charged more in interchange than the prior system (which was pro-rated based on $ amount). “One problem with the Durbin Amendment is that it didn’t take small transactions into account,” said Ellen Cunningham, processing expert at CardFellow.com. “On a small transaction, 22 cents is a bigger bite than on a larger transaction. Convenience stores, coffee shops and others with smaller sales benefited from the original system, with a lower per-transaction fee even if it came with a higher percentage.” These small retailers ended up raising prices in some instances to combat these additional fees - causing the law to have the opposite effect of lowering costs to consumers. Dimon is angry that this law has allowed fintech companies to start charging higher prices for debit card transactions. As shown above, smaller banks earn a substantial amount more in interchange fees. These smaller banks are moving quickly to partner with fintechs, which now power hundreds of millions of dollars in account balances and Dimon believes they are not spending enough attention on anti-money laundering and fraud practices. In addition, fintech’s are making money in suspect ways - Chime makes 21% of its revenue through high out-of-network ATM fees, and cash advance companies like Dave, Branch, and Earnin’ are offering what amount to pay-day loans to customers.

  3. Mastercard and Visa: A history of regulation. Visa and Mastercard have been the subject of many regulatory battles over the years. The US Justice Department announced in March that it would be investigating Visa over online debit-card practices. In 1996, Visa and Mastercard were sued by merchants and settled for $3B. In 1998, the Department of Justice won a case against Visa and Mastercard for not allowing issuing banks to work with other card networks like AmEx and Discover. In 2009, Mastercard and Visa were sued by the European Union and forced to reduce debit card swipe fees by 0.2%. In 2012, Mastercard and Visa were sued for price-fixing fees and were forced to pay $6.25B in a settlement. The networks have been sued by the US, Europe, Australia, New Zealand, ATM Operators, Intuit, Starbucks, Amazon, Walmart, and many more. Each time they have been forced to modify fees and practices to ensure competition. However, this has also re-inforced their dominance as the biggest payment networks which is why no competitors have been established since the creation of the networks in the 1970’s. Also, leave it to the banks to establish a revenue source that is so good that it is almost entirely undefeatable by legislation. When, if ever, will Visa and Mastercard not be dominant payments companies?

Dig Deeper

  • American Banker: Big banks, Big Tech face-off over swipe fees

  • Stripe Sessions 2019 | The future of payments

  • China's growth cements UnionPay as world's largest card scheme

  • THE DAY THE CREDIT CARD WAS BORN by Joe Nocera (Washington Post)

  • Mine Safety Disclosure’s 2019 Visa Investment Case

  • FineMeValue’s Payments Overview

tags: Visa, Mastercard, American Express, Discover, Bank of America, Stripe, Marqeta, Adyen, Apple, Open-loop, Closed-loop, Snowflake, AWS, Nike, BNPL, Andreessen Horowitz, Angela Strange, Slack, Google Cloud, UnionPay, BigCommerce, Jamie Dimon, Dodd-Frank, Durbin Amendment, JP Morgan Chase, Debit Cards, Credit Cards, Chime, Branch, Earnin', US Department of Justice, Intuit, Starbucks, Amazon, Walmart
categories: Non-Fiction
 

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