Note: Not Financial Advice

Introduction:

MA is one of the duopoly in the card network business. The card network business is a unique model that heavily rewards first mover advantage, with large barriers to entry due to the large fixed cost associated with setting up POS, achieving large merchant acceptance locations, and gaining the trust of major financial institutions. The card network business has large potential but also large hurdles to overcome, with regulators and competitors all eyeing a piece of MA's business.

Market:

APAC and some EMEA have one of the lowest credit card penetration rates as their society is “less developed” due to a lack of the relevant and appropriate infrastructure to support cashless payments (SOURCE).

I believe that most of the developing world would follow a similar trend as China in terms of how payment has progressed. In the early 2010s, China was mostly a cash-based society (SOURCE) coincidentally then, smartphone penetration in the market was ~75%. Both Alipay and WeChat pay with a large user base took advantage of that and introduced mobile payments. Part of the growth equation was also due to mass merchant adoption, as merchants only needed QR codes without the need for costly POS systems that traditional credit cards require.

A potential competitor to credit cards is P2P payments like Venmo where payments are made directly from 1 party to the other through mobile wallets (SOURCE). However, the largest flaw with P2P payment is that since transactions are instantaneous the onus is on the consumer to verify the legitimacy of a transaction before proceeding. P2P payments don't have the same extensive fraud protection that traditional credit card payments offer.

In India, a credit card is still seen as a “premium” product with credit cards only having a penetration rate of 5.5% (SOURCE). However, getting in the way of mass credit card adoption is the competing United Payment Interface(UPI). UPIs are smartphone applications that allow for peer-to-peer RTP between merchants and consumers. UPI already has a strong foothold in India at 50 million merchant acceptance locations. The future going forward will be that UPI will be able to be linked to credit cards. “In terms of data, around INR 39 bn count of UPI transactions were recorded in 2021, compared to INR 211 Mn credit cards POS transactions” (SOURCE).

Mobile payments could lead to the acceleration of the growth of transactions using credit/debit cards. However, mobile payments do take a cut out of the fees so it could cut into MA’s topline. This would be an even more prevalent issue in the future when these mobile payment providers have an established reward system rivaling traditional credit card companies.

Over the upcoming decade, ASEAN is expected to be the fastest-growing emerging market (SOURCE) fueled by robust global Free Trade Agreements (FTAs), strong recovery of the tourism sector in the region, and the rebound of domestic consumption of their larger trade partners e.g. China and India which drives ASEAN’s exports, this effect is further compounded as certain of their trade partners have an aging population with large disposable income. The kinds of exports that ASEAN is expected to contribute to will be in the form of raw material, and value-added exports e.g. semiconductors. ASEAN is expected to grow at a Y/Y CAGR rate of 10.00% over the next 13 years (SOURCE).

Revenue:

Mastercard breaks down its revenue into “payment network” and “value-added services and solutions”.

Payment Network

Payment network is when MA charges a % fee based on Gross Dollar Volume (GDV) of all mastercard-related transactions, GDV is calculated through purchases made using an MA-branded card.

MA is building out its service to roll out in China, so far, it has partnered with ICBC and Bank of Communications, but they have a long road ahead to establish its presence in China. Initially, to pay using Alipay or WeChat in China, you have to open a Chinese bank account. However, Alipay and WeChat have begun allowing consumers to link the app to their foreign credit card. China is the perfect ground for MA to establish itself, given that the value of mobile transactions in China in 2022 is 500 Trillion Yuan (SOURCE).

I believe that payment network should be broken down into APMEA and Non-APMEA, APMEA represents a large growth opportunity as the APMEA region is beginning to explore mobile payments and global e-commerce. Whereas the Non-APMEA region represents a mature region that has little wiggle room left to grow.

APMEA

When forecasting the number of transactions, I forecasted it with a backloaded growth rate as I believe that GDV for APMEA will grow heavily through a larger number of transactions as more and more people in the APMEA region are wealthy enough to be offered the luxury of a credit card. On top of that, the growing smartphone penetration rate and growth in mobile wallets all help to boost the total number of transactions.

When forecasting the GDV/Transactions, I believe that historically GDV/Transaction had been declining for APMEA due to the poor macro environment from COVID-19 affecting disposable income of the APMEA region which leads to unwillingness to make purchases. However, I assume that it takes another 1 year of forecast for the lingering effects of COVID-19 to dissipate and for consumers to regain the confidence to make bigger purchases. On top of that, I believe that in the future GDV/Transaction in the APMEA region will grow in part due to the rising disposable income of these countries attributed to their strong forecasted GDP growth, and as consumers get used to the convenience of MA and trust the reliability & security of their payment network, they will utilize MA for a greater number of transactions leading to higher GDV per transaction.

When forecasting %GDV earned, opting for less granularity I forecasted it to taper towards the perpetual inflation rate.

Non-APMEA
When forecasting the number of transactions, I assumed that the Non-APMEA regions are sufficiently matured so the number of transactions is unlikely to have any large spikes. So, I forecasted it as a % of historic averages.
When forecasting the GDV/Transaction, I assumed that the Non-APMEA regions are sufficiently matured so there are unlikely to be any large spikes. So, I forecasted it as a % of historic averages.
When forecasting %GDV earned, opting for less granularity I forecasted it as a % of perpetual inflation rate. This is especially true given how there is growing legislation against MA and VISA in the Western world for holding a duopoly. So, I assumed that MA or VISA would be unlikely to raise %GDV earned through higher merchant discount rates.

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Value-added services and solutions

Value-added services and solutions refer to MA’s other services e.g. Cyber and Intelligence solutions, open banking solutions, etc.
MA believes that value-added services and solutions help to drive payment network. “And if you look at some of these big wins…all have a significant contribution of services…oftentimes, they are one of the reasons that we win those deals” – 2023 Q4 Earnings conference. A few examples of the services MA provides are:

1) Data, because MA handles a large number of transactions they accumulate a lot of consumer data. MA acquired a personalization company to help merchants analyze data to make personalized recommendations.

2) Biometric, MA is looking for new ways to make payment even more seamless through using biometric data.

3) Cyber, Click-To-Pay, MA allows for your credit card details to be stored safely so that for subsequent transactions you can just conveniently bring up your details previously entered.

Given that the success of Value-added services and solutions is hinged on the success of MA’s payment network, I forecasted it as a % of Payment Network, forecasting it as a % of historic averages.

Cost:

MA has 3 different costs “COGS”, “Marketing”, and “Others”. COGS refers to G&A as MA relies on its workforce to produce its G&S.

When forecasting COGS, looking at the historic numbers of employees (SOURCE). I forecasted it as a % of historic averages.

When forecasting cost per employee, I assumed that historic trends continue for 5 years before wages grow in line with the perpetual inflation rate.

When forecasting Marketing and Others, opting for less granularity I forecasted it as a % of historic averages.

WACC:

RFR (1M Avg) = 4.23%

Beta (SOURCE) = 1.07

Stable Market ERP (SOURCE) = 4.60%

COE = 9.15%

MA bond is rated “A+” (SOURCE)

COD (1M Avg) = 5.38%

Marginal Tax Rate = 21.00%

AT-COD = 4.25%

Stock Price (5D Avg) = $471.19

Shares O/S = 932.89M

Market Value of Equity = 439569.15M

FY23 Interest Expense = 575.00M

Average maturity of debt = 9 years

Market Value of Debt = 15138.04M

%Debt = 3.34%

%Equity = 96.66%

%WACC = 8.99%

Conclusion:

Ultimately, in my base case, I value MA at $455.14 per share. I believe that the markets have correctly priced MA, seeing the value that MA could potentially bring to the consumers. News of the Credit Card Competition act has not eroded investor's confidence in the stock and what it brings. However, I believe that going forward MA has a strong potential to grow exponentially but also the potential to see their growth rate taper aggressively. This is hinged on how well MA can execute its growth strategy in critical areas like China and APMEA.

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