Measuring Wise’s Moat

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The last post, Ratio Obscura, prompted some follow up questions on the Robustness Ratio and how to apply it.

It is, fortunately or unfortunately, not a ratio that can be calculated after a quick glance at an income statement. This may be part of its value, pulling what is inherently qualitative into a quantitative form but nevertheless it is something where examples tend to be more useful than a definition.  

So, what follows is the process and logic behind calculating the Robustness Ratio of what I believe to be one of the “moatier” businesses out there right now, Wise.

Company Overview

Wise (ticker WIZEY in the US) provides cross-border money transfer services for personal and business customers in the UK, EU, Asia-Pacific, North America and a few more international markets. The company’s offerings include Wise Account for individuals to move and manage money across borders; Wise Business for international business needs; and Wise Platform that allows businesses and banks to offer their own customers international transfers through a white label solution.  

Note, as a UK listed company, the bulk of the financial metrics will be in British Pounds.

Founded in 2010 it has grown to roughly 6M users and is on track to process nearly £100B per annum. They are currently in about 80 countries which support 2.5K currency exchange routes.

The overall market consists of roughly $100T of cross-border transfers per year which has been growing at roughly a 5% annualized rate. If subtracting out the governmental and large business transfers, that total is about $11T made up of $2T and $9T for personal and small business respectively.

Wise currently makes up less than 4.0% of just that personal amount.

On an operational front, Wise charges roughly 0.73% on transfers vs. the banks’ fee of 6.0%-7.0% and remittance services such as Western Union and Money Gram at about 5.0%.

50% of all their volume is processed instantly, and 90% occurs within 24 hours compared to the banks’ multi-day process. Additionally, 80% of all new user onboarding is handled within one hour.

Both in cost and operational metrics, they are beyond their legacy competition by a country mile.

How do they accomplish this?

The incumbent system, SWIFT, requires banks to line up intermediaries creating a chain that ultimately routes your transfer to the end account. The further the degree of separation, the more complex the line of handoffs. This must occur for a $50 transfer, or a $50M. It is static complexity, but in the wrong direction.

Wise, on the other hand, holds accounts in the jurisdictions they operate within. Rather than actually transferring the funds, what occurs is a rebalance of the ledger that accounts for all their funds in total. They can rebalance after the fact, and they are actually managing liquidity rather than transferring funds. Anyone who has read up on the Lightning Network will recognize this format.

As they scale into a market they continually absorb the links in the chain to make themselves integrated for that given market. For instance, after ten years in business, they are now completely vertically integrated in the UK market relying on no other parties. In this way they drive unit economics beyond their core feature.  

While their business model could constitute its own deep dive a high level understanding is all that is needed for this write up since it is about the Robustness Ratio.  

As a refresher, the Robustness Ratio is a measure of how the value of an enterprise is being split amongst those parties that interact with it. That is, what is the ratio of value provided to the Customer, plus the value provided to the Employees, over the value provided to the Share Holders.

(Value to Customer + Value to Employees) / (Value to Shareholders)

If the ratio is below one, the shareholders are taking more out of the business than it is giving to the other parties. While different for each business, a good rule of thumb is that the greater the amount of value a company provides to its Customers and Employees in relation to its Shareholders, the more resilient that business is to competition and other growth headwinds.

 It is a measure of how big a company’s moat might be.

Calculating the Robustness Ratio

On the Customer front, Wise prides itself on pushing fees as low as they possibly can, and they have managed to build a platform that would be very hard for incumbent organizations to adjust to.

The current landscape of cross border payments is as follows:

• Banks at roughly 67% of volume

• Remittance processors such as Western Union and MoneyGram at 10%-20% of volume

• The rest is made up of companies such as Wise

The fees charged by the banks and remittance processors are roughly 6.5% and 5.0% respectively. To arrive at a single fee to compare Wise to we can assume a weighted average of the alternatives, which is 6.32% compared to Wise’s fee of 0.73%.

So, said another way, every pound that a customer spends at Wise would’ve been £8.66 spent elsewhere. If we were to apply that to their average customer that transfers roughly £20k per year on their platform, the savings are £1,134 annually (£1,264 vs. £146).

It is also worth noting that the fees charged by banks were closer to 9.0% in 2008/2009, so it would seem alternatives are creating very real pressure as time goes on.

If we were to apply this to the company level financials, the numbers would look as follows:

This is a massive delta in savings by the Wise customer versus incumbent alternatives.

For an indicator of how defensible this might be, beyond customer savings, let’s consider Western Union as a proxy for the remittance landscape which carries slightly lower fees than the banking alternative.

Running at about a 5.0% take rate, Western Union makes $50 for every $1,000 it transfers. This translates to about $11.95 on their EBITDA line.

Wise, on the other hand, only takes about $7.30 on that same $1,000 which it converts to about $1 in EBITDA.

If Western Union were to try and drop their rate below 4%, they would make nearly nothing at the EBITDA line (pending no other operational cuts) only to arrive at a fee that is still 5.5x higher than Wise.

On the employee front, it is a bit harder to arrive at a highly accurate assumption of value received. This is not just a consideration of how much employees are paid, but rather how much they are paid relative to alternatives. That is their value received.

Normally, comparing the average salary to that of their competitors would be the first step. In a company like a retailer this is pretty straight forward but in the case of Wise they do not look anything like their banking nor their remittance competition. For instance, Western Union relies on an agent network for their 20K currency routes.

They consider themselves a fintech company, but surgical precision is not required here and given the massive amount of savings Wise provides their customers (which will boost their Robustness Ratio), I am inclined to get conservative on my approach to Employee Value.

A review of employee surveys shows that roughly 46% feel they are not adequately compensated for their role. This unfortunately says nothing of whether this is skewed towards highly paid or lower compensated employees. So, we will assume it is equally weighted across the Company. As it almost certainly skews to lower compensation package employees, this is a first layer of conservatism.

We’ll assume that these employees feel they are under compensated to the tune of 35%. Nothing scientific in that but it is higher than the typical raise one gets for jumping ship to a competitor. So, a second layer of conservatism.  

If 46% feel they are under compensated by 35%, and the rest feel adequately compensated, it would give us a blended rate of £0.86 vs the £1.00 they should be paying.

Applying this to the Company’s financials and we’d get:

For those calling out using 100% of the SG&A expense, this is going to be the third layer of conservatism as it overstates a negative in this case. Obviously not every pound spent in this category goes to salaries, but with 2/3rds of new clients coming from referrals, it is not that obscene to assume it is 100% as they run the enterprise very efficiently.

It could very well be that this approach is incorrect, and there may actually be a positive value for the employees. They are a very decentralized company that provides a lot of flexibility in how their employees can chose to live and work. But rather than call up management to get more details on this, if the ratio still lands at an impressive level despite hamstringing this component, then I will feel that much more comfortable with the outcome.

On the part of shareholders, this is reasonably straight forward. We will use the Owner Earnings approach to approximate ownership returns.

At the company financials level, it would look like this:

 

Brining it together, now that we have the three key components we can compute the Robustness Ratio.

For reference, one of the great “moaty” businesses out there, Costco, was about 5.5x before the market started recognizing its superiority.

An average Robustness Ratio of 1.91x for the last three years is very good. Certainly well above average. But, what is notable about Wise’s particular case is just how large the value add is to the Customer. The massive amount of value provided to customers, and the pain it would cause the competition to drop their rates to a level that still would’ve be in the same zip code as Wise, is staggering.

As I have stated in the past, New West is not in the business of providing analyst reports, price targets, macro forecasts, etc. But, this is a very compelling business model.

A risks analysis would be the next step, but that would constitute its own post. Hopefully the logic presented here helps to paint a picture of how to calculate the Robustness Ratio.