Payments Optimization As A Service

How Payment Service Providers can reverse the Commoditization of Payments.

For the last five years FinTech has been extremely interesting, and I would say the most dynamic industry to be in. Were the hundred year old financial institutions had a stake in each part of our financial products, from checking accounts to credit cards to mortgages and even insurance, now the un-bundeling of banks has lead us to different categories of services within the FinTech space.

Lending has created companies like LendingClub, Kabbage and Affirm, Retail Investments has given us RobinHood, Wealthfront and Kapitall and Remittance has been changed by the likes of Transferwise, Ebury and WorldRemit.

But no other industry has seen the impact of new companies as much as the Payments industry. With companies like Stripe, Adyen,, Square, iZettle, Venmo, Dwolla, changing the way we pay online and offline, as well as send money to friends and family.

The Commoditization Trap

However as most of these Payments companies have been build on the infrastructure of card schemes like Mastercard, Visa and American Express, industry professionals know that the commoditization trap is right around the corner.

Once seen as a high-value solution, Payment Service Providers are now becoming commoditized because companies like PayPal and Stripe have changed the decision-making process for selecting a PSP from a business decision to a developer decision. Where in the past a thorough analysis of needs would be matched with one or multiple providers, a developers only criteria is the lines of code necessary to implement it into the application.

As the functionality of PSP’s have become pretty much the same, the decision comes down to the lowest common denominator — price. Instead of taking into consideration other financial calculations like return on investment, net profit impact, effect on key metrics, PSP’s are starting to compete with each other to offer merchants the lowest price possible.

A Race To Zero or Not?

With PSP’s being commoditized and companies competing on price, we will see more of the large incumbents like Ingenico, First Data and Vantiv, continue their acquisition spree (Bambora, CardConnect, WorldPay) to ensure that the economies of scale result in actual profits.

But as with every industry I believe that the biggest opportunity is still ahead of us. Instead of worrying about the commoditization of Payments, I spend most of my days thinking, strategizing and planning for the Optimization of the Payments Industry.


With optimization, I do not mean the strategic optimization to squeeze out every possible cent out of the workforce, but rather the mathematical perspective of optimization.

In this case I would refer to the PSP a an input system and the performance, pricing and functionality as the outputs that I would want to maximize.

If you are familiar with the Payments Industry and especially the Four Party Model, you might be aware that the different systems that a transaction goes through is extremely fragmented. Systems included in a transactions range from the Gateway, the Two-Step Verification, Fraud Detection System, Card Processor, Card Scheme Switching Systems, Issuer Processing Systems and Integrations into Financial and Fraud Systems.

As a PSP processes transactions and analyses the results of individual and aggregated transactions, patterns can emerge. These types of patterns can lead to configuration parameters to the system, which can impact the result of the output of the system.

Payments Optimization as a Service

Where companies like Google and Amazon have learned how to take the inputs that go into their individual systems and optimize the output, I believe that PSPs need to do the exact same thing if they want to create a sustainable business model for the future. One that does not rely on the ability to process transactions, but rather on the value-added services that it can provide.

I believe that the great opportunity within the Payments industry lies in the in-efficiencies that have been created by having a local issuing and acquiring entities, and either creating new payment methods or finding data-driven solutions to reduce those in-efficiencies.

Currently, Acquirers (Merchant Banks) have to apply for a membership to the global card schemes on a country/regional level, but are required to accept transactions from cards issued all around the world.

Like Acquirers, Issuers apply for country/regional level membership to be able to issue cards on a country level. Depending on the country, the maturity of card processing, and the spending habits of the consumers, each issuer has to put systems in place to deal with risk for fraud and delinquent card holders.

For example, the U.S. market is the oldest card issuing and accepting country in the world, which has led to a wide acceptance of credit cards, but at the same time issuers also deal with the highest level of card fraud globally.

Uniqueness of PSPs

So as each PSP develops their own unique data set over time, because of the merchants they process for, the region they operate in and the functionalities they support. Each PSP has the ability to use Data Science to develop their own unique set of algorithms to optimize their merchants transactions and provide value-added services like AI Fraud Detection, Authorization Rates Optimization and Interchange++ Optimization.

For example; AI Fraud Detection systems can use well known algorithms for detecting fraud, but by relying on smart Data Scientists to play around with the configuration parameters, each PSP will still be able to optimize Fraud for their individual merchants.

Authorization Rates, which are impacted by reputation, data quality or regionality, can be improved using Data Mining techniques to determine what the underlying cause of underperformance and using rule-based logic to improve the next input into the system to optimize the end result.

As Interchange++ is gaining traction especially under large merchants, the financial impact it can have the total cost of card processing, has many wondering what can be done. Regionality, Speed and Data Quality are all components in the final applied Interchange and Scheme Fees. By Data Mining results, the Optimal Route for each Transaction can lead to an Optimization in Pricing.

Value-added services

Optimizing to reduce fraud, improve authorization rates or reduce pricing are just a few examples of how Optimization As A Service will change the way the Payments Industry will interact with Merchants. By developing value-added services and showing merchants how those services impact their profit’s, PSPs will start to move away from commoditization and be able to truly differentiate themselves from other PSPs.

Thanks for reading 😉 , if you enjoyed it, hit the applause button below, it would mean a lot to me and it would help others to see the story. Let me know what you think by reaching out on Twitter or Linkedin. Or follow me to read my weekly posts on Data Science, Payments and Product Management.

Recent Posts