Transparency in card transactions: how to improve it and how much profit it can preserve

Kirill Lisitsyn, Co-founder and CEO of Torus, explains the importance of transparency in card transactions, elaborating on how this can be improved to prevent profit losses.

As the volume of card payments continues to grow, the need to calculate the cost base of these transactions is becoming increasingly critical. Accordingly, it is extremely important for all market participants to understand which parameters influence the formation of this cost.

In card transactions, there are two main cost blocks: (1) interchange and (2) scheme fees. Historically, in Europe the regulatory focus was on interchange, which began to be regulated through the IFR (Interchange Fee Regulation), while scheme fees were somewhat overlooked. 

In recent years, scheme fees have also come under increasing regulatory attention: pressure is growing both from acquirers and, through them, from merchants.

What was interchange++ originally intended to be, and why doesn’t it fully work as planned?

Originally, interchange++ (IC++) was designed both as a pricing model and, as a secondary effect, as a way to increase transparency. This is because it breaks the total fee into three main components: the interbank fee (interchange fee) redistributed by the payment scheme in favour of the issuing bank, the payment scheme fee (scheme fee, for example Visa or Mastercard), and the acquirer’s markup (processor markup).

However, not all market participants have access to how scheme fees are actually calculated, and as a result, these players (for example, PSPs) don’t always trust how fees are calculated or allocated by acquirers. Moreover, even those who do have access to the source scheme information/fee guides (such as acquirers) don’t always perform detailed calculations due to the lack of specialised experts in card transaction analytics and dedicated teams that continuously track changes in scheme fees and incorporate them into pricing models.

As a result, increasing complexity – including in pricing – does not always lead to greater transparency. In some cases, making the system more complex leads to a higher number of errors within it.

Who faces greater complexity: non-direct principals (PSPs and merchants) versus direct principals (acquirers and issuers)

For the market, scheme fees remain a significantly more complex construct than interchange. Especially in Europe, where interchange rates have become transparent and standardised, it is precisely the closed and less visible nature of scheme fees that increasingly creates opacity and a blind spot in the structure of card transaction costs.

On the PSP and merchant side, transaction analysis is heavily constrained because they do not have access to all card scheme rules, as they are not direct principals. The billing logic of partners is not visible to them, there is no access to card scheme invoices for reconciliation, and as a result, not all parameters can be calculated independently.

This leads to situations where acquirers don’t always allocate fees to PSPs and merchants with full accuracy, as this requires substantial operational and methodological effort, and there are relatively few specialists in the market with deep expertise in scheme fee analytics. Even when questions arise, it’s not always possible to clearly explain why fees have been allocated in a particular way, which regularly triggers concerns from these market segments.

At the same time, acquirers themselves often face situations where not all costs are fully allocated, causing them to suffer transaction-level losses within their own portfolios.

The complexity of scheme fee analysis: changes and legacy details

The core challenge in calculating transaction-level fees lies in the fact that they consist of a set of heterogeneous charges (typically ranging from three to ten), unlike interchange fees – where a single fee with a clearly defined rate applies to a given transaction. The composition, frequency, type, and amount of scheme fees depend on a large number of factors and transaction attributes.

In addition, some fees are not transaction-based at all, which further complicates accurate allocation. The card scheme rules and pricing schedules themselves span hundreds of pages and are extremely difficult to interpret and apply in practice without specialised expertise. These factors make modelling scheme fees highly complex not only for PSPs and merchants, but also for acquirers and other direct principals themselves.

Analytics solutions for card transactions: build in-house or rely on external partners

Detailed analysis of card transaction profitability can be implemented either internally or through external solutions – but both approaches come with trade-offs.

In-house development provides full control over data and analytical logic, but typically requires (1) rare expert knowledge, (2) long development cycles, and (3) continuous effort to keep up with rapidly evolving card scheme rules.

External analytics platforms, including solutions like ours, allow financial institutions to move faster, but often require a certain level of trust in third-party models and data handling – something not all organisations are comfortable with.

A third option, still used by many market participants, is to analyse profitability at the portfolio level by manually collecting and consolidating data in Excel. This approach can provide a high-level view, but preserving a meaningful share of profit is only possible when transactions are analysed individually, down to each one – something that is not feasible in a manual setup.

A few practical examples

Below are several cases from our work in the past 12 months where detailed analytics helped uncover previously hidden sources of profit leakage:

1. A pan-European ecommerce acquirer set out to increase revenue by improving transparency for merchants. By predicting transaction fees at the daily settlement level, modelling the allocation of fixed scheme fees, and regularly updating pricing logic in line with Visa and Mastercard announcements, the acquirer was able to correct billing inaccuracies and offer clearer pricing explanations. As a result, the company achieved a 13% revenue uplift and strengthened its competitive position with merchants.
2. In another case, a payment service provider decided to review how its acquiring bank priced interchange++, scheme fees, and markup. Using the PSP’s transactional data, fees were recalculated independently and compared with the actual charges applied by the acquirer. The analysis showed that the PSP’s transaction costs should have been around 15% lower than billed, providing a clearer understanding of market benchmarks and enabling a more informed, fact-based dialogue with the acquiring bank.

Key takeaways

1. Transparency in card transactions is no longer about just compliance – it is a tool for protecting margins.
2. The main risk area today is not interchange, but the complex and less predictable structure of scheme fees, driven by multiple transaction attributes and frequent rule changes.
3. Portfolio-level analytics is no longer sufficient: only transaction-level analysis enables accurate cost allocation and can deliver double-digit profitability improvements in today’s environment of margin erosion.
   
   

About the author

Kirill Lisitsyn is the go-to expert for card issuers and merchant acquirers aiming to enhance their card payments profitability. With over 15 years of consulting experience with industry leaders like Accenture and Mastercard, he co-founded Torus to revolutionise how payment mid-market players access data-driven insights typically reserved for the high street players. At Torus, the mission is clear: to enhance transparency in card payments and empower businesses to boost their profits by up to 50% through improved efficiency in managing scheme fees by Visa and Mastercard. The SaaS intelligence platform enables card issuers and merchant acquirers to optimise fees and improve transactional earnings through in-depth profitability analysis and strategic product pricing.

Under Kirill’s leadership, the company won MPE Startup Innovation of the Year 2024 and FF Awards 2025 (Data Insights), became a finalist of the Banking Tech Awards and Europe FinTech Awards 2025, and was ranked among the Top-5 fastest-growing Baltic fintechs by Sifted 2025.

About Torus

Torus is the award-winning SaaS intelligence platform for banks and fintechs to enhance their profits on card transactions by up to 50%. We enable card issuers and merchant acquirers to optimise card scheme fees and to improve their transactional earnings through card-/merchant-level profitability analysis and product pricing optimisation.