Profit Engine


Revenue, Cost, Profit, Sustainability


What must be clearly demonstrated for credibility is how the statement on the homepage is constructed:

USD 6,7+ million / 1000 micro / year profit


Revenue side

The foundation of the revenue is extreme scalability.

From a horizontal perspective, the system can target approximately 33 million micro-businesses in the EU.

From a vertical perspective, we have identified 12 revenue-generating points per client.


Out of these:

  • the first revenue source is based on measured, factual data
  • the second is based on market-based estimation from comparable solutions

At the same time, there is no exact data for additional effects such as:

  • the value of data asset growth
  • faster and more accurate lending
  • cross-selling revenues
  • reputational improvement
  • marketing efficiency

These represent further upside, but are not included in the core calculation.


Factual baseline and rule-of-thumb

At 1000 micro-business clients, assuming:

  • USD ~320,000 annual revenue per business

the core banking revenue is approximately:

→ USD ~ 2960 / client / year


This results in:

→ USD ~296,000 / year core banking revenue (1000 clients)


Our assumptions

If the client receives the system free from the bank, price sensitivity decreases, therefore higher banking fees are accepted.

Fee-based banking revenues represent approximately 64% of total banking revenue, while the remaining 36% is driven by BUBOR-related income. The 30% pricing uplift applies only to this 64% fee-based portion, as BUBOR-related income is yield-driven and not subject to pricing adjustments.

A 30% increase in banking fees results in:

→ USD ~568,000 additional annual revenue (per 1000 clients)


Marketplace revenues

Since the bank provides the sales channels (webshop, ordering applications, digital interfaces), it can charge commission on transactions generated through them.

This is the same model used by platforms such as:

Fizz, eMAG, Amazon, eBay, Foodora, Wolt.

These typically operate with 5–15% commission levels.


We estimate marketplace revenues based on the assumption that:

  • 10% of the client’s turnover flows through these channels
  • the bank charges a 10% commission

For a micro client with USD 320,000 annual revenue:

  • 10% = USD 32,000
  • 10% commission = USD 3,200

In a more conservative scenario:

→ USD 320,000 / client / year


At 1000 clients, this results in:
→ USD 3,200 million annual marketplace revenue


Conclusion of the profit calculation

  • USD 2,96 million core banking revenue
  • USD 0,568 million additional revenue from increased pricing
  • USD 3,2 million marketplace revenue

→ Total: ~ USD 6,7 billion / year / 1000 micro clients

This means that the statement on the homepage is achievable using only two revenue sources.


Cost structure

To evaluate profitability, cost must also be considered.

With Ordware, costs approach zero.


The cost structure is designed so that:

  • if the bank captures the value
  • the bank bears the operating cost

At the same time, due to the technology, these costs remain minimal.


Entry cost and business model

The model is:

B2B2B White-Label Core License + Royalty


With the license, the bank receives a system that is already:

  • developed
  • tested
  • proven

Therefore:

  • no development cost
  • no development time
  • minimal risk

The royalty applies to revenue streams that were previously inaccessible to the bank, such as marketplace commissions.


For example, when a customer purchases a product (e.g. food through the application), the bank earns a 3–10% commission, from which Ordware receives a share.


Operating cost

Due to the All-in-One-All-in architecture:

  • further development cost is minimal
  • customization cost is minimal
  • support requirement is negligible

Measured data shows:

  • ~9 minutes support / month / 10 clients

System usage:

  • • ~5–10 MB data / day / client

→ operating cost approaches zero


Profitability

As a result:
→ Revenue ≈ Profit


Sustainability

Sustainability is built into the model.

The client receives massive value, but cannot take the system with them.


Therefore:
→ long-term retention is ensured