The Googlisation of Payments; B2B fintech pricing: Pricing model definitions; Embedded fintech revenue model;

Sam Boboev

10 min readJun 28, 2023

In this edition:

1️⃣ The Googlisation of Payments

2️⃣ Uncovering the potential of embedded finance

3️⃣ X1, a credit card startup, has been acquired by Robinhood for $95M

4️⃣ Embedded Fintech Revenue Model

5️⃣ Why Payment Apps Are Targeting More Teens Now

6️⃣ B2B fintech pricing: Pricing model definitions

7️⃣ Three models for leveraging generative AI within financial services: Construct, Configure and Adopt

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The Googlisation of Payments

I have been a fan of serving ads through payment or fintech companies for a long time. You may ask why should one use payment companies to run ads? The answer would be they have got access to data and merchants and trust me they can do better targeting than major ads platforms.

Zilch the UK based BNPL did exactly the same with their Ad-Subsidised Payments Network (ASPN).

We all know how Google and Meta work. They provide free services to users and make money by selling ads. This allows them to offer high-quality and sustainable solutions for social media and search respectively.

But have you thought that a payments platform could be more attractive place for advertisers to invest their marketing budgets than Google or Meta. These two giants account for about half of all online ad spending, but paying is a more essential activity than searching or socializing. To buy something, you don’t need to use a search engine or a social media platform, but you do need to pay.

One of the signs of the rising dissatisfaction of advertisers with the dominant digital platforms where they allocate most of their budgets is the emergence of ‘retail media’. This term refers to advertising within or connected to a third-party retail ecosystem, usually by brands that sell products directly with retailers. Retailers have become a major player in the online advertising space, with Amazon leading the way. In Q3 2022, Amazon reported quarterly advertising revenues of more than $9.5 bn; less than five years ago, this segment was not even separately disclosed in the company’s financial statements.

How does Zilch Ad-Subsidised Payments Network work and what it promises?

Zilch is a payment solution that customers can use anytime and anywhere they shop — online or offline. It has enormous earning potential from ads, as it can match the right customers with the right brands or products at the right moment, and not only track the sale conversion, but enable it, by giving them the means to pay.

Ad-Subsidised Payments Network is based on unique position that connects millions of Zilch customers who have spending power and use its product 800–100 a years with thousands of competing retailers who can offer tailored deals based on rich first-party data.

According to Zilch average e-commerce conversion rates are 1–2%. But as of December 2022, Zilch’s top 10 retailers convert on average 55.4%, with some as high as 72%. This means it’s converting around 30–70x more than the industry standard of search and social.

That’s an impressive results and an interesting business concept.

What are your thoughts on using fintech companies as ad networks?

Reference Zilch

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Uncovering the potential of embedded finance

EmFi is essentially the placement of a financial product in a nonfinancial customer experience, journey, or platform. This concept is transforming the way customers and businesses approach financial services. The following EmFi components have already gained traction:

- Embedded banking — the integration of banking services into nonfinancial products and services. This integration can take various forms, such as card issuance or “know your customer” (KYC) verification integrated into a mobile app or online platform.

- Embedded payments — the integration of payment services into nonfinancial products and services. Enabling mobile payments within a ride-sharing app or allowing customers to pay for goods and services through a social media platform are two examples.

- Embedded lending — the integration of lending services into nonfinancial products and services. Like embedded payments, this service can take different forms, such as financing options for products or services, or loans within a bundled package. For example, an automobile dealership may offer financing options for customers looking to purchase a car by including lending services in the dealership’s overall offerings.

- Embedded wealth — the integration of wealth management services into nonfinancial products and services. This can be accomplished by providing access to investment options, retirement savings plans, and other financial products embedded as part of a broader offering. Wealth management firms aim to offer customers added convenience and value while expanding their revenue streams and reaching new markets.

- Embedded insurance — the integration of insurance services within nonfinancial products and services. Adding insurance coverage to a product or service or offering insurance products as an additional benefit to customers are two of the many possibilities.

- Embedded anything — the integration of financial tools for taxes, accounting, and invoicing into nonfinancial products and services. Examples include embedding taxpreparation services into accounting software or integrating invoicing services into an e-commerce platform.

Download Report

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X1, a credit card startup, has been acquired by Robinhood for $95M

X1, which offers an income-based credit card with rewards, raised a total of $62 million in venture-backed funding from investors like Soma Capital, FPV, Craft Ventures and Spark Capital since its 2020 inception. The company announced its most recent raise of $15 million in December, when it also touted a 50% boost in its valuation.

On the one hand, while X1’s valuation is not known, it looks like Robinhood is getting a good deal with $95 million. If you take a look at recent raises by other credit card companies, you might say that X1 raising $62 million should yield a high valuation in the hundreds of millions. So, the purchase price may reflect the dip in fintech valuations we’ve seen in the past six months.

Source TechCrunch

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Embedded Fintech Revenue Model

In practice, we don’t anticipate that financial institutions will price (and charge for) each value-added service individually, instead opting to create bundled packages or pricing tiers like many fintechs do. To estimate the revenue potential from an embedded fintech strategy, Cornerstone Advisors built a model that assumes:

• Financial institutions will create two subscription tiers: Tier 1 with six to eight bundled fintech services, and Tier 2 with three to four services, priced at $10 and $5 per month, respectively. The baseline checking account growth rate will increase based on the improved attractiveness of the account offering.

• A percentage of accounts will be exempt from a monthly fee based on the scope of their relationship (i.e., number of accounts, balances, spending levels). This percentage will grow over time, which depresses the subscription revenue but produces revenue for other lines of business in the institution. These indirect revenue benefits are not captured in the model.

• Financial institutions will share 50% of the revenue with fintech partners and 10% of the subscription total with a partner that manages the program.

Based on the assumptions above, a financial institution with a starting base of 250,000 checking accounts could generate more than $1.8 million in incremental revenue for a gross profit of almost $750,000 in the first year. With embedded fintech adoption growing to 50% of checking accounts by the fifth year, total subscription revenue will grow to more than $15 million in that year, with a net revenue of more than $6 million.

Source FintechOS

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Why Payment Apps Are Targeting More Teens Now

Teens are getting a head start in understanding personal finance through apps designed to help them manage money, with parental supervision.

Source The Wall Street Journal

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B2B fintech pricing: Pricing model definitions

- License- and fee-based: Often thought of as the original SaaS pricing model, this bucket encompasses everything from all-you-can-eat, to various flavors of per-seat or user pricing which generally tie to the size and complexity of the organization.

Most popular in: Workflow tools, application layer, vertical SaaS, and/or platform components of usage-based products.

Pros: Simple, highly predictable, high gross margin

Cons: Friction while trying to drive wider adoption within an organization (need to sell more licenses). In the case of all-you-can-eat, there can be difficulty upselling as companies can share a login

- Usage-based: Common amongst API-driven companies and other forms of enabling infrastructure, usage-based pricing involves dollar-based fees for a given set of billable events, such as the calling of an API, the verification of an identity, or the processing of a loan application. Another popular pricing driver in usage-based models can be the number of end customers to which the solution is deployed.

Most popular in: B2B infrastructure (e.g., account aggregation, identity verification)

Pros: Aligns cost with value, can result in frictionless rapid growth, easier to identify trends in usage by customer and potential churn

Cons: Spiky, subject to seasonality, operationally burdensome (e.g., reconciling billing), less predictability for you. Customers often don’t know how much they’ve used and the variability in their bill causes frustration

- Take-rate: Common amongst marketplaces and payments companies, take-rate pricing typically monetizes via a percentage of GMV being processed through the platform.

Most popular in: Marketplaces, B2B infrastructure (e.g. payment processing)

Pros: Typically maximizes profit potential when serving large customers / ticket sizes, tied to the customer’s revenue vs. being a cost center

Cons: Subscale players have challenged unit economics

- Per-employee, per-month: Common amongst HR, payroll, and benefits companies, PEPM typically charges a flat fee per either an employee or user of a given product or service.

Three models for leveraging generative AI within financial services: Construct, Configure and Adopt

- Construct (”Create from Scratch”): Creating your own LLM trained on a specific set of data, typically leveraging your own proprietary datasets.

- Configure (”Assemble from the Kit”): Leveraging the foundation of ready-made LLMs (closed-source or open-source), and then customizing them for your specific use case, such as through embeddings, prompt engineering, fine-tuning, etc. Organizations may choose to customize directly, or through a flourishing layer of “tooling” apps (e.g., Contextual AI*).

- Adopt (”Out of the Box”): Purchasing in full a generative AI application for a specific use case within the organization. The application is typically built on top of a closed- or open-source LLM, and then wraps workflow or additional AI algorithms around the generative AI to deliver a complete solution for the given use case, e.g., conversational chatbots for customer service requests. The adopting company may choose ‘flavors’ of the solution, but there’s little (real) customization.

Relating this back to the factors that direct this choice of investment:

- Goal — How does this use case fit into your company strategy? If the goal is building a proprietary product, then perhaps you lean toward construct. Or, if the goal is strictly use case performance, even if you have proprietary data, then you’ll choose to use one of the existing LLMs that has vast amounts of data in the adopt or configure model.

- Budget — How much do you have to spend on developing a proprietary instance of generative AI?

- Ingredients available — Do you already have your data assembled, structured and available?

- Time — Do you need a solution today, or can you afford the time to build for tomorrow?

- Food sensitivity/Allergy — How sensitive is your data to protect, and how important is data privacy to your organization and your regulatory context?

- Skills — Do you have the internal talent required to build? If not, can you find them? Can you recruit them? Can you afford them?

Source Bain Capital Ventures