Goldman Sachs faces rocky exit from Apple credit card partnership; Open Finance — the Gateway to an Open Data World; Preparing for PSD3;
In this edition:
1️⃣ Goldman Sachs faces rocky exit from Apple credit card partnership
2️⃣ Revolut suspends crypto buying for UK business customers
3️⃣ Apple sued with Visa, Mastercard in card-fee antitrust case
4️⃣ Four Visions For The Future Of Digital Money
5️⃣ Preparing for PSD3
6️⃣ Open Finance — the Gateway to an Open Data World
7️⃣ Capturing the full value of generative AI in banking
News
Goldman Sachs faces rocky exit from Apple credit card partnership
Four years after Goldman Sachs introduced a credit card with Apple, the Wall Street giant faces a costly exit from a partnership that is seen by other lenders as too risky and unprofitable.
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Revolut suspends crypto buying for UK business customers
Revolut has suspended some crypto services for business users until it gets up to speed with new regulations on financial promotions.
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Apple sued with Visa, Mastercard in card-fee antitrust case
Apple, Visa and Mastercard have been hit with a new proposed class action that accuses them of conspiring to thwart competition for point-of-sale payment card network services, causing merchants to pay artificially higher fees for credit and debit transactions.
Insights
Four Visions For The Future Of Digital Money
✅ Traditional Finance Successfully Evolves
This paradigm represents an evolution of the existing system, not a revolution, as banks and other incumbent financial institutions continue to dominate. (We will generally say “banks” for short.) It assumes that banks largely evolve successfully, with digital money supporting their continued centrality to the financial system.
For this paradigm to take hold, financial institutions need to demonstrate the commercial value of digital assets. Experimentation will lead to viable business models as banks become leading enablers for the new technologies, tokenizing both money and assets. Momentum could grow as solutions cascade across the system, from core activities like asset issuance and treasury to areas like merchant solutions and payments.
✅ Sovereign Expansion
In this paradigm, central banks would provide retail or wholesale users with CBDCs and use their instantaneous settlement capabilities to pick up a significant share of payment flows. Although central banks considering CBDCs are currently aiming to play a core role in payments without greatly disturbing the existing financial system, this paradigm assumes the process goes much further than current plans and does indeed transform the system.
Radical change in the role of the central bank would require societal support. Individuals could come to prefer the features provided by retail CBDCs. Alternatively, demand could be driven by investors and institutions who want to ensure their digital money is fully backstopped by the central bank. This diversion of payment flows from private money to public could have a significant impact on bank business models, which would have to rely more on equity and wholesale funding rather than deposits.
✅ Rise of Digital Intermediaries
This paradigm sits somewhere between evolution and revolution, with digital natives gaining scale as the traditional financial industry struggles to adapt. Banking could be squeezed, with digital natives controlling customer access and expanding financial services provided.
✅ Universal Networks
This is the most radical paradigm, one that would strongly transform the financial system. The rise of new open networks would enable borrowers and lenders, issuers and investors, and other market participants to deal directly, without intermediaries. Transactions would be powered and governed by smart contracts and institutional decentralized finance protocols. The trend toward capital market-based financing would be accelerated by algorithmic creation and allocation of credit over highly integrated networks. This could disrupt the business models of banks and today’s digital natives.
Source Olywer Wynam
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Preparing for PSD3
In the dynamic landscape shaped by PSD3, practical guidance becomes a compass for businesses and organizations navigating its implications. PSD3, much like any regulatory evolution, demands necessary adjustments across various company facets, whether they are established PSPs or innovative TPPs.
How can organizations prepare for the regulatory changes of PSD3?
✅ Stay informed: monitor the regulatory developments and announcements in the period leading up to expected implementation.
✅ Conduct impact assessments: understand how PSD3 will impact your organization. Identify areas of your business that will be affected to size the work to be done. Sia Partners identifies four key drivers that define the impact:
📌 Type of organization (e.g., traditional bank, PSPs, TPPs)
📌 Service model
📌 Life cycle (start-up, growth stage, maturity stage etc.)
📌 Size of the company
✅ Compliance training: ensure your compliance experts are up to date on the expected regulations and host training and awareness sessions within your organization.
✅ Review existing processes and policies: review policies to meet expected changes in areas like customer authentication, fraud prevention, data protection and risk management.
Considering the critical domains PSD3 impacts, and Sia Partners’ experience with implementing PSD2 for clients, an effort has been made to describe possible changes to the way each company is organized, as illustrated in the figure below.
This introspective evaluation, spanning operations, infrastructure, and systems, is not only a regulatory requirement but a strategic opportunity to ensure compliance readiness while proactively preparing for the shifting landscape. Amid these adjustments, collaboration emerges as a fundamental tenet.
Establishing a unified front among stakeholders — businesses, regulators, and industry players — fosters an environment ripe for cooperative adaptation, knowledge exchange, and the seamless realization of the regulatory transition. Engaging with regulators serves as an instrument for open dialogue, ensuring alignment with expectations and facilitating timely adjustments, thereby contributing to a harmonious and successful transition process.
Companies that proactively prepare for PSD3 before the mandatory deadline will gain a competitive advantage, building trust with customers by showcasing their commitment to security and compliance. They reduce the risk of fines, improve their security infrastructure, and can offer innovative, seamless payment experiences. Early preparation facilitates partnerships with banks and fintech firms, enables data monetization, ensures regulatory alignment, and provides valuable market insights. Moreover, it allows for cost-efficient compliance, positioning first-mover companies at the forefront of the evolving European payments industry.
Source Sia Partners
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Open Finance — the Gateway to an Open Data World
In late June 2023, the European Commission introduced a proposal for an Open Finance Framework in Europe, termed Financial Data Access (FIDA). Industry experts view this as a game-changer for the financial sector. Banks stand to benefit significantly from this new framework. Instead of merely providing data as mandated by PSD2, they can also access a wide variety of consumer information, including insurance, pension, mortgage, and investment data.
FIDA Will Enhance Existing PSD2
Use Cases In the initial three years post-PSD2’s 2019 implementation, banks predominantly concentrated on seamless API integration, without placing significant emphasis on crafting Use Cases based on customer transaction data.
Open Banking platform facilitator, ndgit, revealed that while 83% of their PSD2 users in Europe are banks, a staggering 96% of API requests originate from Third Party Providers (TPPs), illustrating that banks primarily focus on functionalities like Multi-Banking, while TPPs are venturing into more sophisticated business models. Major banks in Germany, including Deutsche Bank and Commerzbank, have launched Account Information Services (AIS), but fintech companies still hold a dominant position in this domain.
Finanzguru, a German financial tech company, is a top example of diving deep into open banking. They stand out, especially in bringing together account details and managing personal finances.
Open Finance is going to enhance current Open Banking Use Cases rather than creating entirely new ones. Most consumers might be unfamiliar with the term “Open Finance”. The key is to seamlessly integrate it into the daily use cases consumers encounter. By harnessing a broader spectrum of financial data, Open Finance will enhance existing Use Cases, such as Credit Assessment Buy Now Pay Later, and Account Aggregation. The graphic below provides a summary of examples of Open Finance use cases and potential future cases for an Open Data Economy.
Source Eraneos
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Capturing the full value of generative AI in banking
Generative AI (gen AI) applications are maturing among a vanguard of banking institutions. Most initial applications have centered on improving customer service, agent productivity, and software development. According to McKinsey analysis, about 75 percent of the value created by gen AI across all industries to date falls under customer engagement and three other categories: content synthesis (virtual expert), content generation, and coding and software.
— Customer engagement. Gen AI solutions can turn tedious, manual processes into more engaging, efficient interactions. For example, a consumer lender’s virtual assistant guides its employees through the loan application process with helpful extracts from chat history and explanations of terms, making the process more streamlined and less onerous. Some corporate banks are using gen AI to give employees an approved initial template that aids in drafting some types of servicing documentation.
— Content synthesis (virtual expert). Gen AI models augment employee performance by summarizing and drawing insights from massive amounts of information — for example, querying the latest public regulations across geographies; creating research reports, pitch decks, customer sentiment analyses, and instruction manuals; or acting as a “virtual expert.” Morgan Stanley has reportedly built an AI assistant, using GPT-4, that helps its tens of thousands of wealth managers quickly find and synthesize answers from a massive internal knowledge base; it also summarizes the content of client meetings and generates follow-up emails. Another leading bank reported it’s close to cutting the time to produce an investment brief by more than 90 percent (from nine hours to 30 minutes) by using gen AI.
— Content generation. Gen AI models can create customized content in real time for many use cases, such as personalized marketing and sales materials, based on customer profiles, history, and product details. One bank is using a GPT-based engine to create hyper-personalized marketing messages to accelerate an end-to-end campaign while improving overall effectiveness.
— Coding and software. Gen AI code assistants are helping companies address tech debt2 and accelerate software delivery. Code assistants translate legacy code to newer languages, using natural language prompts, and support developers by debugging and creating tests. They can also assess the banks’ legacy landscape by prioritizing interventions and refactoring.
Source McKinsey
