Utilization / Ownership of Channels and Changes Driven by AI (A01)

The Transformation of Banking: From Exclusivity to Open Systems

In the 1990s, it was a given: the services we used from banks belonged exclusively to the banks. Every transaction, every account inquiry, every loan was processed through the designated channels of the banks. However, over time, this picture began to change. Initially, commission-based businesses and early partnerships emerged, extending the influence of banks and marking the first steps towards an open market. In the last 20 years, the landscape has continued to evolve: lead generation, marketplaces, and product placements have come to the forefront, followed by strategic partnerships with fintechs that have complemented traditional banking. Today, we are in an era where banks not only offer their own services but increasingly rely on APIs, Banking as a Service (BaaS), and Embedded Finance to enhance their value proposition. Banks are opening up their systems—some voluntarily, others due to regulatory requirements—to grant third-party providers access and unlock new business models and revenue streams.

The Future of Interface Control in a Bot-Driven Economy

Yet, as these developments progress, a critical question arises: Who actually controls the interfaces through which we interact with our data and services in the AI future and Bot Economy? Currently, these interfaces still belong to the banks and financial institutions that maintain their connection to the customer through their own apps and systems.

In Europe, further changes may occur due to regulatory plans. The European Commission aims to expand data sharing beyond the existing regulations with FIDA. In addition to banks, insurance companies and investment funds are also expected to open their customer data to third-party providers. This creates a certain asymmetry: while banks, and perhaps soon other financial service providers, are likely to offer data access for free, third parties such as AI assistants could use this data, enhance it, and either earn commissions or close deals directly.

Bank AI can only remain competitive through interoperability

To illustrate this, let's consider two possible future scenarios:

Level 1: An AI assistant from the bank accesses the bank app, analyzes expenses in real time, and suggests automatically directing unused funds into short-term investments. This can already be achieved today, more or less, with PFM tools (Personal Finance Management) or robo-advisory.

Level 2: An AI agent that seamlessly interacts with calendars, hotel booking apps, and payment systems to efficiently plan trips, automatically book the best deals, and securely process payments. Imagine a specific Level 2 use case: An AI assistant automatically books a hotel for the next business trip through the preferred hotel booking app. The assistant knows from previous booking habits that the customer never cancel a hotel stays and rarely reschedule trips. Therefore, it has chosen the prepaid, non-refundable rate—the most cost-effective option tailored perfectly to customer needs. But the assistant goes even further: it made this decision because it recently signed up for a platinum credit card that includes travel cancellation insurance for health issues. Should illness force to cancel, this insurance would apply.

Of course, this scenario could be expanded further: the assistant could add missing pay-per-use products or, as in the first example, conclude liquidity and investment products. But let's leave it at this example for now. The real advantage of Level 2 lies in the seamless interoperability of various services. While Level 1 offers pure analysis and decision-making within a single application—already largely covered today by PFM tools and robo-advisors—Level 2 demonstrates its true strength through the linkage and interaction of multiple systems. Here, the AI agent not only accesses individual data sources or a single app but also connects different platforms like calendars, hotel booking apps, and payment services. This tight integration allows AI to handle more complex tasks and optimize experiences—from planning to booking to final processing. The ability to integrate data from various sources and make tailored decisions based on this elevates Level 2 to a whole new level, distinguishing a simple financial assistant from a truly intelligent companion. An isolated application with partial AI use doesn’t offer the same value as the fully integrated solution of a Level 2 AI system.

Banks must act quickly and start transforming their platforms towards a super app model. Otherwise, they risk losing ground to tech-driven players who already offer comprehensive and interconnected solutions. This development will be crucial to remain competitive in the fiercely contested market of digital financial services.

Critics would surely come up with 100 reasons why all of this might not work: data protection, security, lack of customer trust in AI – the list could go on endlessly. In fact, surveys show that a significant portion of consumers still have concerns about sharing personal data with AI systems. In a recent poll conducted within my LinkedIn network, which included 30 industry professionals, only 10% stated that they would fully trust an AI banking bot to manage their finances entirely. The majority, 47%, preferred to retain control over most decisions and allow the bot to only execute certain tasks. Another 30% would only trust a bot with simple tasks, while 13% did not want any bot involvement at all.

These results highlight that despite technological advancements, many customers remain skeptical about fully automated solutions. To overcome these hurdles, banks and technology companies must not only ensure technological security but also strengthen users' trust in the ethical use of their data. Striking a balance between automation and control will be crucial to ensuring the long-term acceptance of AI solutions in the financial sector.

Financial Opportunities and Risks: Customer Retention in the Age of AI

Instead of focusing on the hurdles, we ask a central question: Who will ultimately benefit from the revenues when AI assistants increasingly manage customers’ lives? And how strong will customer retention remain with banks if interactions are increasingly controlled by technological platforms of large corporations?

The fact is, the Customer Lifetime Value (CLV) of traditional banks is already under pressure today, as many banking services are becoming increasingly interchangeable, and distribution is no longer primarily controlled by the banks themselves. In response, modern players in the market are increasingly relying on partnerships in new business areas such as embedded finance or banking-as-a-service.

Banks that do not take an active role in the field of Artificial Intelligence (AI) risk being left behind. On the other hand, those that focus on hyper-personalization through AI can secure market share in the short term and increase CLV by offering tailored products and services. However, in the long term, the question arises whether it won’t be the providers of AI infrastructure, supporting the bot economy, who will be the real winners. These companies have the potential to control key interfaces and dominate direct access to customers, which could further marginalize banks.

A look at current developments shows that the future of the bot economy is already taking shape. In the summer of 2024, the U.S.-based startup Skyfire is enabling autonomous payments through AI agents. With a funding round of 85 million dollars, Skyfire aims to further develop this technology and establish itself as an infrastructure provider for the bot economy—a potential challenger to established credit card and online payment providers.

Skyfire plans to revolutionize efficiency and security in payment transactions by providing a platform where AI agents can seamlessly conduct payments and transactions on behalf of users. Their approach enables the linking of various services and allows payments to be processed directly by AI agents, not only increasing convenience for end users but also reducing reliance on traditional banking infrastructures. Through this strategy, Skyfire aims to play a key role in the infrastructure of the new digital financial landscape and take control of the interfaces through which customers will interact in the future.

This development highlights the growing trend towards a decentralized financial world, where banks that do not actively invest in AI and modern technologies risk losing their direct relationship with customers. Providers like Skyfire could be the main players in such a future, dominating customer interfaces through innovative platforms. For traditional banks, this means they must redefine their role to remain competitive in the rapidly changing digital landscape.

The Future of Customer Interfaces: As History Shows, UX Determines Success

In the past, it was the branches where banks had direct access to their customers. But with the advent of digitalization, the landscape has drastically changed.

A look at payment behavior shows how quickly users can be convinced by good user experience (UX). Mobile payment solutions like Apple Pay and Google Pay have managed to gain a broad user base in a very short time. The ease of use and seamless integration into customers' everyday lives have ensured that more and more people are willing to change their traditional payment habits. The high adoption rates of these technologies illustrate that customers are increasingly ready to switch to new platforms if they offer a more convenient and intuitive experience.

Looking at examples like Starbucks or the Apple Savings account, it becomes clear that customer trust no longer solely belongs to banks. Starbucks has managed to build strong customer loyalty with its loyalty program and proprietary payment app, far beyond the sale of coffee. Similarly, Apple has strengthened customer trust as a financial service provider with its savings program integrated directly into the Wallet app. These examples demonstrate that customers are increasingly willing to entrust their financial matters to companies that do not traditionally operate as banks.

Now, if a product comes to market that manages to fully automate and manage the often tedious financial tasks, an important question arises: Which interface will still be relevant to the customer in such a world? The answer to this will be shaped by the user experience. If a provider can significantly simplify users' daily lives through a seamless, intuitive, and smart technology, that interface will become the indispensable gateway for their financial transactions.

In this scenario, control over the customer interface shifts away from traditional banks and toward the technology companies that provide these solutions. These companies, which assume direct contact with customers, will become the new gatekeepers of the financial world. Traditional banks risk being reduced to the role of mere infrastructure providers, while the real added value—and therefore the profits—increasingly lie with the tech providers offering a superior user experience.

But the challenge goes far beyond the user interface: it's not about building the most colorful, beautiful, and simple application screens or the most streamlined processes. Rather, the focus is on the fundamental use and control of the channels themselves. The question of who owns the critical interfaces and who controls access to the customers is increasingly being influenced by AI. The technologies that are accepted and adopted by users will ultimately determine who dominates these channels. AI-based solutions have the potential to control customer interfaces and cut traditional banks out of direct interaction. This shift is profound and demonstrates how AI can reshape both the use and control of channels in the financial sector.

Outlook for the Next Part of the Series

This development leads us to an exciting next topic: competition and collaboration. In a world where artificial intelligence is becoming a central competitive factor, we must take a closer look at the dynamics between Big Tech, Fintechs, and traditional banks. How will these players operate in an AI-dominated financial world? Will they collaborate to create new synergies, or are we on the verge of an era of intense competition? We will explore these questions in the next chapter.