The financial sector has always been a pioneer in the use of data and algorithms; now it is becoming the touchstone for European AI regulation, because hardly any other industry utilizes data-driven models as intensively as the financial sector. With the European AI Regulation (EU Artificial Intelligence Act, or ” EU AI Act” for short) coming into force on August 1, 2024, financial companies are once again the focus of regulatory scrutiny.

Behind the EU AI Act lies the world’s first comprehensive set of rules for the regulation of Artificial Intelligence. The objective of the regulation is to enable innovation, while simultaneously guaranteeing safety, transparency, and the protection of fundamental rights. Similar to the GDPR, the AI Act is intended to set a global standard. For financial companies, banks, and Fintechs, this regulation marks a turning point.

 

Why the AI Act is not a Tech Topic, but a Business Topic

The EU AI Act does not just change compliance processes in IT departments, but rather deeply intervenes in product development, innovation, and business models. AI governance is becoming a central management task, similar to data protection following the GDPR. The responsibility no longer lies solely with developers and data scientists, but with the entire management team.

Data quality, transparency, and traceability are developing into genuine competitive factors. Companies that invest today in clean data architectures and documented AI processes are creating a strategic advantage for themselves. Conversely, those who treat AI as a purely technical project will struggle in the future to meet regulatory requirements and build trust with customers and partners.

The EU AI Act is therefore more than just another compliance topic; rather, it fundamentally changes how financial companies develop, deploy, and monitor AI. Banks and Fintechs already rely today on automated systems, for instance in creditworthiness assessment, fraud detection, or risk analysis, and many of these applications will be classified in the future as high-risk AI systems and will thus be subject to stringent requirements.

What does the EU AI Act understand by an AI system?

In Article 3, Paragraph 1 of the AI Act, “AI system” is defined as follows: It is a “machine-based system that is designed to operate with varying degrees of autonomy and that may be adaptive after its deployment, and that, for explicit or implicit objectives, derives from the received input how outputs such as predictions, content, recommendations, or decisions are generated that can influence physical or virtual environments.”

The Risk-Based Approach: Four Categories, Clear Rules

The core of the EU AI Act is a risk-based regulatory approach. Depending on a system’s potential impact, requirements of differing strictness apply. At the top are prohibited AI practices presenting an unacceptable risk, which endanger fundamental rights or safety and are completely forbidden. These include, for example, social scoring, manipulative systems, or certain forms of real-time biometric identification.

The subsequent category is High-Risk AI Systems. This category applies whenever the system makes decisions concerning the rights, safety, or economic situation of individuals. In the financial sector, this typically includes creditworthiness assessments and scoring models, fraud detection and anti-money laundering, automated credit decisions, robo-advisory and portfolio optimization, and insurance underwriting.

Systems with limited risk , such as chatbots or generative AI, are primarily subject to transparency obligations. Users must be able to recognize that they are interacting with an AI. Everyday applications like spam filters or recommendation systems are finally considered minimally risky and are not subject to any additional obligations.

Furthermore, the EU AI Act clearly distinguishes between Providers (those who develop AI) and Deployers (users who utilize AI).

Definition of “Provider” according to the EU AI Act

Is a natural or legal person, public authority, agency, or other body that develops an AI system or a General Purpose AI (GPAI) model or has an AI system or GPAI model developed and places it on the market or puts it into service under its own name or trademark, irrespective of whether this is done for payment or free of charge.

Definition of “Deployer” according to the EU AI Act

Is a natural or legal person, public authority, agency, or other body that uses an AI system under its supervision, unless the AI system is used in the course of a personal, non-professional activity.

High-Risk AI: Obligations for Providers and Deployers

High-Risk AI systems are particularly relevant for the financial sector.. Both Providers and Deployers/Users bear responsibility. For High-Risk AI systems , particularly extensive requirements apply to Providers:

• Structured Risk Management: Identification, assessment, and mitigation of potential risks throughout the entire system lifecycle.
• Data Quality: Training, validation, and testing data must be representative, error-free, and non-discriminatory. Here, the quality of the data foundation becomes the decisive factor.
• Technical Documentation: Complete traceability of the system architecture, data sources, and functionality—similar to a technical audit trail.
• Transparency: Users must be informed about the system’s functionality, limitations, and purpose.
• Human Oversight: Systems may not make critical decisions completely autonomously. The “Human-in-the-Loop” is mandatory.
• Conformity Assessment: Similar to a CE certification, Providers must prove that their systems meet the EU requirements.

But Deployers or Users are also under an obligation. Companies that use AI systems in their own operations must ensure that only compliant systems are utilized, that the systems are deployed within the intended scope, and that employees are properly trained. Crucially, the responsibility remains even when purchasing external AI solutions, for example, from scoring or fraud detection providers.

 

The Financial Sector in the Dense Web of Regulation

The financial sector is one of the most heavily regulated areas overall. The AI Act supplements existing regulations such as MiFID II, PSD2, the EBA Guidelines on ICT risks, or the upcoming Digital Operational Resilience Act (DORA). This means that financial companies must not view AI compliance in isolation, but as part of a larger governance framework.

The AI Act thus becomes a driver for new structures. Companies must define clear responsibilities, establish internal control systems for AI, and implement audit trails and monitoring processes. This can, however, also be an advantage, particularly for banks and established fintechs, as many already have experience with complex compliance requirements and can build upon existing governance structures.

Practical Steps Towards Compliance

Financial companies should already be reviewing how their existing systems and processes are affected by the AI Act. The following steps are considered best practice:

• Inventory: Creating an overview of all utilized AI systems (internal and external).
• Classification: Categorization according to the AI Act’s risk levels—which systems fall under High-Risk?

• Gap Analysis: Reviewing which requirements are already met and where a need for improvement exists.

• Governance Structure: Appointing responsible parties (e.g., “AI Compliance Officer”), establishing internal control systems, defining decision pathways.

• Documentation: Traceable records of data sources, training processes, parameters, and model decisions. Here, versioning becomes a critical success factor.

• Monitoring & Testing: Introduction of ongoing surveillance and evaluation of the AI systems, including post-market monitoring.

 

Opportunities for Regulated Innovation or: How much Regulation is too much?

The EU AI Act mandates “clean” AI. For fintechs, this presents an opportunity: Transparent, compliant AI creates trust. And trust is the decisive currency in the financial sector. Customers, partners, and supervisory authorities increasingly expect traceable decisions and verifiable fairness in automated processes. Those who focus on “Compliance by Design” today—integrating regulatory requirements into product development from the start—can scale faster tomorrow. The necessary documentation, data quality, and governance are not bothersome supplementary tasks but rather establish the foundation for robust, trustworthy systems.

For banks, the AI Act also opens up new opportunities for partnerships with regulated technology providers. Instead of developing AI solutions completely in-house, they can rely on specialized providers who already supply compliant systems. This saves resources and enables faster innovation. Provided that the partners meet the regulatory standards.

Despite the necessity of regulation, the question also arises: Where is the right balance between security and innovation? The EU AI Act is an ambitious set of rules, but practice will show whether implementation succeeds in being proportional and innovation-friendly.

A central challenge is the risk of bureaucratization, especially for smaller providers. Start-ups and young fintechs often lack the resources to build extensive documentation and compliance structures. Here, there is a risk that innovation will be hampered because the administrative effort becomes too great. The consequence could be a consolidation of the market, at the expense of competition and diversity.

In addition, many technical standards are still missing. How exactly is bias in training data measured? What depth of documentation is appropriate? What exactly does “human oversight” look like in concrete terms? These questions are not trivial. Without clear standards, different interpretations in the Member States threaten to undermine the hoped-for harmonization.

At the same time, a lack of regulation would be even riskier. Without binding standards, there is a risk of a patchwork of national rules, a lack of market confidence, and, in the worst-case scenario, discriminatory or non-transparent AI systems that undermine trust in the entire industry. The EU AI Act provides a necessary framework—what will be decisive is how flexibly and practically the supervisory authorities implement it.

 

Timeline and Transitional Periods

The Regulation entered into force on August 1, 2024, and provides for staggered transitional periods that make different aspects of the regulation effective at different times. Since February 2, 2025, the prohibitions for certain unacceptable AI practices from Chapter II of the Act have already taken effect. One year after entry into force, i.e., since August 2, 2025, the regulations on notified bodies, General-Purpose AI (GPAI) models, administration, and sanctions became applicable.

The full application of the provisions for High-Risk AI follows from August 2, 2026, i.e., 24 months after entry into force. For certain AI systems that are components of large-scale IT systems, an extended transitional period applies until December 31, 2030. Finally, the national supervisory structures must be fully implemented in all Member States by August 2, 2027.

Special regulations apply to systems already on the market: High-Risk AI systems placed on the market before August 2, 2026, only have to be compliant if they undergo substantial changes. GPAI models that entered the market before August 2, 2025, have until August 2, 2027, for adaptation.

In Germany, the Federal Network Agency (Bundesnetzagentur) will function as the market surveillance authority and the German Accreditation Body (Deutsche Akkreditierungsstelle) as the notifying authority. The market surveillance authority monitors compliance with the provisions and can intervene in the event of violations. This creates a dual supervisory regime for financial companies: AI systems must comply with both regulatory requirements—for example, those of BaFin (the Federal Financial Supervisory Authority)—and the technical requirements of the AI Act.

 

Where APIs and Data Infrastructure Come into Play

For infrastructure providers like WealthAPI, the AI Act plays an important indirect role. Even though we do not develop decision-making AI models ourselves, APIs are central interfaces through which data flows, transparency, and auditability are enabled.

The AI Act thus also promotes technological interoperability and data quality —two prerequisites for meeting regulatory requirements in automated financial processes. Clean, structured, and traceable data streams become the foundation for compliant AI systems.

Specifically, this means:

• Data Quality as the Foundation: AI is only as good as the data it is trained with. APIs must deliver reliable, consistent, and complete data.
• Traceability: Audit trails and versioning of data sources become more important than ever.
• Interoperability: Systems must work together seamlessly to enable human oversight and control mechanisms.

This becomes particularly relevant for Embedded Finance and API-based business models. When financial services are increasingly integrated into other platforms via interfaces, these interfaces must be auditable and traceable. The responsibility does not end at the API—it extends across the entire value chain.

For WealthAPI, this means: We see ourselves as an enabler for data access, transparency, and compliant solutions in the financial environment. Our task is to provide financial companies with the data infrastructure they need to use AI responsibly. This includes clean data streams, traceable processes, and the technical basis for audit trails.

 

Conclusion: Regulation as a Framework for Trust

The EU AI Act introduces a new standard for dealing with Artificial Intelligence, particularly in the financial sector. It raises the requirements for transparency, traceability, and governance, but also creates the foundation for trust in data-driven innovations.

The financial industry has a decisive advantage: it is familiar with regulation. Banks and fintechs have decades of experience dealing with complex compliance requirements. This competence makes them ideal pioneers for “Trustworthy AI”—that is, AI systems that are not only powerful but also responsible and traceable.

Financial companies that invest in AI compliance today are laying the foundation for sustainable innovation. They minimize regulatory risks and strengthen the trust of customers, supervisory authorities, and partners. The core message remains: AI needs trust. And trust is created through control, transparency, and compliance.

The EU AI Act provides the framework for this—now it is up to the financial industry to bring it to life. For fintechs and banks, this is less of an obstacle than an opportunity—to take the next step towards responsible, explainable, and sustainable AI.

 

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Frequently Asked Questions

• What is the EU AI Act – and why does it affect financial companies?

The EU AI Act (Artificial Intelligence Act) is the world’s first comprehensive set of rules for the regulation of Artificial Intelligence. The goal is to enable innovation while simultaneously ensuring safety, transparency, and the protection of fundamental rights. Similar to the General Data Protection Regulation (GDPR), the AI Act aims to set a global standard.

The Regulation is highly significant, particularly in the financial sector: Banks and fintechs deploy AI systems in sensitive areas such as credit granting, fraud detection, risk analysis, or investment advice. Many of these applications will in the future be classified as High-Risk AI systems and must meet stringent requirements.

 

• Which AI systems are regulated by the EU AI Act?

According to Article 3 of the Act, an AI system is a “machine-based system that operates autonomously and adaptively after its deployment and generates outputs such as predictions, recommendations, or decisions from inputs that influence real or virtual environments.”

The AI Act operates with a risk-based approach:

• • Unacceptable Risk: e.g., social scoring or manipulative systems – forbidden.
  • High Risk: e.g., scoring, credit decisions, fraud detection – specially regulated.
  • Limited Risk: e.g., chatbots, generative AI – transparency obligations.
  • Minimal Risk: e.g., spam filters – no additional requirements.

 

• What are the obligations for Providers and Deployers of AI systems?

The AI Act clearly distinguishes between Providers (who develop AI systems) and Deployers (who use them).

For Providers of High-Risk AI, the following applies:

• • Structured Risk Management
  • Traceable and non-discriminatory training data
  • Technical documentation and audit trails
  • Transparency regarding purpose and limitations
  • Human oversight (“Human-in-the-Loop”)
  • Conformity assessment similar to a CE certification

For Deployers, the following applies: Even those who “only” use AI systems bear responsibility. Companies must ensure that they use only compliant systems, apply them correctly, and that employees are trained. Important: Liability remains even when purchasing external AI solutions.

 

• What role does the EU AI Act play in the regulatory landscape?

The financial sector is already heavily regulated by MiFID II, PSD2, DORA, and EBA guidelines. The AI Act supplements these sets of rules and creates new requirements for governance, documentation, and monitoring.

Financial companies must in the future:

• • clearly define responsibilities for AI,
  • establish internal control systems,
  • and implement continuous review mechanisms.

For many banks and fintechs, this is not a disadvantage: existing compliance structures can be extended.

 

• Which practical steps must fintechs and banks take now?

Financial companies should start implementation early. Best practices are:

• • Inventory: Create an overview of all utilized AI systems.
  • Classification: Categorization according to the AI Act’s risk levels.
  • Gap Analysis: Determine where there is a need for improvement.
  • Governance Structure: Appoint responsible parties, define control systems.
  • Documentation: Record all data sources, training processes, and model decisions.
  • Monitoring: Implement ongoing surveillance and evaluation (“Post-Market-Monitoring”).

 

• What opportunities arise from the EU AI Act?

The EU AI Act mandates “clean” AI. This can be a competitive advantage. Fintechs that focus early on Compliance by Design create trust with customers and supervisory authorities. Transparent and traceable systems enable sustainable scaling, higher data security, and new collaborations between banks and tech providers.For smaller providers, the challenge remains to fulfill documentation and audit obligations in a resource-efficient manner. Collaboration with specialized API or infrastructure partners can help here.

 

• When does the EU AI Act take effect?

  • Entry into force: August 1, 2024
  • Prohibited AI practices: since February 2, 2025
  • High-Risk systems: from August 2, 2026
  • National supervisory structures: by August 2, 2027

In Germany, the Federal Network Agency (Bundesnetzagentur) takes over market surveillance, while the German Accreditation Body (Deutsche Akkreditierungsstelle) acts as the notifying authority. This creates a dual supervisory regime for financial companies: in addition to the requirements of BaFin, technical proof obligations now also apply.