Category: Hungary

Several provisions of the new Act on Hungarian Architecture (“Architecture Act”) entered into force on 1 October 2024, as a result of which the previous Building Act was repealed. The Architecture Act has taken over and supplemented many of the provisions of the previous Building Act, however, also contains a number of new rules.

In connection with the Architecture Act, the following government decrees were published in the Hungarian Gazette:

(a) the Government Decree on the Basic Regulation on Town Planning and Building Requirements, which will enter into force on 1 January 2025 and determines detailed and strict rules for the creation and number of car parks,

(b) the Government Decree on Procedures and Inspections by Building Authorities, a significant part of the provisions of which entered into force on 1 October 2024 and repealed the previous Government Decree in this subject,

(c) Government Decree on Municipal Green Infrastructure, Green Spaces Certificate and Green Trademark, which entered into force on October 2024 and which aims, among others, to create a liveable urban environment, improve the quality of life, increase the resilience of the municipality to climate change, and protect and enhance green spaces and biodiversity,

(d) the Government Decree on Architectural and Town Planning Councils, a significant part of the provisions of which entered into force on 1 October 2024,

(e) and several other decrees which amended other government decrees in the subject of architecture, certain government decrees relating to the entry into force of the Architecture Act and certain government decrees in connection with the land registry. As a result, from 29 September 2024, the Government Decree on the Building Industry Construction Activity has also been significantly amended. For example, it provides for additional provisions in construction contracts in the case of the involvement of the project fund manager (in Hungarian: “fedezetkezeő”), extends and modifies the responsibilities of the builder and the contractor, lists the responsibilities of the design inspector and regulates in detail the liability insurance of the contractor.

By Lidia Suveges, Attorney at law, KCG Partners Law Firm

The General Secretariat of the Belgian data protection authority has published an informational booklet outlining the relationship between the EU General Data Protection Regulation and the Artificial Intelligence Regulation, which came into force on 1 August 2024. The authority’s aim with the informational booklet is to provide insights into the application of data protection requirements during the development and deployment of artificial intelligence systems. Data protection requirements and legal standards are key to ensure that artificial intelligence systems operate ethically, responsibly and lawfully.

According to the authority, the two EU legislation establish complementary rules to ensure that the processing of personal data by artificial intelligence systems is lawful, fair and transparent. Legal professionals and data protection officers play a key role in ensuring compliance with data protection regulations, especially in adhering to rules regarding the processing of personal data. Moreover, it is also crucial for professionals working with the technical side of artificial intelligence systems, such as analysts, architects and developers to be knowledgeable about data protection requirements.

The authority provides a specific definition of artificial intelligence systems under the AI Regulation. According to this definition, an artificial intelligence system is an IT system designed to analyse data, recognise patterns, and make decisions or predictions based on this. The authority emphasizes that some systems evolve as they operate, learning from themselves and thus making more detailed and accurate decisions.

The Belgian authority gives the following examples from everyday life:

• E-mail spam filters: these filters distinguish between valid and invalid, false emails and evolve themselves over time, functioning as (i) an automated system; (ii) analysing data [the content of emails]; (iii) recognizing patterns [i.e., how a potential spam email is structured]; and (iv) making decisions [whether to direct the email to the spam folder or the inbox].
• Content recommendation system on a streaming platform: the streaming service provider operates an artificial intelligence system on its platform to recommend and display content that may interest users, which is also (i) an automated system; (ii) analyses data [based on past video views]; (iii) recognizes patterns [based on the personal preferences of the user and other similar users]; and (iv) makes recommendations based on the identified patterns.
• Virtual assistants: these assistants execute tasks based on voice commands, such as playing music, setting alarms, or controlling smart home devices. These assistants also (i) are automated systems; (ii) analyse data [the user’s voice commands]; (iii) recognize patterns [during interactions to understand specific commands]; (iv) make decisions [on how to respond to the user]; and (v) potentially improve themselves [e.g., by learning the user’s preferences].
• Medical image analysis: in many hospitals and healthcare providers, image analysis solutions are used to assist doctors in evaluating, for instance, X-rays and MRI scans. These systems are typically trained with vast amounts of diagnostic images to recognize specific patterns and ultimately anomalies. These systems (i) are automated; (ii) analyse data [images]; (iii) recognize patterns [deviations, disease indicators, anomalies]; and (iv) provide decision support [helping doctors make more accurate diagnoses when evaluating images].

Requirements of the General Data Protection Regulation and the AI Regulation:

• Lawfulness: the processing of data by AI systems must also rely on one of the six legal bases for data processing as defined in the General Data Protection Regulation [note: throughout every phase of their lifecycle, considering that these legal bases may change per cycle]. This lawfulness requirement must be interpreted together with Article 5 of the AI Regulation, which defines prohibited AI practices. According to the authority, examples of such prohibited practices include the use of social scoring systems or, with certain exceptions, the application of real-time facial recognition systems in public spaces.
• Fairness: the authority points out that although the AI Regulation does not explicitly mandate the application of fair processes, it builds upon the principle of fair data processing as stated in Article 5(1)(a) of the GDPR. The AI Regulation’s rules are aimed at minimizing biases and discrimination during the development, deployment, and use of AI systems.
• Transparency: the AI Regulation imposes minimum information requirements for all artificial intelligence systems. Accordingly, users must be informed that they are using an artificial intelligence system. For instance, a chatbot named “Nelson” must clearly indicate that it operates as a chatbot. High-risk AI systems require additional information, explaining clearly and understandably how the system uses data, particularly during decision-making processes, and what other factors influence decisions to mitigate bias.
• Purpose limitation and data minimisation: the principles of purpose limitation and data minimisation outlined in Article 5(1)(b) and (c) of the GDPR ensure that AI systems do not process data for purposes they were not designed for, nor should they collect excessive data. The AI Regulation particularly for high-risk AI systems reinforces this principle, requiring that the purposes for data processing be well-defined and documented in advance. The authority mentions credit scoring AI systems as an example, which, in addition to identification data, may also process geolocation and social media data, which makes it questionable whether they comply with the principle of data minimisation.
• Accuracy and currency of data: in line with the accuracy requirement of Article 5(1)(d) of the GDPR, the accuracy of personal data processed within AI systems must be ensured. The AI Regulation, building on this principle, mandates that data processed in high-risk AI systems must be of “high quality” [free from errors] and “objective” [complete]. For instance, in the case of a credit scoring AI system that evaluates applications based on location [postal code], bias may occur if residents of certain neighbourhoods are generally classified as lower income, which could result in discrimination against high-income applicants from the same area, even if their actual income level does not justify automatic rejection of their loan applications.
• Storage limitation: beyond Article 5(1)(e) of the GDPR, the AI Regulation does not impose additional requirements concerning storage limitation.
• Automated decision-making: both the AI Regulation and the General Data Protection Regulation place significant emphasis on human participation and oversight in automated decision-making, but from different perspectives. According to the GDPR, data subjects have the right to avoid being subjected to automated decision-making and can request human review of such automated decisions [see Article 22 of the GDPR]. On the other hand, the AI Regulation requires human oversight during the development, deployment, and application of high-risk AI systems. This oversight includes not only guiding decision-making but also human review of training data, measuring the AI system’s performance, and intervening in the decision-making process to ensure responsible AI development and use.
• Data security: a core requirement of the GDPR is to ensure the confidentiality of personal data throughout the entire data processing lifecycle. However, AI systems pose additional data security risks, therefore, additional measures are needed. High-risk AI systems face specific risks, such as biases in training data that could distort decision-making or malicious manipulation of training data by unauthorized individuals. Therefore, the AI Regulation prescribes preventive measures such as identifying risks, conducting risk assessments, continuously monitoring the system for data security [for example vulnerability assessments] and biases, and ensuring human oversight to safeguard security.
• Data subjects’ rights: the General Data Protection Regulation provides individuals with the means to exercise control over their personal data by ensuring data subject rights. However, this requires informing the data subjects in a transparent manner about the details of the data processing. Building on this basis, the AI Regulation imposes additional transparency obligations.
• Accountability: the General Data Protection Regulation lays down several requirements regarding liability for data processing, such as ensuring transparency in data processing, developing internal policies related to data processing activities, applying and documenting appropriate legal bases, keeping various records [e.g., records of data processing activities, records of data subject requests, records of data breaches], implementing organizational and technical security measures, conducting and documenting data protection impact assessments, and appointing a data protection officer [if required].

The AI Regulation does not separately address the principle of accountability, relying instead on the obligations outlined in the GDPR, while additionally requiring the application of a risk management framework. Risks must be assessed in two steps: (i) first, determine the risk classification of the AI system; (ii) for high-risk AI systems, a more detailed, system-specific risk assessment, such as a fundamental rights impact assessment, must be conducted. Furthermore, the design and installation of the AI system must be thoroughly documented, human oversight must be ensured for high-risk AI systems, and formal procedures must be established to detect and manage incidents related to the operation of AI systems or unintended outcomes.

By Adam Liber and Tamas Bereczki, Partners, and Eliza Nagy, Associate, Provaris Varga & Partners

 

Oppenheim has advised Romania’s MedLife Group affiliate Genesys Medical Clinic on the acquisition of Budapest-based VP-Med Health Centre from Attila Szabo and Olga Szegvari.

MedLife Group is a provider of private medical services in Romania, operating medical clinics, hospitals, and medical analysis laboratories. According to Oppenheim, “since the acquisition of RMC Clinics in 2019, MedLife has been one of the significant market players in Hungary as well.”

VP-Med Health Centre is a Hungarian private varicose vein center offering personalized treatment and surgery.

According to Oppenheim, the acquisition will expand RMC Clinics’ surgical services to include vascular surgeries. Attila Szabo, one of the founders of VP-Med, will “actively participate in the development and the management of the company after the acquisition. According to MedLife, education and training are important to both companies, so it was not difficult to align these goals.”

The Oppenheim team included Partner Mihaly Barcza, Counsel Zoltan Kolodzey, and Associate Lilla Julia Toth.

CMS has advised Werfen on its approximately USD 25 million acquisition of Omixon Biocomputing. Hogan Lovells advised Omixon.

Werfen is a Barcelona-based healthcare company.

Omixon Biocomputing is a transplant diagnostics company headquartered in Budapest.

The CMS team included Partner Aniko Kircsi, Senior Counsels Peter Toth and Gyorgy Balint, and Associates Orsolya Pass and Gergely Torma.

The Hogan Lovells team included Partner Sandor Bekesi and Senior Associate Gabor Koszo.

The National Bank of Hungary (NBH) introduced a new guideline No. NBH’s 9/2024, also known as the ESG (Environmental, Social and Governance) Guideline. This initiative aims to help financial institutions incorporate sustainability considerations into their risk management processes. The Guideline seeks to standardise the collection and assessment of ESG information, thereby enhancing predictability in legal compliance and reducing administrative burdens for businesses applying for credit.

Purpose and scope

The primary objective of the Guideline is to establish a standardised questionnaire for financial organisations to use during credit risk assessment. This will ensure that ESG information is consistently collected and evaluated, facilitating a more uniform application of the regulations. The Guideline applies to Hungarian financial institutions as well as branches of foreign institutions in Hungary.

Key components of the ESG questionnaire

The ESG questionnaire, detailed in the NBH’s recommendation, is divided into four main thematic blocks and 15 sub-blocks, covering the following topics:

1. General information

• Company size
• Activities

2. Environmental factors

• Climate change mitigation
• Adaptation to climate change
• Sustainable use and protection of water resources
• Transition to a circular economy
• Pollution prevention and reduction
• Protection and restoration of biodiversity and ecosystems

3. Social factors

• Employee relations
• Impact on society
• Consumer relations

4. Governance factors

• Reporting
• Supplier evaluation
• Ethical conduct
• Corporate governance

Implementation and compliance

The NBH expects financial organisations to incorporate the ESG questionnaire into their credit risk assessment processes. This involves collecting ESG information from new corporate loan applicants and integrating it into their risk management process. The Guideline also emphasises the importance of maintaining an up-to-date database of ESG information, which should include details such as the time of data collection, reference period and any significant ESG risks identified.

The NBH developed the Guideline in collaboration with the Supervisory Authority for Regulated Activities (SZTFH), which oversees compliance with ESG reporting under the Hungarian ESG Act (Act CVIII of 2023). However, the Guideline focuses solely on the credit assessment process and not on general compliance with the ESG Act.

Alignment with international standards

The ESG Guideline aligns with several international and European regulations, such as the Non-Financial Reporting Directive (NFRD), the Taxonomy Regulation, the Corporate Sustainability Reporting Directive (CSRD) and the European Sustainability Reporting Standards (EFRS). Such alignment ensures that the ESG information collected in Hungary meets global standards, making Hungarian sustainability reports more comparable and reliable.

Future developments

The Guideline outlines a phased implementation plan with different compliance deadlines based on the size of the loan agreements.

Financial organisations are expected to apply the Guideline to new corporate loans exceeding HUF 500m (approx. EUR 1,244,986) from 1 July 2025, with progressively lower thresholds in subsequent years (HUF 350m from 2026, HUF 200m from 2027, and HUF 100m from 2028). Financial institutions may voluntarily apply the questionnaire even for lower contractual amounts or from earlier dates.

Furthermore, the Guideline differentiates between micro, small, medium and large companies regarding the number of questions to be answered from the 62 questions and the level of detail required from the potential 321 items to be disclosed.

In compliance with the Guideline, financial organisations must, from 1 January 2025, publish information on their website highlighting the requirements for collecting ESG information.

By Gabor Pazsitka, Partner, Balint Bodo and Nora Lilla Szilvasi, Associates, Schoenherr

Wolf Theiss has advised XPartners Samhallsbyggnad on its acquisition of Aqvila and its Hungarian subsidiary Aqvila Consult Hungary.

XPartners is a technology consultant company.

Founded in Aarhus, Denmark, in 2010, Aqvila specializes in delivering engineering solutions, particularly in large-scale industrial projects and the life sciences sector. According to Wolf Theiss, this acquisition strengthens XPartners’ presence in Denmark and the broader Nordic region, while expanding its service portfolio.

The Wolf Theiss included Partner Janos Toth, Senior Associate Peter Ihasz, and Associate Nora Bogdany.

Editor’s Note: After this article was published, Wolf Theiss informed CEE Legal Matters that Danish law firm Bech-Bruun advised the sellers.

Former Dentons Partner Timea Bana has joined Kinstellar as a Partner and new head of the local TMT service line and sector.

Bana focuses primarily on TMT, data protection, and intellectual property.

Before joining Kinstellar, Bana was with Dentons as a Counsel between 2016 and 2022, and as a Partner between 2022 and 2024 (as reported by CEE Legal Matters on May 3, 2022). Earlier, she worked for Weil Gotshal and Manges as a Senior Associate between 2008 and 2016. Earlier still, she was an in-house counsel with the Hungarian Public Television between 2007 and 2008 and with RTL between 2002 and 2007.

Kinstellar has advised Banque Federative du Credit Mutuel on the acquisition of BNP Paribas’s Hungarian subsidiary Magyar Cetelem Bank. Wolf Theiss advised BNP Paribas.

The acquisition was carried out via Banque Federative du Credit Mutuel subsidiary Cofidis Bank.

BFCM is at the core of the Credit Mutuel Alliance Federale group, a French mutual group made up of 14 regional federations, supported by two networks (Credit Mutuel and CIC) whose main activity is Bancassurance. Its capital is 91.7% owned by Caisse Federale de Credit Mutuel.

The Kinstellar team included Budapest-based Partners Gabor Gelencser, Levente Hegedus, and Peter Voros, Senior Associates Bianka Kovacs, Aron Barta, and Daniel Endre Nagy, and Associates Judit Sos, Orsolya Staniszewski, and Veronika Heiszer and Prague-based Partner Karla Rundtova.

Editor’s Note: After this article was published, Wolf Theiss announced its team working on the deal included Partner Janos Toth, Counsel Melinda Pelikan, Senior Associate Gergely Szaloki, and Associates Laszlo Lovas and Viktoria Horvath.

Convertible loans have emerged as a pivotal financial instrument for start-ups navigating the challenging terrain of early-stage funding (pre-seed and seed), also called angel investment. These loans are a hybrid of debt and equity financing, offering a unique solution for companies that are not yet ready for a formal valuation or are seeking to bridge funding gaps between capital-raising rounds.

The essence of convertible loans

At its core, a convertible loan is a debt instrument that can be converted into equity at a later stage, typically during the subsequent round of funding. Convertible loans circumvent the need for immediate valuation, allowing investors to defer this decision until the company’s prospects become clearer and more stable.

The allure of convertible loans for start-ups lies in their ability to provide quick access to capital. This is crucial for maintaining momentum in operations, R&D and market expansion. Securing a convertible loan is often faster than traditional venture capital funding, which involves extensive due diligence and valuation processes.

On the other hand, investors benefit from the mitigation of risk inherent in convertible loans. Initially, the investment is structured as a loan with a fixed interest rate and maturity date. If the start-up succeeds and undergoes a new round of equity financing, the loan can be converted into equity at predetermined terms, which often include a discount on the share price. The potential for a discounted equity stake in a growing company can be a significant draw for investors.

Convertible loan agreements: “simplicity” and flexibility

Convertible loan agreements are typically concise and less complex than traditional debt or equity financing agreements. They can be drafted on a few pages, thereby significantly reducing transaction costs. The terms of these agreements are highly customisable, allowing for negotiation on interest rates, conversion discounts, valuation caps and repayment schedules to suit the needs of both start-ups and investors.

Key components of convertible loan agreements

A standard convertible loan agreement has the following critical elements.

1. Basic terms of the loan: These outline the amount, disbursement schedule, interest rate and loan repayment conditions.
2. Conversion mechanism: This section specifies the conditions under which the loan may be converted into equity, including the conversion rate, any applicable discounts or caps, and the rights and obligations of the investor.
3. Rights of the investor: These include the legal and financial protection granted to investors, such as rights to information, participation in decision-making (“reserved matters”), anti-dilution, share transfer restrictions, subscription, drag/tag-along, or preferences in the event of liquidation.
4. Subordination: Convertible loans often contain a subordination clause that places the repayment of loans behind other creditors in the event of insolvency.

However, the conversion of debt to equity is not automatic. It typically requires a shareholder resolution and capital increase resolution, as new shares are issued at the time of conversion. The terms of conversion, such as the valuation discount or cap, play a crucial role in determining the number of shares the investors receive. Usually, a valuation discount allows investors to convert their loans into equity at a lower price than that offered to new investors in the next funding round.

Hungary

The adoption of convertible loan principles in Hungarian legislation, namely Act XXXIV of 2004, as of 1 September 2023 marks a significant development for Hungary’s venture capital market. The legislation facilitates the use of convertible loans by not requiring supervisory authorisation from the National Bank of Hungary, provided certain conditions are met.

A key feature of the Hungarian model is the limitation on convertible loans to SMEs. Convertible loans may be issued no more than 15 times within a single calendar year. These regulations impose monetary caps on the total outstanding loan amount. For natural persons, including their family members, the cap is set at two billion Hungarian forints (HUF). The same cap applies to legal persons and their affiliates. Furthermore, the amount that can be ceded to the same company is limited to HUF 150m. Significantly, these regulations provide an exemption for financial institutions. Transactions of a similar nature conducted by such institutions are not subject to these requirements.

Conclusion

Convertible loans represent a strategic financing option for start-ups, balancing the immediate need for capital with the complexities of early-stage valuation. They offer a streamlined, flexible approach to funding that can adapt to the evolving needs of both start-ups and investors. As the venture capital landscape continues to evolve, convertible loans will likely remain one of the cornerstones of start-up financing, providing a bridge to future growth and success.

By Gabor Pazsitka, Partner, and Balint Bodo, Associate, Schoenherr

Adam Kaplonyi has joined Act Legal as a Partner in Budapest.

According to the firm, Kaplonyi focuses on real estate, corporate law, M&A, banking and finance, environmental law, and dispute resolution.

Before joining Act Legal, Kaplonyi worked for OPL Gunnercooke between 2020 and 2024. Earlier, he was a part of KPMG Legal Toaso between 2018 and 2019. Earlier still, he spent more than 11 years with Dentons as Of Counsel between 2007 and 2018.