German companies or German-based subsidiaries of international businesses may become subject of, or otherwise involved in, investigations by German or foreign regulatory or law enforcement authorities. In the context of such investigations, it is not unusual for the concerned company to face informal requests from German or foreign regulatory and law enforcement authorities for voluntary cooperation. Oftentimes, such requests focus on the transfer of electronic data for investigatory purposes, and such data typically relate, in whole or in part, to individuals (e.g. employees, suppliers and customers). In these and other cases, compliance of German companies or German-based subsidiaries with informal requests from regulatory and law enforcement authorities may itself entail a compliance risk or even constitute a breach by the corporate entity of the German data protection laws resulting in criminal prosecution, administrative sanctions, or damage claims and other actions by third party individuals. This article outlines the scope of application of the German Federal Data Protection Act, introduces the applicable statutory provisions, and discusses the relevant considerations in the context of an informal request by a regulatory or law enforcement authority for voluntary cooperation in the context of global investigations, in particular where a German-based entity faces requests from authorities abroad.

In light of the demanding requirements inherent to the operation of a university hospital, a multitude of compliance risks are entailed in the medical care, training, and research entail which such institutions are engaged in. If such risks materialize, the public will notice, which will substantially tarnish not only the public’s confidence in the proper functioning and the integrity of the impacted hospital, but ultimately, the whole German health care system. In examining the structural and requisite prevention protocols, three risk groups can be distinguished. The Düsseldorf University Hospital provides a leading example in the area of compliance management.

Conflicts of interest (COI) in healthcare have increasingly gained attention in the lay press as well as among healthcare professionals. COIs increase the risk of undue influence on professional decision making and may have far-reaching consequences in healthcare. Therefore, it is essential to develop strategies to deal with such risk situations in order to prevent negative outcomes for patients and the health care system. This article describes recent research on COIs in Germany as well as initiatives aiming at more transparency and better management of COIs in Germany.

The Munich Compliance Talk entitled "Legal Privilege – What is its use actually about?" took place on April 26th, 2016 at the Literaturhaus Munich. At this event, which has been organized together by the Deutschen AnwaltSpiegel – Gruppe and Recommind, compliance professionals, namely lawyers, employees of in-house legal departments, compliance officers and compliance managers have been present. The conference program included impulsive lectures by the experts Dr. Burkhard Schmitt1 (Vice President, Head of EMEIA Compliance at Fujitsu, Munich) and Patrick Späth2, LL.M. (Counsel of WilmerHale in Berlin). Emphasis was – among other things - placed on the legal framework of legal privilege. Moreover the focus was on the company''s point of view, thus the question, how to deal with legal privilege in the company.

It gives us great pleasure to introduce you to our fourth edition of the Compliance Elliance Journal (CEJ). We are particularly pleased of a significant innovation, which accompanies our new edition. From now on the CEJ has an Advisory Board, consisting of Derek Six (Compliance Manager at DAW Group, Germany), Marcus Traut (Attorney at and Owner of Anwaltskanzlei Marcus Traut, Germany) and Kenneth Tung (Co-Founder and Chief Strategy Officer at In-Gear Legalytics Limited, China). We are glad that they are willing to support CEJ by their pushing ideas, suggestions and contributions. Thank you for deciding to join CEJ.

The edition features first-rate articles by specialists in the field of healthcare and data security. Apart from that we will face some classical compliance topics and last but not least CEJ Founder Michele DeStefanos new book Legal Upheaval will be introduced and reviewed.

The presented study investigates the role of Machine Learning in Regulatory Compliance software systems by conducting a case study in the maritime industry. There is a need to obtain a clear understanding of Machine Learning approaches for automating regulatory compliance.  Background: Organizations and software developers face different regulations in different domains that need to be satisfied by the requirements of systems. Trading across borders brings challenges in managing each country's regulatory requirements. Even though a large amount of effort from international and local organizations, an efficient AI-based system is not yet fully deployed for offering decision support in handling such complex issues as a viable solution. The increasing enforcement of sanctions and anti-money laundering by various institutions and countries poses a significant threat to many industries worldwide if they are not educated or aware of the legal and financial risks. therefore, Regulatory Compliance plays a critical role in this area. Regulatory Compliance is a guideline for laws or regulations related to the business that the stakeholders must abide by to promote a safer business environment and benefit society. Developing a Digital Compliance(DigiComp) system as a software service is a solution that involves both technical and organizational challenges which need a large amount of research. As a case study, an AI-based DigiComp system has been implemented in the port of Vordingborg for the EU-financed project "Connect2SmallPorts". A major Corporate challenge was the choice of appropriate and efficient approaches and tools for designing the automated regulatory compliance system. This study investigates the role of Machine Learning in regulatory compliance systems and its possible opportunities and limitations.  Objectives: The significant role of compliance management made it an interesting research topic since some highly regulated systems need to follow specific laws and guidelines. As the objectives of this study, the role of machine learning on regulatory compliance systems has been investigated by extracting the most popular ML approaches and their benefits and challenges from previous studies and then analyzing the related benefits and limitations in a real-world case. Methods: We have done a systematic literature review as the qualitative research method with database search and snowballing to collect the applied Machine Learning approaches and their benefits and challenges for Regulatory Compliance software systems. Then a case study was conducted for implementing a regulatory compliance system in the maritime industry and investigating the benefits and challenges in a real-world project. Also, Focus groups and interviews with the stakeholder and domain experts were held as data collection methods during the case study.  Results: After investigating the existing challenges in regulatory compliance and identifying the risk assessment framework based on Machine Learning as the most popular AI approach in this area, we implemented a risk assessment framework based on neural networks. It provides high accuracy and a low error rate in predicting the future state to prevent the non-compliance risk. Conclusions: Examining the proposed digital compliance system explores its similarity to the benefits and limitations extracted from SLR. This study has provided the development of a new AI-Based system that can inspire software companies to build more efficient regulatory compliance systems for different domains in the industry.

Compliance with data protection requirements is always a tricky business and even more intricate when it comes to cutting-edge technologies such as distributed ledger technology (DLT), better known as Block Chain Technology (BCT). These difficulties increase even more when the personal data concerned is accorded a special level of protection, as is the case with health data. The following article aims to describe and analyze the legal issues associated with this scenario. The focus here is on the European Union's (EU) General Data Protection Regulation (GDPR) 1, which took effect on May 25, 2018. Furthermore, the functionality of BCT and its possible fields of application in healthcare will be outlined.

Data-driven business models make up the medical and healthcare market in large parts, a trend reinforced by further technological developments and regulation. Care must be taken to avoid a situation where only a few players benefit. It’s weird the patient has to become a customer in order to be a human being in the health business: The consistent empowerment of patients to handle their own data is essential.

In May 2018, the 121st German Medical Association in Erfurt decided to relax the prohibition of exclusive remote treatment which had previously been standardized in the Model Professional Code of Conduct for physicians working in Germany (MBO-Ä). With this, the German Medical Association has responded to the continuing call for progress and further development in terms of digitization. Nevertheless, many questions remain unanswered, such as the implementation and interpretation of the provisions of § 7 para. 4 MBO-Ä in its new wording and their embedding in existing regulations. Data protection, which defines the legal limits of remote treatment, also plays an important role here.