Digitalization and technologization affect numerous domains, promising advantages but also entailing risks. Hence, when decision-makers in highly-regulated domains like Finance implement these technological advances—especially Artificial Intelligence—regulators prescribe high levels of transparency, assuring the traceability of decisions for third parties. Explainable Artificial Intelligence (XAI) is of tremendous importance in this context. We provide an overview of current research on XAI in Finance with a systematic literature review screening 2,022 articles from leading Finance, Information Systems, and Computer Science outlets. We identify a set of 60 relevant articles, classify them according to the used XAI methods and goals that they aim to achieve, and provide an overview of XAI methods used in different Finance areas. Areas like risk management, portfolio optimization, and applications around the stock market are well-researched, while anti-money laundering is understudied. Researchers implement both transparent models and post-hoc explainability, while they recently favored the latter.

While digitalization offers numerous new possibilities for value creation, managers have to overcome a number of threats and obstacles that it harbors. In this context, the concept of Corporate Digital Responsibility (CDR) is of increasing interest to practitioners. Drawing on the well-established paradigm of Corporate Social Responsibility, CDR comprises a set of principles designed to encourage the ethical and conscientious development, adoption, and utilization of digital technologies. This work aims at contributing to the evolving research base by empirically assessing consumer preferences and a consumer segmentation approach with regard to companies’ concrete CDR activities, thus supporting the operationalization of CDR. Hence, this work provides concrete guidance for firms’ CDR activities in practice. To this end, a series of Best–Worst Scaling and dual response studies with a representative sample of 663 German-speaking participants assesses consumers’ perspectives on firms’ concrete (possible) activities within several CDR dimensions. Both DURE studies reveal the potential halo effect of data privacy and security activities on the perception of the CDR engagement at large, suggesting a more holistic approach to digital responsibilities. Besides, the findings reveal that in case of CDR one size does not fit all. Especially in terms of informational approaches, consumer preferences are rather heterogeneous suggesting that consumer segmentation is beneficial for companies. Additionally, the high importance of price for the consumers’ evaluation shows that it can be useful to offer a slimmed-down version in terms of CDR activities for more price-conscious consumers.

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