This chapter discusses the most important challengesChallenges of delivering transparencyTransparency for black-box modelsBlack-box models in the context of the latest explainable AIExplainable AI literature and the regulatory framework introduced by the European UnionEuropean Union AI ActAI Act. The key AI technologiesKey AI technologies in FinanceAI technologies in finance are presented. Recent advances in AIArtificial intelligence (AI) applied to financeFinance are mainly credited to Machine LearningMachine learning techniques based on Deep Neural Networks. As AIArtificial intelligence (AI) becomes more integrated into the financial sector, a significant challengeChallenges emerges from the limited human ability to comprehend the complexities of the black-box modelsBlack-box models. Recent legislation, such as the European AI ActAI Act, emphasises the importance of AI systemsAI systems transparencyTransparency, particularly in high-risk areas. There is a growing demand for explainable AIExplainable AI to ensure that the decision-makingDecision-making processes of AI systemsAI systems are clear and well-documented to meet regulatory transparencyTransparency requirements. However, there is no agreement on how to promote the transparencyTransparency of AIArtificial intelligence (AI) models. While post-hoc explanatory models can be useful in many situations, they also have limitations and therefore, especially in high-stakes decision-makingDecision-making contexts, interpretabilityInterpretability should be favoured over explainabilityExplainability.