Over the past few decades, the financial industry has shown a keen interest in using computational intelligence to improve various financial processes. As a result, a range of models have been developed and published in numerous studies. However, in recent years, deep learning (DL) has gained significant attention within the field of machine learning (ML) due to its superior performance compared to traditional models. There are now several different DL implementations being used in finance, particularly in the rapidly growing field of Fintech. DL is being widely utilized to develop advanced banking services and investment strategies. This chapter provides a comprehensive overview of the current state-of-the-art in DL models for financial applications. The chapter is divided into categories based on the specific sub-fields of finance, and examines the use of DL models in each area. These include algorithmic trading, price forecasting, credit assessment, and fraud detection. The chapter aims to provide a concise overview of the various DL models being used in these fields and their potential impact on the future of finance.