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This article discusses recent advances in mathematical methods for finance. It highlights the impact of developments in financial markets, technology, and societal challenges on the field of Mathematical Finance. The article also mentions the emergence of new financial products, regulatory frameworks, and trading infrastructures, as well as the revolutionary changes brought about by artificial intelligence and machine learning techniques in numerical methods for finance. Additionally, it acknowledges the growing importance of new types of risks, such as climate-related and cyber-risks, in the financial industry. The article introduces a special issue on Recent Advances in Mathematical Methods for Finance, which provides a comprehensive overview of the latest developments in the field. The special issue includes 44 papers that underwent a rigorous peer review process, covering both theoretical and applied research in mathematical finance. The authors express their gratitude to the editor and staff for the opportunity to edit the special issue and to the referees and authors for their contributions. They hope that this collection of papers will stimulate further research in the field. [Extracted from the article]

The data revolution transforms operations, innovation, and society through artificial intelligence and advanced analytics. Data-driven innovations (DDI) have the most potential to tackle global challenges, including poverty, healthcare, climate actions, disaster management, gender inequality, peace and justice and others. This paper identifies the sources of DDI capabilities to address various global challenges. The findings show three major foundations of DDI capabilities: market orientation, infrastructure orientation, and talent orientation. Theoretically, these findings highlight the role of dynamic DDI capabilities to sense, seize and transform global challenges. Practically, we present guidelines for developing DDI in an agile and efficient manner that is fair and inclusive. [ABSTRACT FROM AUTHOR]