TY - JOUR
T1 - Advances in explainable artificial intelligence (xAI) in Finance
AU - Klein, Tony
AU - Walther, Thomas
N1 - Publisher Copyright:
© 2024 Elsevier Inc.
PY - 2024/12
Y1 - 2024/12
N2 - Explainable Artificial Intelligence addresses the black box problem associated with AI, aiming to promote greater transparency, traceability, and trust in applications of AI. xAI is becoming a vital element in finance and economics in fields like risk management, credit decisions, and regulatory compliance. The need for xAI arises from the challenges in understanding, trusting, and communicating AI-generated results. While some argue for the adoption of inherently interpretable models, others critique popular xAI methods. This special issue explores xAI’s role in finance and its advances, focusing on its implications for future research, practice, and policy in FinTech.
AB - Explainable Artificial Intelligence addresses the black box problem associated with AI, aiming to promote greater transparency, traceability, and trust in applications of AI. xAI is becoming a vital element in finance and economics in fields like risk management, credit decisions, and regulatory compliance. The need for xAI arises from the challenges in understanding, trusting, and communicating AI-generated results. While some argue for the adoption of inherently interpretable models, others critique popular xAI methods. This special issue explores xAI’s role in finance and its advances, focusing on its implications for future research, practice, and policy in FinTech.
KW - Artificial intelligence
KW - Explainable AI
KW - FinTech
KW - Machine learning
UR - http://www.scopus.com/inward/record.url?scp=85209124023&partnerID=8YFLogxK
U2 - 10.1016/j.frl.2024.106358
DO - 10.1016/j.frl.2024.106358
M3 - Editorial
SN - 1544-6123
VL - 70
JO - Finance Research Letters
JF - Finance Research Letters
M1 - 106358
ER -