Artificial Intelligence in Investment Banking: Automating Deal Structuring, Market Intelligence, and Client’s Insights Through Machine Learning
Keywords:
AI and ML; Investment Banking; Market Intelligence; Financial Technology; Digital TransformationAbstract
This study examines how artificial intelligence transforms investment banking operations through deal structuring automation, market intelligence generation, and client insight development. Using the Technology-Organization-Environment framework and Resource Based View, we investigate AI’s impact on operational efficiency, decision-making accuracy, and competitive advantage. Through mixed-methods analysis of 47 investment banks (2019-2022) and interviews with 32 senior executives, we find that AI reduces transaction time by 34%, improves valuation accuracy by 23%, and enhances client satisfaction by 41%. However, implementation faces barriers including data quality issues (73% of respondents), regulatory compliance concerns (68%), and talent challenges (61%). We identify three AI maturity archetypes pioneers (21%), followers (52%), and laggards (27%) each with distinct strategies and outcomes. This research contributes empirical evidence of AI’s impact on investment banking and offers practical insights for digital transformation
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