Artificial Intelligence in Investment Banking: Automating Deal Structuring, Market Intelligence, and Client’s Insights Through Machine Learning

Abstract

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