AI Tools for Finance Workflows Proliferate
New AI-powered platforms are emerging to streamline finance workflows. Global Financial AI launched a no-code platform for strategy modeling, while other startups are introducing AI plug-ins to assist with tasks like deal reviews in investment banking and portfolio management.
- In the Technology, Media, and Telecom (TMT) sector, AI is now a primary driver of M&A activity. Approximately 80% of current AI-related investments are led by large tech companies known as "hyperscalers," who often co-invest with private equity firms and infrastructure funds to finance essential infrastructure like data centers. - For Financial Sponsors, AI platforms are automating the creation of Leveraged Buyout (LBO) models, reducing a process that once took weeks to as little as 30-60 minutes. These tools can automatically build three-statement models with integrated debt schedules and calculate IRR and MOIC across various scenarios. The private equity firm EQT uses a proprietary tool called "Motherbrain" that has reportedly increased its modeling efficiency by 40%. - Natural Language Processing (NLP) is significantly accelerating M&A due diligence by analyzing legal documents. AI tools can automatically extract key terms, clauses, and obligations from hundreds of pages of contracts in minutes, a task that would manually take lawyers days to complete. - In Corporate Finance and FP&A, AI is automating routine tasks like variance analysis and data collection, allowing teams to focus more on strategic business partnering. AI-driven analytics can now embed environmental, social, and governance (ESG) data directly into financial forecasts to identify correlations between sustainable practices and financial results. - For portfolio management, asset managers are using machine learning to construct and optimize portfolios, moving beyond traditional mean-variance optimization. These algorithms analyze unstructured data from news articles and social media to identify complex patterns and market signals that may not be apparent to human analysts. - The role of the investment banking analyst is shifting away from manual data entry and toward supervising AI outputs and focusing on more strategic analysis. A Deloitte study predicts that generative AI could boost the productivity of front-office employees by 27-35% by 2026. - To adapt to this shift, major financial institutions have started to mandate AI training for new hires. For example, JPMorgan initiated mandatory generative AI training for all new employees in 2024, and Citi began upskilling its workforce in prompt writing in 2025.
