Edith Heroux

Financial institutions face an escalating compliance burden that has grown 300% in complexity over the past decade, with regulatory reporting requirements now consuming an estimated 10-15% of operational budgets at mid-tier and enterprise banks. Traditional approaches to compliance automation have relied heavily on rigid, rule-based systems that require extensive reconfiguration with each regulatory update—a cycle that has become unsustainable as regulatory frameworks evolve with increasing frequency. The emergence of adaptive automation technologies capable of navigating legacy compliance systems, extracting data from disparate sources, and executing multi-step verification workflows represents a fundamental shift in how financial institutions approach regulatory technology infrastructure. The practical application of Computer-Using Agents within financial compliance operations addresses several longstanding automation challenges that have resisted conventional RPA solutions. Regulat...

When investment banks like Goldman Sachs or Morgan Stanley execute a complex merger transaction, the sheer volume of data processing, document review, and analytical work happening behind the scenes is staggering. What clients see is a seamless deal execution, but what powers that efficiency today is increasingly sophisticated technology. The integration of automation, machine learning, and intelligent systems has fundamentally changed how M&A advisory teams operate, transforming workflows that once required armies of analysts into streamlined, technology-enabled processes that deliver faster insights with greater accuracy. The transformation brought by Intelligent Automation in M&A represents more than just efficiency gains. It fundamentally reshapes how advisory teams approach due diligence, valuation analysis, and integration planning. Rather than replacing human expertise, these systems amplify it, handling the repetitive, data-intensive tasks that previously consumed hund...