At a time when professionals across finance face increased pressure to integrate artificial intelligence into their workflows, data has become the cornerstone of every decision system. It’s not the fuel; it’s the foundation. Yet more data doesn’t automatically mean better intelligence, and overreliance on AI can create costly blind spots.

In this Keynote, Cornell Professor Victoria Averbukh and Evan Reich, Chief Product Officer and Head of AI at BWG Global, will use real-world examples to illustrate how and why AI models often fall short in finance. They’ll explore how bias, flawed assumptions, and misplaced trust in machine outputs can lead to poor decisions — and why human judgment remains essential.

You will discover practical ideas for sharpening your instincts, critically evaluating AI-driven insights, and striking the right balance between automation and expertise in financial decision making.
  • Why more data doesn’t guarantee better AI outcomes and how focusing on quality over quantity can safeguard against costly failures in finance
  • Techniques for spotting common AI failure patterns that lead to inaccurate outputs and unreliable decision making
  • How to integrate AI assistance with human judgment to enhance accuracy and manage risk in complex financial contexts
  • Frameworks for applying professional skepticism to ensure the effective and ethical adoption of AI tools in financial workflows

View Keynote by completing the form below.

Gain access to this free event