Mr. Mohamed Abdul Kadar Mohamed Jabarullah

Algorithmic Trust and Transparency: The Role of Generative AI in Shaping Investor Confidence in Brokerage Services

Abstract:

Generative AI is rapidly transforming financial services—powering algorithmic trading, predictive analytics, and personalized investment advice. But with innovation comes a challenge: can investors truly trust decisions made by opaque AI systems?

This keynote explores how transparency shapes investor confidence in AI-driven brokerage services. Drawing on surveys of 200+ investors, industry interviews, and real-world case studies, the research shows that trust is not built on performance alone. Platforms that clearly explain AI decisions achieved higher investor trust (4.5/5), satisfaction (90%), and engagement, compared to equally accurate but opaque systems.

Through case studies of firms using predictive analytics and “reason codes” for trades, the talk demonstrates how explainable AI builds stronger investor relationships. At the same time, it addresses risks such as information overload, bias, and regulatory gaps.

Attendees will gain practical insights into how brokerages, regulators, and investors can work together to design AI systems that are not only powerful, but trustworthy—turning AI from a mysterious black box into a transparent, reliable partner in finance.

Profile:

Mohamed Abdul Kadar Mohamed is a researcher and industry leader specializing in generative AI, cloud systems, and automation. As Manager of QC Automation in New York’s digital media sector, he integrates practical enterprise experience with academic research, authoring impactful publications that guide developers, executives, and policy thinkers.