Managing Director and Global Head of Technology Consulting
Protiviti
Kim is Protiviti’s Global Leader of Technology Consulting. She is responsible for the strategy, offerings, consulting delivery and external alliance partnerships for all of Protiviti's technology capabilities, including Security & Privacy, Business Application Solutions, Technology Strategy & Architecture, Enterprise Data & Analytics, Software Services, Emerging Technologies, Technology Risk & Resilience, and Cloud. Previously, Kim was the Financial Services Lead for the Technology Consulting solution. With over 30 years of experience in the financial services industry, information technology, and consulting, Kim has been at the forefront of the convergence of technology innovation, business management, and regulatory reform.
Prior to Protiviti, she spent 14 years with UBS in several senior Chief Information Officer (CIO) positions including Global CIO of Corporate Technologies and most recently as Global Head of IT Risk Management. Kim was responsible for understanding the regulatory context surrounding the business, defining required controls, and driving the cultural mindset for compliance. In parallel, Kim had regional responsibility for the Technology group as CIO for Americas and sat on Intermediate Holding Company (IHC) governance boards. Prior, Kim spent 15 years at Andersen Consulting/Accenture where she rose to Partner in the Financial Services industry, aligned to both Capital Markets and Retail Banking clients with a focus on large scale technology implementations, merger execution, organization and solution design and reengineering.
A passionate advocate for diversity and LGBTQ+ equality, Kim serves on the advisory board of Protiviti’s women in technology employee network group. She is also an executive sponsor for Protiviti’s involvement in external industry organizations such as SIFMA, the Women’s Bond Club (where Kim co-chairs the Technology Committee), and the WSTA. In 2021, Kim was named to Consulting magazine’s ‘Women Leaders in Technology’ list in the Excellence in Innovation category.
Financial institutions that are looking to generate business outcomes with artificial intelligence (AI) must identify use cases that drive adoption by creating a strategic framework that aligns business value, data readiness and risk management. The goal is to achieve production-grade deployment that delivers a return on investment. The challenges that institutions face: data ecosystems are often fragmented and unprepared for AI scale, and risks—bias, privacy, security and regulatory compliance—can derail adoption if not addressed early. Among the points to be discussed by panelists: