EP 4 — Fidelity National Financial’s Ward Balcerzak on Navigating Data Security in a Cloud-First World

In this episode of The Future of Data Security Show, Jean speaks with Ward Balcerzak, AVP and Director of Data Security & Insider Risk at Fidelity National Financial, who shares his expertise on the evolving challenges of data security in today’s cloud-first landscape. Ward discusses the critical importance of establishing a comprehensive data inventory and discovery process to effectively manage sensitive information.    Ward also offers his insights into the implications of generative AI on data protection, highlighting the need for robust governance strategies to mitigate risks. With a focus on collaboration across departments, this episode offers valuable insights for organizations looking to enhance their data security practices in an increasingly complex environment.   Topics discussed:   The shift from traditional data security to cloud-first strategies and the challenges that come with managing sensitive data in a decentralized environment.   The unique data protection challenges faced by organizations in the financial services and real estate sectors, particularly regarding title services and sensitive information.   The complexities of managing structured versus unstructured data and the importance of understanding data types for effective protection and compliance.   The role of generative AI in transforming data security practices and the need for organizations to adapt their strategies accordingly.   The significance of building a comprehensive data inventory and discovery process to identify and protect sensitive information across various platforms.   The importance of collaboration between departments, such as IT, HR, and legal, to gain a holistic view of data security needs.   Strategies for implementing effective governance processes around AI usage to ensure sensitive data is not inadvertently exposed or mishandled.   The challenges of data loss prevention technologies and how they can be used to mitigate risks associated with new AI tools.   The necessity of having well-defined policies and enforcement mechanisms to support data security efforts and prevent user pushback.