Gerald Joseph is a technology and finance executive with 30+ years of leadership in enterprise data platforms, cloud transformation, and AI and machine learning enablement across financial services and federal organizations.
Drawing on deep expertise in data governance, cybersecurity, and regulatory compliance, he has led cross-functional teams to modernize analytics and risk capabilities—delivering large-scale cloud and data-warehouse initiatives that migrated 2,000+ users and 150+ applications, building analytics in Salesforce, Amazon Web Services, and Azure, as well as NLP platforms, and standing up security insight dashboards for senior executives on accelerated timelines.
Gerald also brings deep finance-domain experience spanning enterprise risk, capital markets, and mortgage analytics. At Fannie Mae, he led AI/ML quantitative model risk and analytics, overseeing risk reporting strategy, product roadmaps, and budgeting while developing risk frameworks, KRI/KPI metrics, and mortgage compliance dashboards aligned to regulatory expectations.
Earlier, he supported market and credit risk oversight within Fannie Mae’s Enterprise Risk Executive Office, and delivered capital-markets-focused solutions including mortgage forensic review workflows that supported fraud prevention, along with SEC enforcement analytics for insider trading and fraud analytics.
Education
- MBA, Johns Hopkins Carey Business School
- BEng, National Institute of Technology, Trichy, India
Teaching
Current
- Practical Machine Learning
Impact and engagement
Business
- Presenter and delivery in conferences with AWS/Azure/Databricks conferences
- Expert in business analytics, presenting to credit risk committee
- Large scale budget and people management
- Represent enterprise with university relationship such as recruiting, hackathons
Policy
- Internal Risk policy development wrt Market Risk,Credit Risk and Model Risk
- Aligning CyberSecurity Framework with ZeroTrust/RMF/NIST/DOD Frameworks
- Large scale Modernization