CDAO APEX Financial Services schedule

Panelists: 

Jalaj Roy, Vice President, Enterprise Data Architecture, DEUTSCH BANK

Diego de Aragao, Senior Vice President, Balance Sheet Management & Analytics CITI

• How can you gain, and maintain buy in from those horizonal and vertical to you?
• What are the key principles to driving a culture of data? Do these really work? 
• How to effectively navigate people process and change management as part of your data strategy
• Data monetization and new revenue streams; what are some strategies to monetize data assets and create new revenue streams, whilst ensuring compliance with privacy regulations?
• What does good engineering, infrastructure and architecture look like in your enterprise?
• What are the latest trends in financial technology and how can data analytics be leveraged for innovative solutions? 
• Designing and delivering data governance and analytics capabilities in line with business goals

As Finance professionals and technologists, we are all aware of the time value of money, and the need for speed. We are also in a pivotal moment regarding various types of intelligence: Artificial, Business and Human.  Could it be that TTV ~ Speed * AI (BI + HI)?  Come to this session for some brief sensemaking in this opaque space.

-    Insights into how enhance value creation occurs when data goals and business goals are aligned 
-    The importance of agile and adaptable data strategies as a response to changing business needs
-    How can a robust data strategy empower informed decision making, optimizing process and identifying growth avenues for business success

Erum Manzoor, Senior Vice President, CITI

Ravi Bandaru, Director, Strategy and Innovation Lead, Enterprise Data Management Operations, BANK OF AMERICA

Brandon Walker, AI Strategy Lead, ROCKET MORTGAGE

Moderated by: 
Bhaskar Kalita, Global Head of Financial Services & Insurance, QUANTIPHI

• What are some of the potential risks associated with generative AI and the need for robust ethical frameworks
• Address challenges of protecting sensitive information, ensuring compliance with data regulations, and addressing the potential vulnerabilities
• Explore strategies for implementing privacy-preserving techniques to maintain integrity and confidentiality of data
• Insight into advances predictive modelling techniques for risk assessment, credit scoring, market analysis and investment strategy formulations
• Uncover how organizations can harness generative AI to generate novel ideas, prototypes, and insights, ultimately driving innovation and competitive advantage
• Discuss the potential of generative models to create realistic synthetic data

Panelists: 

Wendy Zhang, Vice President & Analytics, HAYWARD HOLDINGS

Jen Courant Head of Technology, Data and Innovation, DEUTSCHE BANK

Tu Le, Head of Retail Bank Operations Analytics, USAA

• Highlight the importance of fostering a data-driven culture essential to deliver growth and value amid cultural barriers
• Fostering an environment that enables self service data
• Addressing resistance to change within a large organization, and the importance of looking to the future
• Upskilling and reskilling the workforce to succeed in an evolving AI age
• How can enhanced culture and upskilling of the workforce improve business performance and data driven decision making
• Understanding the impact of a poor culture can hinder data sharing, quality and collaboration to foster new insights
• Discuss how to effectively encourage collaboration and leverage collective expertise
• The importance leadership in setting a data-driven vision for your organization

• Understanding how data management impact customer satisfaction and business growth. How can this be leveraged?
• How can data warehouses, data lakes, the cloud and advanced analytics tools can improve data management?
• Meeting regulatory compliances and privacy laws
• The future of data management in an increasingly digital world
• Best practice and strategies for data resilience

Explore the potential of Generative AI in enterprises while addressing key concerns such as data privacy, prompt injections, hallucinations, and AI Governance. Learn how to overcome these hurdles to enable the safe, secure, and compliant adoption of Generative AI, paving the way for accelerated innovation for your business.

• Discover best practices for ethical AI implementation, including responsible data collection, unbiased algorithm development, and transparent decision-making processes 
• Understand the importance of cross-sector collaboration and partnership-building to maximize the impact of AI for good  
• Keeping transparency at the forefront of AI in order to maintain trust and regulatory compliance
• Explore real-world case studies where data leaders successfully implemented AI-driven initiatives that resulted in tangible benefits for communities and the environment 
• Gain insights into strategies for measuring and evaluating the effectiveness of AI for good projects, demonstrate the value and outcomes of their initiatives to stakeholders and the wider community 
• Examine ethical considerations in algorithmic trading, robo-advisors, and investment strategies
• How can AI potentially impact market integrity
• Discuss the impact of ethical AI practices on public perception

Brandon Walker, AI Strategy Lead, Rocket Mortgage

Abha Dawesar, Divisional CDAO – Institutional Investor Group, VANGUARD

Ravi Bandaru, Director, Strategy and Innovation Lead, Enterprise Data Management Operations, BANK OF AMERICA

Ivan Fernandez, Head of Cloud Payments and FinTech Ecosystems, GOOGLE CLOUD

Moderated by:

Robert McMenamin, Lead Data Scientist, DATAROBOT

• The pros and cons of natural language processing to provide instant customer support and streamlined interactions
• Highlight the need for transparency and accountability in how customer data is collected, processed and used
• Exploring the intersection of AI and human collaboration in data analysis, focusing on how AI can augment human decision making rather than replacing it
• Ensuring there is sufficient data governance in gen AI and understanding the necessary regulatory implications
• Promoting explainability and transparency in AI systems empowers to provide clear insights into how AI models make decisions, enhancing trust, and facilitating better understanding of AI-generated outcomes

• Successfully navigating the rapidly evolving landscape of emerging technologies and determining which ones hold true value for your organization
• Integrating emerging technologies into the current technology stack
• Overcoming resistance to change and fostering a culture of experimentation and innovation
• Investing in skilled resources and expertise - acquiring the right talent to effectively deploy and integrate these technologies into the current stack

Rajiv Prakash, Head of Data Engineering, Bank & Digital, ALLY

Tu Le, Head of Retail Bank Operations Analytics, USAA

Lurdu Kunireddy, Director, Enterprise Data Science & AI, BMO FINANCIAL GROUP

Panel discussion – Improving your data strategy, data management, data governance and data security

• Understanding the importance of your data strategy being part of your business strategy
• Discuss the role of a data steward in ensuring data quality and compliance
• Understanding the importance of robust data architecture in effective data management
• How can data architecture improve and support scalability, performance and data integration?
• How can data quality be continuously be improved in order for data driven decision making