AI Risk Program

Introducing our complimentary executive program

The Program

Embark on a comprehensive journey through our AI Risk Program, spanning three impactful modules! From unraveling the uses of AI technology to delving into the risks associated with AI technologies, this program equips you with insights on ethical considerations, legal implications, and compliance requirements. Explore real-world examples, governance frameworks, and strategies for risk identification and mitigation. Join us from April 3-17, 2024, to navigate the dynamic AI landscape.

2hs every Wednesday April 3, 10, 17, Total program length 6hs.

Introducing our complimentary executive program.

Day 1

April 3, 2024 10am - 12pm(East Coast Time)

Introduction to Artificial Intelligence and Machine Learning. Understanding Key Words


Explore the uses of AI technology.

  • Deep Analysis: Dive deep into the intricacies and risks of AI and ML technologies, moving beyond theoretical concepts.
  • Risk Assessment: Critically analyze the real-world application of AI and ML, understanding both their potential and potential pitfalls.
  • Advanced Topics Exploration: Explore complex areas like deep learning and algorithms for solving significant problems such as fraud and money laundering.
  • Future Insights: Gain a view into the future with expert panelists sharing trends, thought leadership, and the evolving landscape.
  • Broad Understanding: Conclude the module with a significantly enhanced understanding of the impact and utility of AI and ML technologies.


Andres Sarcuno

Deloitte Partner | Cono Sur Forensic Practice Leader | S-LATAM Forensics Data Analytics Leader| Designer of APPs to strengthening business ethics | Master in Data Science (studying)


Alejandro Picos

Global C-Suite Executive| Technology, Data/Analytics, Digital, Operations, Innovation | Vision, Strategy, Execution, Growth, Turnarounds, Profitability | Compliance, Risk| Big Data Transformation/Mgt, AI/ML | Product Mgt


Leandro Loss

Principal Data Scientist (Quantaverse AMLRS) | Visiting Professor (ESSCA Shanghai) | Adjunct Professor (ITU)

AML RightSource


Ana Maria de Alba

Founder & CEO at CSMB - A Risk Management Practice


Day 2

April 10, 2024 10am - 12pm(East Coast Time)

Introduction to AI Risks


Understand the risks associated with AI technologies. Discuss the potential ethical, legal, and social implications of AI. Explore the AI regulatory landscape, including existing regulations and compliance requirements for AI systems. Examine AI bias and fairness, and the importance of transparency and explainability in AI decision-making. Gain insights into interpreting and explaining AI models while considering the challenges and limitations of explainable AI.

  • Deep Analysis: Using Semantic Data to understand human behavior. Demonstration of how algorithms can predict, prevent, and detect dishonest actions.
    The Fraud Triangle as the theoretical basis for monitoring anti-ethical behaviors. Regulatory considerations.
  • Regulatory Landscape: EU Artificial Intelligence Act, AI Guidance and Data Protection. The fragmented state of U.S. guidance and legal frameworks.
  • Legal Considerations: Data Privacy, Consumer rights, Consent, and Copyright issues. Managing third-party supplier risks. Stayin ahead of the curve in AI development
  • Future Insights: Is 2024 the year of AI regulations in the U.S.? The rise of state level regulation and the move towards greater clarity at the federal level.


Stanley Foodman

Global Forensic CPA providing Complex Tax, Forensic Accounting and Financial Institution Compliance

CPA, CFE, CFF, CAMS, CGMA, TEP Foodman CPAs & Advisors

Gabriel Caballero

Abogado concentrado en Derecho Corporativo y el Sector Financiero

Holland & Knight

Richard Lopez

Regulatory & Compliance Chief Information Officer



Jairo Namur

Founder, Chief Commercial Officer

Intelligence for Action

Day 3

April 17, 2024 12pm - 2pm(East Coast Time)

AI/ML Case Studies and Risk Management


Explore real-world examples of AI risks and compliance challenges through case studies. Learn from lessons learned and best practices. Introduction to AI governance frameworks and standards, discussing the components of effective AI governance. Discover methods for identifying and assessing risks in AI projects, along with risk prioritization and mitigation strategies. Understand the unique risks associated with AI data, models, and decision-making. Address data privacy and security challenges in AI applications, and learn best practices for ensuring privacy and security in AI system development and deployment.


Richard Lopez

Regulatory & Compliance Chief Information Officer


Marta Cadavid

I am a Fraud Fighter | Behavioral Risk | Human Risk Prediction | AI NPL HBA | The Fraud Explorer | Fraude al Desnudo


María Catalina González

IT Project Lead - Retail, Digital Transformation & Technology Projects | Scrum SMAC™ | Kanban

Mercado Libre


Raul Saccani

Navigating the Dark Side of Human Nature in Business | Financial Crimes Specialist | Integrity & Compliance Professor | Speaker |


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