AI and Data Analytics for Anti-Corruption Compliance – New York

Our opening session takes a focused look at the data‑quality foundations required to ensure reliable AI performance, covering the essential standards, validation workflows, and continuous‑monitoring mechanisms needed to maintain trustworthy outputs across evolving datasets. During this session, we will explore:

• Establishing data-quality standards as the bedrock of trustworthy AI
• Reducing variability at the source via collection protocols, controls, and human-in-the-loop validation
• Best practices and modern approaches to cleansing and enriching production-ready data
• Establishing continuous data monitoring by ensuring stability and detecting shifts in real-world data

This session explores how enterprises can responsibly design, govern, and deploy agentic AI while meeting regulatory obligations, maintaining human oversight, and preserving defensibility in high‑stakes environments.

• Understanding how agentic systems differ from traditional AI tools, including autonomous decision‑making, goal‑setting, and task execution; and exploring why this shift matters for compliance and investigative functions
• Examining emerging regulatory expectations, accountability frameworks, and ethical considerations when AI systems take actions that may impact individuals, evidence integrity, or regulatory outcomes
• Examples of agentic AI in compliance monitoring, triage, and investigations, and how organizations can mitigate them at scale

As organizations race to adopt AI, many struggle to quantify its true business value. This session demystifies the AI‑ROI equation, helping leaders identify which problems AI should solve, which it should not, and how to determine the right level of investment. Attendees will learn practical frameworks for measuring ROI, avoiding common value traps, and prioritizing AI use cases that drive measurable, sustainable impact.

During this practical and candid two-part series, compliance and data leaders will share how they built, scaled, and/or operationalized AI programs in real-world compliance environments. Panelists will discuss:

• Overcoming real-world AI implementation challenges by prioritizing strong data foundations and governance over technology-first experimentation.
• Leveraging AI to enhance compliance workflows by augmenting human judgment rather than attempting full automation.
• Applying transparency and explainability practices to build regulatory confidence and organizational trust in AI-driven compliance decisions.
• Repositioning compliance leaders as strategic partners who actively shape responsible AI adoption across the enterprise.

This panel examines how AI is being applied across the compliance lifecycle—from AI‑powered ABAC and due diligence to AI‑enhanced investigations intake and early‑stage case work. Panelists will discuss practical use cases for identifying and prioritizing risk, escalating meaningful signals, and accelerating first investigative responses. The conversation will focus on operational impact, governance considerations, and how compliance teams are balancing automation with human judgment as AI adoption matures, including:

• Leveraging intelligent signal detection in ABAC due diligence and early triage to shape the investigation lifecycle
• Accelerating early‑stage case work through automated evidence gathering and risk‑based prioritization
• Enabling mid‑cycle analysis and decision pathing with AI‑driven pattern detection and case progression
• Closing the loop with stronger outcomes, defensible documentation, and post‑investigation insights

High‑performance data teams are essential for organizations operating at global scale, where oversight, risk visibility, and data integrity depend on tightly aligned talent, governance, and technical capabilities. During this session, speakers will explore how leading enterprises structure, skill, and operationalize data teams to strengthen controls, embed quality across pipelines, and enable faster, more reliable decision‑making across complex international operations, including:

• Leveraging high-performance global data teams that enable real-time risk visibility through unified analytics capabilities across regions, functions, and regulatory domains
• Using advances analytics to strengthen cross-border compliance by detecting emerging patterns, anomalies, and jurisdiction-specific risk drivers earlier and more accurately
• Improving oversight and shortening decision cycles by modernizing analytics platforms that empower data teams
• Creating a culture of high performance built on shared standards, agile execution, and continuous skill development

Explore how next‑generation digital‑forensics tools and analytics techniques streamline evidence discovery, enhance visibility across jurisdictions, and improve speed and accuracy of global risk decision‑making. During this session, we will explore:

• Using advanced digital forensics tools to accelerate cross-border investigations
• Leveraging AI-enhances analytics to uncover hidden patterns, relationships, and anomalies that traditional forensic methods often miss
• Best practices for automated triaging and evidence-ranking workflows, enabling teams to focus quickly on the most critical risk signals
• Integrating digital-forensics platforms to improve global risk management through consistent, defensible investigative practices across jurisidictions