A-Team Group’s RegTech Summit, New York enters its tenth year in 2026. During the past decade we’ve seen rules-based/on-prem point solutions give way to cloud based SaaS implementations. The industry has come though significant regulatory refits and updates including a successful move to T+1 settlement in the US and Canada while Europe, UK and Switzerland prepare for the transition to T+1 this time next year.
Despite considerable progress, the industry continues to struggle with data governance, legacy infrastructure, brittle integrations, regulatory divergence across jurisdictions and soloed operations. As RegTechs are deploying AI Agents and advanced technologies, much of the industry still struggles moving pilots into production systems that can satisfy regulators, internal audit and risk committees.These issues will shape this year’s agenda where regulators, financial institutions and RegTechs will examine how firms can deploy AI and advanced technologies within controlled processes, extract value from fragmented data and respond to risks across established and emerging markets.
AI Meets Supervision
The opening keynote sets the tone for the day. Kaitlin Asrow, Acting Superintendent of the New York State Department of Financial Services (NYDFS), will address what supervisors expect as firms move AI into production.
Compliance teams have used machine learning for detection, risk scoring and alert prioritisation for years. Generative and agentic AI extend that role into policy interpretation, evidence gathering, investigations and workflow management, giving systems access to sensitive data and greater influence over regulated decisions.Firms must define what each system can do, which data it can access and when a person must intervene. They also need records that show how the system reached an output and who approved the result.
The opening panel will take that discussion into the compliance operating model. Speakers from ING, SMBC Group, Marex, NICE Actimize and Smarsh will examine where AI can deliver returns, why some projects remain stuck in sandboxes and which investments can move the needle for compliance performance.
Data Behind Controls
AI alone cannot resolve weak data ownership or disconnected systems. Compliance investigations draw on transactions, communications, documents, voice recordings and customer records held across business lines and platforms.
A panel led by Women in RegTech New York will examine how firms can combine structured and unstructured information for improved results. The discussion will cover data silos, lineage, quality and the growing volume of AI-generated communications.
These controls affect the value of every downstream use case. Surveillance teams need to trace an alert to the source material. Investigators need evidence they can test. Regulators need firms to explain the basis for a conclusion.
Reporting Problems Persist
Regulatory reporting shows both the progress and the limits of the past decade. Standards, cloud services and automated validation have improved processing, yet firms continue suffer overheads from incomplete or inaccurate submissions.
Andrew Pinnington of Novatus will address the remediation and back-reporting cycle before a subsequent panel examines current reporting demands. Its remit includes OTC derivatives reporting, the FINRA’s Consolidated Audit Trail (CAT), Customer Account Information System (CAIS) and Blue Sheets, as well as the SEC’s Form 13F-2 requirements. The session will consider buy-versus-build decisions along with AI and machine learning deployment best practices.
New Markets, Familiar Risks
Prediction markets and event contracts have witnessed rapid growth and present new market integrity challenges. David I. Miller, Director of the CFTC’s Division of Enforcement, will discuss enforcement priorities as new products and market structures develop. A follow-up panel featuring Robinhood, Kalshi and Novig will then take a deep-dive around manipulation, insider activity and conduct risk in event-driven markets.
An order book can show when a position changed, but not what the trader knew or whether someone sought to influence the market. Investigators must be able to reconstruct the sequence across orders, news, social posts, private communications and the trader’s relationships.
AI can identify activity that fixed rules miss. Investigators must rank connections and then test each connection against the source evidence and record why they escalated or closed the case.
A Wider Risk Perimeter
AI becomes an operational risk when it can read case files, query internal systems or influence a compliance decision. Prompt injection can alter its instructions, poisoned data can distort detection, and leakage can expose customer records or employee communications.
The risk also extends through the technology supply chain. Hosted models, cloud infrastructure and open-source components leave firms dependent on systems they may not control or inspect. An afternoon panel will examine how firms can map those dependencies, restrict system access, test failure scenarios and maintain service when a provider or model fails.
These risks cut across established control functions. Procurement teams assess suppliers, security teams test systems, model-risk teams challenge performance and compliance teams remain accountable for regulated outcomes. A well-governed, defensible AI operating model must connect those responsibilities.
The closing roundtables will take the discussion into implementation. Topics include the business case for compliance AI, perpetual KYC monitoring, global reporting architectures, unstructured data governance and AI security.
Over the past decade, RegTech has presented firms with stronger tools and greater processing capacity. The next phase will depend on whether the industry can turn those capabilities into controlled, measurable and repeatable processes. RegTech Summit New York brings together the people responsible for that work. You can be part of that discussion. Secure your spot by registering HERE.
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