Artificial Intelligence is rapidly becoming a strategic imperative for banks, but successful adoption requires more than implementing new technology. It demands robust strategy, clear governance, and a focus on delivering measurable business value.

Provenir’s Senior Data Scientist, Jiale Cheng, discusses how financial institutions can accelerate AI adoption in a way that is explainable, defensible, and aligned with evolving regulatory expectations.

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First-party fraud is becoming one of the toughest challenges facing banks and lenders today. Traditional fraud controls are struggling to keep pace as fraudsters leverage technology, social media, and increasingly sophisticated tactics to exploit gaps across the customer lifecycle.

The challenge is that first-party fraud is no longer a single problem. It has evolved into three distinct behavioral types: Criminal Operators, Opportunists, and Intentional Misrepresentation. Each have their own unique motivations, risk signals, and detection challenges. Treating them the same can leave institutions exposed to unnecessary losses while creating friction for legitimate customers.

In this Provenir-hosted webinar, Jason Abbott and Jason Gunther will break down these three first-party fraud personas, exploring how they operate, the warning signs they leave behind, and how organizations can use AI-driven approaches to identify and address risk earlier and more effectively.

AML and CFT expectations are evolving, and credit unions are being asked to prove results, not just process.

With the introduction of the proposed 2026 AML/CFT framework, regulators are moving decisively away from rule‑based compliance and toward measurable effectiveness. Examiners want to see clear evidence that financial institutions can identify risk, prioritize action, and adapt continuously as threats evolve.

For credit unions, this shift exposes a critical challenge. Traditional AML programs—built on fragmented data, static rules, and manual workflows—were not designed to demonstrate ongoing effectiveness across the member lifecycle. As a result, institutions face growing pressure to modernize how AML decisions are made, governed, and explained.

Provenir helps credit unions close this readiness gap by transforming AML from a reactive compliance function into an intelligent, risk‑based decisioning capability. By unifying data, analytics, and decision orchestration on a single platform, credit unions can continuously assess risk, align resources dynamically, and respond to regulatory change with confidence.

This report explores what the new AML/CFT model demands—and how Provenir enables credit unions to meet those expectations faster, more efficiently, and with greater transparency.

Decision-making in financial services has evolved. Static scorecards and retrospective insights are no longer enough in a world defined by real-time risk, rising fraud, and increasing regulatory pressure.

Watch this webinar replay which introduces Decision Intelligence —our powerful platform designed to help banks move from understanding risk to actively simulating, testing, and optimizing decisions before they go live.

In this on-demand session, we formally launch our new Decision Intelligence capabilities, walking through how models, insights, and simulation now work together to give decision-makers far greater control, transparency, and confidence.

We start by setting the scene: what’s changed in the market, why traditional decisioning approaches are falling short, and how simulation has become critical to managing risk, growth, and compliance. From there, we cover best practice approaches for using Decision Intelligence effectively across the credit lifecycle.

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