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Beneficial ownership has long been one of the most challenging aspects of anti-money laundering, but the task is becoming significantly more complex. Multi-layered corporate structures, cross-border entities, trusts and nominee arrangements can obscure who ultimately owns or controls an organisation, making it increasingly difficult for financial institutions to distinguish legitimate complexity from deliberate concealment. As …

For decades, KYC has been a cornerstone of financial crime compliance. Verify a customer’s identity, assess their risk and review them periodically. It is a model built around a simple assumption: that risk changes slowly. Today’s financial system tells a different story. Customers can onboard in minutes, move money instantly and change their risk profile …

Compliance was built for a slower world of periodic reviews, manual checks and retrospective oversight. But finance no longer operates at that pace. Transactions move instantly, risks evolve continuously and financial crime adapts in real time. As AI, automation and connected data systems mature, firms are beginning to rethink compliance not as a reactive function, …

AI is no longer peripheral – it is embedded in decision-making, risk, and control. As that shift accelerates, tolerance for ambiguity around accountability is collapsing. Regulators are no longer asking whether firms use AI, but whether they understand, control, and can stand behind it. This is where the accountability gap becomes real. The core tension …

Financial regulation has always been shaped by the boundaries it seeks to defend. Once, those boundaries were physical—bank branches, vaults, national borders. Then they became digital, defined by networks, firewalls, and systems. Today, those perimeters are dissolving. In their place, a new focal point is emerging: identity. As financial services fragment across platforms, jurisdictions and …

Launched in 2021, Massachusetts-based Rhino Federated Computing is focused on one of AI’s biggest challenges: activating siloed data through federated computing. Over the past three decades, financial institutions have invested heavily in making data available to enable better decisions for the business. Now the focus is on enabling advanced AI models and agents on top of that …

Regulation used to sit at the edges of the enterprise, tracked by specialist teams, interpreted periodically and pushed downstream into compliance, legal and risk functions. That model is starting to break. As regulatory change grows faster, broader and more complex, firms can no longer afford to treat regulatory intelligence as a background task or a …

Regulation was once positioned at the periphery of the financial system. A necessary constraint, reviewed periodically, handled reactively, and largely viewed as a cost of doing business. That perspective is starting to unravel.  Today, the sheer volume, speed and complexity of regulatory change mean that interpretation alone is no longer sufficient.    Firms are no longer just reading regulation; …

Financial crime detection is being quietly rebuilt from the ground up. What was once a rules-driven discipline – defined by static thresholds, retrospective reviews, and an ever-growing backlog of alerts – is now being reshaped by machine intelligence that can detect patterns, context, and intent in real time. The shift is not just technological; it …

RegTech was built to solve fragmentation in compliance. But as the sector consolidates and platforms expand across surveillance, reporting, identity and risk, a new question is emerging: are firms replacing operational fragmentation with platform concentration risk? For financial institutions, the appeal of unified RegTech stacks is obvious. Consolidated platforms promise lower costs, integrated data models …