Community
Regulatory pressure remains one of the most critical challenges facing financial institutions today. Regulations differ by country, are often vague or even contradictory, and continue to evolve - whether through the introduction of new rules or updates to existing ones. At the same time, regulators are becoming significantly more demanding, both in terms of timing and evidentiary requirements.
Regulatory expectations have intensified in two distinct but interrelated ways:
Today, data proof is essential. Banks must demonstrate that compliance procedures are consistently applied across all transactions - not just exceptions. This marks a fundamental shift: it’s no longer sufficient to describe what should happen. Institutions must now prove what did happen.
This new paradigm demands granular visibility into every transaction, including:
Banks must also maintain full data lineage, tracing how data moves and transforms through systems. This is no longer a nice-to-have. It has become a regulatory imperative.
Additional this data must be retained and easily accessible for 8 to 15 years, depending on jurisdiction and transaction type. This generates massive volumes of data, which must be accessible both individually (e.g. details for one transaction) and in aggregate (e.g. all transactions over a certain threshold from a specific counterparty, country, or customer, along with derived statistics). Legacy systems, often siloed and fragmented, make this difficult. Banks need modern, integrated solutions capable of consolidating these large volumes of data and ensuring fast access, analytics and compliance reporting.
The scale and complexity of such data-driven compliance mean that modernization and automation are essential. Financial institutions must adopt solutions to capture, store, and analyze these vast datasets and derive actionable insights. AI can assist by validating processes, tracking evolving rule applications, and identifying anomalies in real time. It can detect hidden patterns - for example, a customer receiving multiple small payments that appear suspicious only when combined, or several customers using similar descriptions to mask coordinated activity.
This shift calls for a move from reactive to proactive compliance. Instead of responding only when flagged by a regulator, institutions must continuously monitor for risks and generate automated alerts when irregularities occur. This approach builds regulatory trust and reduces operational risk.
Non-compliance now brings consequences far beyond fines. It damages reputations, erodes client trust, and limits future business opportunities. Today’s regulators demand not just transparency, but also traceability and reproducibility. Banks must be able to demonstrate not only what decision was made - but also how and why it was made.
As financial crime becomes more sophisticated, data-driven compliance is both a necessity and a strategic advantage. Institutions that master it will not only meet regulatory expectations but also differentiate themselves in a competitive marketplace.
For more insights, visit my blog at https://bankloch.blogspot.com
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
Serhii Bondarenko Artificial Intelegence at Tickeron
30 July
Prashant Bansal Sr. Principal Consultant at Oracle
28 July
Carlo R.W. De Meijer Owner and Economist at MIFSA
Steve Morgan Banking Industry Market Lead at Pegasystems
Welcome to Finextra. We use cookies to help us to deliver our services. You may change your preferences at our Cookie Centre.
Please read our Privacy Policy.