Financial crime is evolving at a rapid pace, in the last few years alone we’ve seen an explosion in the sophistication involved in new criminal fraud tactics. In the years running up to 2024, nearly half (49%) of businesses worldwide reported experiencing deepfake or AI-related scams. This itself resulted in losses per company reaching the $600,000 mark.
The creation of synthetic identities. Cross-border mule networks coordinated via the dark web. And the use of privacy coins and decentralised mixers in crypto laundering, are all other forms of fraudulent activity on the rise. And this is just the tip of the iceberg.
For banks and institutions, tackling these new sophisticated crime tactics is one thing, the other is navigating the increasingly complex regulatory environment.
It’s a tough time, and one that requires a new approach to tackling both fraud and compliance, an approach that goes above and beyond the traditional compliance models in use today which are largely based on static, rules-based systems.
This is where Artificial intelligence (AI) comes in.
AI and compliance are the perfect partners. It’s revolutionizing how banks and financial institutions meet today’s challenges, not by replacing human judgment, but by enhancing it.
From automating repetitive reviews to detecting subtle behavioral shifts, AI is taking compliance and fraud detection from being a reactive burden, into a proactive intelligence-driven function. AI is now a must-have in the fight against fraudulent activity.
The complex regulatory mandates that banks and institutions need to comply with include the EU’s AI Act which stipulates that any AI decisions must be interpretable and traceable.
Further to this, The Financial Action Task Force (FATF) also recommends that AI tools should be integrated into AML programs in order to automate risk, working from large volumes of unstructured data.
The EU's Digital Operational Resilience Act (DORA), effective from January 17, 2025, mandates that financial entities bolster their resilience against ICT-related disruptions to ensure continuity and security of services.
Lastly, both the The Financial Crimes Enforcement Network (FinCEN) in the USA and the Financial Conduct Authority (FCA) in the UK are both advocates for the use of AI to enhance the effectiveness of AML detection.
To remain compliant with financial crime regulations, institutions must monitor every transaction and conduct thorough due diligence on every customer. However, the sheer scale of global financial activity makes this increasingly unmanageable with conventional tools. Legacy systems rely on fixed rules that often lack the nuance to distinguish between suspicious and benign activity, leading to:
More critically, these rigid systems also divert attention away from complex, high-risk cases that demand deeper investigation. The result? A compliance model that’s reactive, inefficient, and increasingly unsustainable.
AI offers a smarter, more scalable alternative.
By learning from vast historical datasets, AI models can identify patterns of both legitimate and illicit behavior across thousands of variables, something static rules simply can’t do.
AI systems can:
AI not only increases the accuracy of alerts but also enables compliance teams to focus on what matters most: investigating genuinely suspicious activity and staying ahead of emerging threats.
For banks and institutions, the transition to AI can seem daunting. That’s why we implement it using a phased approach, enhancing what institutions already use and gradually building trust rather than a complete switch over from legacy systems immediately.
Our three-step phased AI implementation approach looks like this:
Using an institution's existing transaction data, we insert our Calibration Module which works on refining the existing rule thresholds.
It does this by simulating various rule settings and scenarios before recommending the optimal thresholds to use, each tailored to specific customer segments.
There is no one size fits all approach to this and by segmenting clients into more homogeneous groups, banks and institutions can significantly reduce false positives from the start.
This work lays the groundwork for smarter detection all round.
With an optimized rule system in place, we then deploy AIDa (AI Detection Advisor), a machine learning engine that predicts which alerts are likely to be false positives.
AIDa is able to do this by analyzing and learning from past alert outcomes, it then intelligently suppresses low-value alerts, sharpening its focus on truly risky transactions.
Used in tandem with the Calibration Module, this layered approach is extremely powerful and dramatically reduces alert fatigue while boosting investigative efficiency.
With a strong AI foundation established, it’s time to introduce an advanced deep learning model that goes way beyond the simple rules based systems previously used.
Our deep learning model is able to identify:
These insights provide compliance teams with much richer, smarter and more informed views of risk, empowering them to spot sophisticated laundering schemes and hidden financial crime networks.
A human member of the compliance team is then able to investigate further, safe in the knowledge that the due diligence has been completed beforehand.
In a regulated industry, black-box solutions won’t suffice. In accordance with the EU AI act, any AI system used in credit scoring and fraud detection is subject to stringent requirements.
And this is why our suite of AI solutions offer as standard, everything needed to be explainable and auditable. We embed explainability into every AI-generated alert, offering clear, plain-language justifications and visual tools like link analysis and behavior charts.
An example of this:
Before deployment, we provide comprehensive documentation outlining the model’s design, methodology, and intended use.
During an in-depth pre-deployment analysis phase, our data scientists run simulations using the bank’s historical data, fine-tuning the model to align with the institution’s specific risk profile and operational realities.
This process ensures the bank has a clear, upfront understanding of how the model will perform in day-to-day scenarios, fostering trust and accountability from day one.
As AI capabilities continue to evolve, the next major leap lies in agentic AI.
These are intelligent systems that are capable of acting as digital compliance assistants and operate beyond simple question-answering. They can ingest multiple large data sources and use third-party applications to independently answer your queries, analyzing challenges, developing strategies and executing tasks.
In the world of compliance this could look like:
Imagine an AI agent being alerted by the transaction monitoring system after a particular entity is flagged.
Instantly, it initiates a comprehensive investigation, gathering and synthesizing data from both internal and external sources. Within moments, it produces concise, coherent, and actionable insights, enabling the investigator to make a well-informed decision about whether the entity’s activity is genuinely suspicious.
The agent doesn’t stop at surface-level checks. It can autonomously review the outputs of related rules and models, analyze historical alerts, and assess transaction patterns over time. Simultaneously, it scours external data sources such as news articles or public databases to uncover any additional context that could inform the case. The result is a thorough, context-rich narrative that brings clarity to even the most complex scenarios, saving valuable time and effort for human investigators.
When it’s time to file a Suspicious Activity Report (SAR), that too can be just a click away. The agent can generate a detailed and well-structured write-up, incorporating all relevant findings and insights, streamlining the reporting process while enhancing its quality and completeness.
All from a single user query.
Agentic AI will free up human officers, allowing them to transition into strategic oversight roles. They can then use their expertise for high value decision making rather than time consuming reviews.
It promises to revolutionise the world of compliance, allowing banks and institutions to work with new found speed, precision and scalability.
Agentic AI is closer to reality than many think and we are already laying the foundation.
We’ve already embedded Large Language Models (LLMs) into key compliance workflows, enhancing sanction screening and detecting trade-based money laundering risks such as over- and under-invoicing. For example, we’ve built a lightweight AI agent capable of browsing the web to validate the market pricing of goods and services, an early demonstration of autonomous, real-world decision support.
But this is just the beginning.
By the end of 2025, we will launch a fully capable agentic AI copilot designed to support investigators across sanction screening, AML, and KYC.
This next-generation assistant will allow compliance teams to interact with the AI through natural language, enabling it to retrieve relevant data, summarize alert histories, and provide contextual insights to support human decision-making.
Behind the scenes, we’re actively developing the core agent framework, validating use cases with clients, and conducting rigorous evaluations on real-world data.
Our focus remains on delivering transparent, explainable, and regulation-ready agentic AI that works seamlessly within existing compliance ecosystems.
Financial crime and regulatory complexity mean that banks and institutions can no longer stay static, they have to move with the times.
AI is the solution, it offers complete transformation over legacy systems and is the future of how institutions will approach compliance and fraud prevention.
Implementation does not need to be daunting either, through a phased, explainable, and data-driven strategy, Eastnets empowers institutions to evolve at their own pace while staying ahead of risk.
Compliance doesn’t have to be a burden. With the right AI strategy, it becomes a strategic advantage.
To find out how our Artificial Intelligence solutions can help you, speak with one of our experts today.