Combat Financial Crime with AI

1. The EU AML package, along with rising requirements for documentation, traceability, and risk analysis, is increasing operational pressure on banks, insurers, and financial service providers.
2. Compliance professionals are hard to find. At the same time, research, analysis, documentation, and case handling create a high level of manual effort. Skills shortages and cost pressure are therefore increasing the need for automation.
3. Rule-based software is the stable foundation of modern compliance systems. However, it often reaches its limits when dealing with unstructured information, complex relationships, and large volumes of data. AI agents can provide targeted support here — for example, in adverse media research, transaction histories, investigation processes, or regulatory documentation. 

In compliance environments, specialized AI agents are particularly relevant when they operate within clearly defined processes, roles, and permissions. 

They support compliance teams with time-consuming tasks such as research, analysis, and documentation. At the same time, governance, traceability, and human-in-the-loop processes must remain in place. 

The best foundation for this is the combination of regulatory standard software, such as ACTICO Compliance Solutions, with specialized AI agents. The compliance platform provides governance, roles, permissions, review paths, and auditability. Within this framework, AI agents take over the preparatory work. 

Generative artificial intelligence models, or GenAI, are trained to create content. This includes text, summaries, images, or code, for example. One particularly well-known type is the large language model, or LLM, known from applications such as ChatGPT by OpenAI, Anthropic Claude, or Google Gemini. 

An LLM is specialized in processing and generating human language. It can evaluate unstructured information such as news, documents, or free text, and generate natural-language texts such as summaries, draft decisions, or documentation.

Agentic AI systems go one step further. They combine generative AI, often LLMs, with structured process steps, roles, permissions, clearly defined subtasks, control mechanisms, and system integrations. This control layer is often referred to as the agent harness. 

If modern AI is the engine, then the agent harness is the rest of the vehicle: steering, brakes, and navigation. It turns a language model into an agent that can act in a controlled way. 

Many discussions around AI agents focus on large models such as OpenAI ChatGPT, Microsoft Copilot, Google Gemini, or Anthropic Claude. 

At the same time, specialized, controllable small language models and AI agents built on top of them are becoming increasingly important. They are particularly suitable for clearly defined regulatory tasks. 

One advantage is efficiency: specialized models can be significantly smaller and more cost-effective than large general-purpose models. They extend existing compliance platforms precisely where high manual effort or complex analytical tasks arise. 

ACTICO follows this approach: the controlled combination of regulatory standard software and specialized AI agents. 

An API, or Application Programming Interface, is an interface that enables software  to exchange data, functions, or services. 

APIs are increasingly becoming the central integration layer of modern compliance architectures. Standardized and controlled interfaces make it possible to integrate AI agents into compliance processes in a traceable and secure way. 

ACTICO Compliance Solutions provide domain-specific APIs through which AI agents can support regulatory processes. This allows them to be integrated in a controlled way into existing customer screening, AML, or case management processes.