Atfinity's AI-Powered Rule Engine
At the heart of Atfinity’s software is our rule engine, that applies structured logic and decision-making rules for different banking processes.
However, unlike a traditional rule engine, Atfinity utilises AI to infer rules from the desired outcome. This means that users do not have to manually create process flow charts, adding to Atfinity’s ease of use, adaptability, and implementation speed.
Rules are authored using a central configuration tool (our no-code studio) and versioned for tracking. This ensures consistent, auditable execution across use cases like customer onboarding, KYC/KYB, client lifecycle management, and loan origination. Teams can simulate and test rules before launch to ensure compliance and expected outcomes.
At the heart of the engine lies RuLa (Rule Language for Atfinity); a domain-specific language that supports conditional logic (if‑then, case and switch), filters (where), loops, and rule chaining. RuLa enables rules to reference structured data objects like legal entities, beneficial owners, or document submissions, defining exactly how they should be assessed or transformed.
Related reading: Atfinity's no-code solution explained.
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Examples
During client onboarding, a bank needs to determine whether Enhanced Due Diligence (EDD) is required. A RuLa rule is configured to evaluate attributes such as country of registration, annual turnover, and whether any beneficial owner is a politically exposed person (PEP).
As the relationship manager inputs data via the user interface, the rule engine evaluates the information. If the client is registered in a high-risk country and meets the turnover threshold, the rule automatically triggers additional EDD questions, initiates a World-Check screening, and generates a risk report.
All of this is configured declaratively, without custom code, and applied automatically as regulations evolve.
FAQ
How does Atfinity's AI rule engine differ from traditional business rules engines?
Traditional business rule engines rely on predefined workflows and static conditions. In contrast, Atfinity’s AI-powered rule engine infers workflow steps based on desired outcomes. It adapts dynamically, deciding which steps to display, which integrations to trigger, and which data to collect; all at runtime, and without custom code or separate deployments.
How does Atfinity’s AI-powered rule engine perform compared to legacy systems?
In most of our case studies, our rule engine has been about 80% faster to configure than our clients’ previous system for processes such as onboarding. Additionally, staying compliant has been made drastically easier and faster.
How does Atfinity’s rule engine handle complex regulatory rules and decision logic?
Atfinity’s rule engine addresses complexity through RuLa, which supports conditional logic, filters and even custom functions. Rules work with hierarchical data models, such as client structures or ownership hierarchies, and can trigger external services like KYC or screening tools based on input. This architecture ensures that sophisticated compliance workflows are modeled accurately and applied consistently.
