FRAUD PREVENTION & AML COMPLIANCE
Q. WHEN SHOULD FINTECH COMPANIES BUY A PROVEN SOLUTION WITH BUILT-IN ML AND AI CAPABILITIES VS BUILD THEIR OWN?
» The decision to buy a proven financial crime prevention solution versus building one in house is one of the most consequential choices a fintech company can make. Too often, firms underestimate the complexity, cost and long-term obligations associated with building their own AI-enabled fraud and AML infrastructure.
Building in house can seem tempting, especially for engineeringdriven companies or those wanting complete control. But in reality, custom-built systems frequently exceed budgets, miss deadlines and create ongoing maintenance burdens that fall disproportionately on fraud and compliance teams.
“AI will force a profound shift in governance, sovereignty and compliance”
Ivan Stefanov, CEO & Co-founder, NOTO
These projects require far more than engineering capacity: they demand deep domain expertise, continuous model tuning, data governance, explainability controls and constant upkeep as criminal behaviour evolves. Crucially, building in-house is a permanent programme, not a one-time build.
Fintechs should reserve in-house development for areas that create direct competitive advantage like core product features, payment flows, customer experience and embedded financial services.
Fraud and AML infrastructure, by contrast, is a highly specialised discipline that requires dedicated tooling, governance and ML capabilities that mature vendors have refined over many years.
A proven platform with built-in AI and machine learning is the better choice when:
• You need fast implementation and measurable impact
• You operate at scale and require real-time decisions with sub-100 milliseconds latency
• You must meet regulatory expectations for explainability, auditability and continuous monitoring
• Your teams lack the capacity to maintain models, handle drift or build robust governance frameworks
• You cannot afford the risk of overrun, downtime or technical debt
96 February 2026