FRAUD PREVENTION & AML COMPLIANCE
To help institutions combat financial crime we deliver speed( by having the tools to react quickly to new threats) and complete control. With NOTO, teams can map any data in any format, orchestrate risk signals from multiple sources and deploy new rules and models in minutes without relying on external development.
This flexibility allows organisations to evolve their risk strategy at the same pace as emerging threats.
NOTO unifies fraud prevention and AML into one ecosystem. This creates shared intelligence, centralised case management and a holistic view of customer behaviour and risk. Instead of juggling separate tools, institutions gain a single powerful platform that reduces operational complexity and improves decision accuracy.
Ultimately, our mission is to help organisations stay ahead of financial crime while giving them the confidence, transparency and agility needed to grow safely.
Q. WHAT KEY DIFFERENCE BETWEEN AI AND MACHINE LEARNING SHOULD FINANCIAL INSTITUTIONS UNDERSTAND?
ยป AI and Machine Learning( ML) are often used interchangeably, although the terms usually refer to different parts of a spectrum.
AI is a general discipline concerned with creating machines that mimic human cognition, such as solving grand scientific problems or autonomously navigating unpredictable environments while strategically striving to achieve a given goal.
Machine learning is a narrow subfield of AI that uses mathematical models that self-improve at solving a particular task by incorporating data.
Large Language Models( LLMs) are widely labelled as AI, even though they are still far from actual human cognition. The main difference between AI and ML lies in model complexity, associated execution speed and explainability.
Classical ML models excel at learning patterns from vast amounts of tabular data.
94 February 2026