Money laundering and fraud cause billions of dollars in damage to banks every year. Traditional approaches to Anti-Money Laundering (AML) and fraud detection operate exclusively on rule-based systems to identify risky transactions and catch bad actors. However, criminals have proven themselves capable of exploiting these rules – easily bypassing the AML systems that banks rely on.
In addition to being exploitable, these rule-based AML systems often require large-scale manual efforts to sort through alert reports and determine actual threats vs. legitimate activities. This costs institutions time and money and leaves them vulnerable to errors and exposure to elevated levels of operational risk.
At swissQuant, we’ve developed an advanced AI-powered AML solution that leverages a novel machine learning approach and advanced data analytics to provide our clients with real-time fraud detection that tracks suspicious activities and generates alerts based on changes in behavioural patterns.
Flexibility is at the core of our product development strategy, meaning our solutions can be deployed as either standalone solutions or integrated into existing detection system and IT architecture. And, unlike rule-based implementations, our adaptive technology learns from data and detects novel fraud patterns.
To date, swissQuant has implemented fraud detection models at banks of various sizes throughout Switzerland. Our experienced quant development team builds and tailors advanced AI-based solutions which leverage both market-leading technology and years of functional banking and financial market expertise.
Download our AML fact sheet or contact us directly for more information.