Sygno

Join our founder Sjoerd Slot tomorrow at CBA-Live in Washington DC by the Consumer Bankers Association with a panel on "Navigating the new era of fraud protection in banking?". Including Chris Como, Eric Kraus and Laura Kornhauser.

Proud to see Chartis recognizing Sygno’s “model-as-a-service” solution not only as a valuable enhancing solution for Transaction Monitoring, but especially giving a high score for model validation. Sygno #knowgoodcatchbad #transactionmonitoring #compliance #aml #regtech #modelvalidation

Effective Transaction monitoring is no longer possible without Machine Learning In a changing landscape, effective money laundering monitoring has become more and more complex. How are you going to meet your responsibilities as a gatekeeper in the financial sector and make sure you can continue to do so? DNB (Dutch Central Bank) is clear regarding their expectations: “Machine learning can also improve transaction monitoring. Banks deploy transaction monitoring systems on a large scale to detect anomalous transactions(43). Although some banks are experimenting with more advanced models, these currently tend to be relatively static rule-based systems. The predictive ability of these systems is relatively limited, meaning they also produce many false positives and false negatives. Rule-based systems rely on threshold values (e.g. a quantity of cash deposits) for certain criteria. When these are exceeded, the system automatically designates a transaction as anomalous. According to the EBA44, using machine learning for this purpose would result in improved transaction analyses, thus increasing the effectiveness of transaction monitoring and reducing the burden on customers and institutions. Moreover, these models are better able to cope with a more dynamic environment in which the financial system is in an ongoing state of development while also facing a constant barrage of threats. Self-learning components can help keep transaction monitoring systems up-to-date on a real-time basis.”  (source: https://lnkd.in/eXrAApxr ) Explainability of the outcomes and operation of artificial intelligence (AI) applications is an important condition for safeguarding consumer and society confidence in AI applications, especially in the financial sector. That is why the University of Applied Sciences Utrecht has started the FIN-X project- Towards a meaningful explanation of AI systems. Several partners are participating in this research, also DNB and Sygno are participating in this important project. (https://lnkd.in/ecxKwEag ) Sygno is happy to help to take the next step and implement our machine learning AML models in your current transaction monitoring system. 

Yesterday Sjoerd Slot (CEO Sygno) and Mandy Lablans (CFO/COO Sygno) welcomed Jeroen Ekkel and Peter van der Steege at Sygno’s office to festively complete our successful financing process with Rabobank! Happy and proud to say that Startup & Scale-up banker, Jeroen, together with SME Banker, Peter, helped us through the onboarding and financing process. Happy to be working together to help Sygno take the next step in the scale-up process!    Sjoerd Slot Mandy Lablans Jeroen Ekkel Peter V. Roel Reijnen Maarten Derks

Effective continuous Fraud and/or Money laundering detection - business rules plus anomaly detection: 1+1=3! Implementing and optimizing business rules in combination with anomaly detection can be challenging, but is unavoidable if you pro-actively want to meet regulatory requirements. Learn more in our latest insight! https://lnkd.in/e8v3kjh2

In the podcast How to Lend Money to Strangers, our CEO and founder Sjoerd Slot discussed the necessity for financial institutions to validate trust in almost every process, to ensure their good customers can do their business. This aligns perfectly with Sygno‘s #knowgoodcatchbad approach in #transactionmonitoring. 

Interesting article, also relevant because this one doesn't forget to mention: "Does this consider elements like appropriateness of system calibration". In addition, good to emphasize that there is a system agnostic #ai and #machinelearning solution that works with the #transactionmonitoring systems that #banks and other #financialinstitutions already use. By delivering automatically generated models for #aml and #frauddetection, we support our clients by making their #transactionmonitoring systems and processes more efficient. #sygno #knowgoodcatchbad. https://lnkd.in/eyt9KjvC

In leading US banking publication American Banker our CCO Karin Schreiber argues that the banking industry is ready to turn inwards to adopt a new approach towards risk. From preparing against economic shocks to combating financial crime, banks and financial institutions should make use of the vast data capabilities they have and focus on what they know. Instead of chasing the unknown ever-changing patterns, Machine Learning solutions have reached a level of marketability that should pave the way for effective adoption in highly regulated functions such as compliance and anti-money laundering. However, #regulators & #lawmakers are also crucial to take along this important momentum of artificial intelligence.    #BankThink #AML #BlackSwans #Risk #Regtech #MachineLearning #FinancialCrime #transactionmonitoring #algorithms #transparency #frauddetection #compliance #artificialintelligence #usbanks #americanbanker https://lnkd.in/eCPrtTYX