Sygno, the provider of Automated Machine Learning (AutoML) transaction monitoring models, has reportedly joined the recent cohort of scale-ups that will enter the ING Labs 2022 Program.
During the 2022 program, Sygno will aim to bring its tech stack into ING’s transaction monitoring environment and assist the banking institution with combatting financial crime. As noted in the announcement, Sygno and ING will enter a co-creation cycle, beginning with models on automated alert handling.
Jonas Buyle, Director of Fraud and Cybersecurity at ING Belgium, stated:
“By now there’s no one left in #Belgium that hasn’t already received a dodgy SMS or sneaky e-mail in an attempt for #phishing. We’re about 11,5 million people in our country but in the end there are only a handful of #fraudsters that cause this societal problem whereas it affects many more. So I am really excited to try out with Sygno what we can learn from all of our good fellow citizens to catch the bad guys.”
Pieter-Jan Boiten, Head of ING Labs Brussels, remarked:
“With this year’s participating scale-ups, we focus more than ever on creating value and taking a leap forward in some of the most strategical topics for ING. Welcome Sygno to our ING Labs Brussels family.”
Sjoerd Slot, CEO and Co-founder, Sygno, added:
“Regulators and customers expect from banks to have efficient solutions in place to combat fraud and money laundering It is an honour to be selected as cohort partner and we are looking forward to help ING in becoming a data driven bank with our AutoML model generation and expertise.”
As noted by Sygno’s management:
“Fighting financial crime isn’t fair. Both your hands are tied. Criminals keep changing the game, while you have to play by the rules. Lots of rules. Meanwhile your business keeps accelerating.”
In order to keep up and comply at the same time “means adding layer upon layer of
complexity.” This can lead to “higher costs and ever more cumbersome processes, burdening your clients.” According to Sygno, this way of thinking “isn’t working, so shouldn’t we rethink the problem?”
The firm also noted that financial criminals are “always looking for loopholes to stay ahead of being detected. Normal people aren’t.”
The company asks, “so why base your approach on exceptions and not on the rule? When you focus on regular customer behavior, the anomalies clearly stick out.”
The added that this may sound simple, but it is “also very effective.” The firm also noted that you “drastically reduce false positives and increase true positives as previously undetected patterns now become visible.” So you can “identify the right cases faster, at lower cost,” the company added.
They also shared:
“Our automated machine learning technology generates detection models. Based on your own raw data and regulatory requirements. It deploys these models in your transaction monitoring system of choice. Because the value isn’t in the system, it’s in the detection models running on it. They enhance the monitoring system to better identify known and yet unknown financial crime.”
They further noted
“This makes everyone’s lives so much easier. Your case analysts can now spend their time on meaningful investigations. Your data scientists can get rid of their backlog and focus on other, more bank-specific risks. Your compliance team can explain these transparent models to regulators. Think white box, not black box.”
At Sygno, they claim to approach financial crime “from a clear-cut premise: most of your customers are not criminals.”
By looking at it this way, they “make transaction monitoring more manageable and effective” so you “can catch crooks, comply and be in full control.”