In an increasingly complex and digitalized world, fraud methods are becoming ever more sophisticated. At Enin, we work every day to stay one step ahead. Through targeted intelligence work and manual analysis of new events, we uncover patterns and signals that can indicate that a company is either already involved in disreputable or criminal activity, or is about to become so.
The interplay between human and machine in the fight against fraud
At Enin, manual analysis is still a core activity in the work of uncovering new fraud methods. Every day, our analysts assess events that are not necessarily picked up by automated models. That insight forms the basis for the continued development of our technological solutions.
When we pick up anomalies or unfamiliar patterns, our experts are alerted, and they in turn carry out an investigation and a qualitative assessment based on it. This investigative work lets us develop our tools further with new indicators. That is how a continuous learning loop arises between human and machine – where each side strengthens the other.
It is easy to assume that algorithms alone can identify fraud. But human judgment is still invaluable. At Enin, we combine data analysis with intelligence work done by people. Our analysts weigh up context, interpret signals and draw conclusions that go beyond what machines can detect on their own. This lets us turn hits from uncertain models with many false positives into solid models that can actually be used.
Early warning – before the damage is done
The goal is of course to be able to anticipate likely fraud before it happens, so that it can be stopped. That is not always possible, but in most cases of serious corporate fraud, it could have been stopped earlier if someone had connected the dots in time. That is exactly what we are trying to do.
By identifying trends and recurring traits in new, suspicious events, we can flag companies that have not yet done anything illegal, but that are highly likely to do so. This gives our customers in banking, financial institutions and the public sector a valuable early warning and a better basis for their decisions.
Knowledge sharing and continuous learning
We work not only to uncover fraud, but also to understand how it evolves. Every event we analyze gives us new insight that we build on. This is necessary because fraud methods change over time: old methods fall out of use, while new ones are systematically tested out by the fraudsters.
By systematizing our intelligence work, we build an ever better basis for decisions and an understanding of how fraud methods develop over time, and we can also pass that on to our customers so that they are better able to avoid being hit. We believe that sharing knowledge helps strengthen both society and our customers.
A fight we take personally
For us at Enin, this is not just about technology and data. It is about responsibility. Every time we help prevent financial crime, we protect individuals, companies and the financial system. It is a fight we take personally, and seriously.
