It’s a basic rule in data science: when precision and accuracy are required for fraud prevention, make sure you choose the algorithm appropriate to a bank’s data sets and needs. A complex algorithm ...

Software that focuses on transactions rather than staff behavior to spot and stop internal fraud avoids the problem of personalizing fraud risk, which can demotivate staff and put off new recruits. ...

When NetGuardians recently brought together some of Europe’s top fraud specialists from major banks and organizations, the resulting discussion was open, frank, and insightful Covid-19 has changed ...

Banks running fraud-prevention software that incorporates collective artificial intelligence can cut fraud monitoring costs by 77 percent, helping them meet new regulations efficiently and ...

The widespread use across Asia of mobile phones, m-banking and payment apps has left consumers particularly vulnerable to fraud. Financial services providers in the region must ramp up investment in ...

For a number of years now, financial institutions have depended on big data technology to keep business ticking. Top use cases include high-frequency trading, risk management and regulatory ...

An estimated $67 billion was lost to banking fraud in 2014, with nearly 75 % of it being internal. Most alarming, the majority of this fraud remains undetected.