Steward Bank Selects NetGuardians' Software To Fight Financial Crime

Zimbabwe-based Steward Bank has selected NetGuardians' software in its fight against cyber-fraud.

Steward Bank is NetGuardians’ first customer in Zimbabwe.

NetGuardians’ acclaimed anti-fraud solution will plug straight into Steward Bank’s core banking platform – T24 from Temenos. As a Temenos Complementary Solution Provider, NetGuardians’ solution integrates with T24 by means of preset connectors, dramatically reducing implementation time and cost.

Steward Bank chose NetGuardians as its new cyber-fraud mitigation solution after rapid growth in customers, transactions and customer channels compromised the Bank’s ability to spot and block fraud in a timely manner.

NetGuardians’ financial-crime solution allows Steward Bank to continuously monitor in real time all transactions across all its channels, including ebanking, and mbanking. Suspicious transactions are blocked and alerts automatically sent to the appropriate staff for swift resolution.

Steward Bank CEO Lance Mambondiani said: “Digitization opened up new channels for the bank and helped us grow. We needed a more effective and proactive system to monitor the subsequent increase in transactions and complexity of the bank to prevent fraud. We picked NetGuardians because it is a solution made specifically for banks and is proven to cut fraud across all channels.”

NetGuardians CEO Joël Winteregg said: “By signing up with NetGuardians, Steward Bank will not only benefit from our real-time fraud mitigation solution, but will also become part of the NetGuardians’ global community, sharing fraud mitigation best practice. Together, they put Steward Bank at the forefront of fraud prevention, helping to keep its customers’ balances safe and its reputation sound.”

Cyber-fraud is a growing challenge for banks as fraudsters adopt increasingly sophisticated methods. Fraud and other forms of cyber-crime are expected to cost $6 trillion a year by 2021.

NetGuardians uses advanced analytics, dynamic profiling and machine learning to catch fraudsters before they strike. Its solution boasts dramatically higher rates of accuracy in correctly identifying fraudulent transactions and cutting the number of false positives (by 80% ). The result is a better customer experience and lower operational costs. Fraud management time is cut by 93%.