Successful US trials mean fraud technology will be used in the UK
HSBC is rolling out a real-time card fraud detection system in the UK following its successful implementation in the US.
The system will scan all HSBC’s UK card transactions and identify potentially fraudulent items in less than 30 milliseconds. In the US project, the number of transactions scanned for potential abuse increased by 87 per cent.
The bank aims to roll out the security measure for transactions involving more than 100 million credit or debit cards in more than 30 countries.
The system reviews HSBC’s card transactions alongside other changes in customer behaviour, and delivers a real-time decision to proceed or seek customer clarification.
The new system will help keep the bank ahead of the criminals, said HSBC head of group fraud risk Derek Wylde.
“The new system takes us a significant way forward in our fight against fraud,” he said.
The application builds on existing rules-based fraud detection to incorporate neural network analysis using patented advanced predictive modelling to determine if a particular transaction is fraudulent.
The biggest challenge with existing methods of credit and payment fraud investigation is the reduction in efficiency over time as fraudsters become aware of behavioural detection patterns.
The new system, developed with software provider SAS, constantly changes its detection models to keep the prediction and detection rates high.
The software also monitors non-monetary activity such as changes of address.
Secure banking and credit rests on three factors: user authentication, transaction authorisation and risk-based activity monitoring, said Forrester Research analyst Bill Nagel.
While the first two techniques are widely used, the third is still being developed.
“Risk-based activity monitoring addresses credit and payment problems because both forms of fraud are based on behaviour patterns,” said Nagel.
Greater losses occur through fraudulent credit applications than from criminals exploiting existing customer payment processes, said Nagel.
HSBC is rolling out a real-time card fraud detection system in the UK following its successful implementation in the US.
The system will scan all HSBC’s UK card transactions and identify potentially fraudulent items in less than 30 milliseconds. In the US project, the number of transactions scanned for potential abuse increased by 87 per cent.
The bank aims to roll out the security measure for transactions involving more than 100 million credit or debit cards in more than 30 countries.
The system reviews HSBC’s card transactions alongside other changes in customer behaviour, and delivers a real-time decision to proceed or seek customer clarification.
The new system will help keep the bank ahead of the criminals, said HSBC head of group fraud risk Derek Wylde.
“The new system takes us a significant way forward in our fight against fraud,” he said.
The application builds on existing rules-based fraud detection to incorporate neural network analysis using patented advanced predictive modelling to determine if a particular transaction is fraudulent.
The biggest challenge with existing methods of credit and payment fraud investigation is the reduction in efficiency over time as fraudsters become aware of behavioural detection patterns.
The new system, developed with software provider SAS, constantly changes its detection models to keep the prediction and detection rates high.
The software also monitors non-monetary activity such as changes of address.
Secure banking and credit rests on three factors: user authentication, transaction authorisation and risk-based activity monitoring, said Forrester Research analyst Bill Nagel.
While the first two techniques are widely used, the third is still being developed.
“Risk-based activity monitoring addresses credit and payment problems because both forms of fraud are based on behaviour patterns,” said Nagel.
Greater losses occur through fraudulent credit applications than from criminals exploiting existing customer payment processes, said Nagel.
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