Fighting Cybercrime with data analytics

Today’s consumers and businesses require payment methods that are fast and convenient, no matter what channel they are using. However, as domestic and international payment networks evolve and payment channels progress to meet these growing demands, Financial Initiations (FIs) face an increasing variety of fraud risk and techniques. This is becoming ever more prevalent for …

by | September 22, 2016 | Fiserv

Today’s consumers and businesses require payment methods that are fast and convenient, no matter what channel they are using. However, as domestic and international payment networks evolve and payment channels progress to meet these growing demands, Financial Initiations (FIs) face an increasing variety of fraud risk and techniques. This is becoming ever more prevalent for online payment channels, with reports of cyber fraud attacks making headlines on a regular basis.

Cyber fraud is constantly adapting and looking for the path of least resistance, and the path to increasing the value of fraud. When cyber fraud infects the world of high-value global payments, it poses a material threat to the stability of financial institutions and the global financial system itself.

SWIFT’s recent warning for members to demonstrate greater security awareness has raised the profile of payment fraud, placing high-value cybercrime once again in the spotlight. The $81 million cyber theft from the Bangladesh central bank account at the New York Federal Reserve Bank in February wasn’t the first fraud perpetrated and won’t be the last. Cybercrime is a real threat and financial institutions and corporations need to take action against it.

Analytic models

FIs and corporations of every size can take steps to help protect themselves, and more importantly, their customers who demand first class service and security. One way to achieve this is through the deployment of technology and advanced analytic models that are specifically designed to detect payment fraud. The inherent value of payment data supplemented with critical fraud tags is an extremely effective tool when looking at how to combat payment fraud.

In order to detect fraud patterns, organisations need to understand customer behaviour and their typical payments activity as well as previous fraud patterns and the outcome of previous investigations. For example, knowing the frequency of transactions, beneficiary history, time of day, velocity and size of the payments typically made, as well as which channels a customer typically uses is vital. Using technology to collate and analyse customer data, enables FIs to have all this information and creates a complete picture of what typical behaviour look like for each one. Hence, if a transaction falls outside of what is deemed normal behaviour for a particular client, the fraud analytics team can be notified in real-time and carry out further investigations.

Intercepting electronic transactions in real-time means that an organisation can stop fraudulent activity before the transaction has been made. This prevents the need to combat fraud after it has occurred and also means that the customer isn’t inconvenienced and avoids becoming a victim of cybercrime. Accurate detection of fraud through the use of data analytics means customers receive a better experience and are therefore more likely to remain with that institution as they can trust them to keep them safe.

Leveraging consortium data

To fully utilise the power of data and analytics, they can be used in a predictive consortium (subject to approval from the contributing FIs) to deliver even more accurate detection and more powerful protection. This requires organisations from a number of areas – FIs, payment companies, fintech providers, etc. to pool their data on legitimate and fraudulent electronic payment transactions, to help determine fraud patterns and flag potentially fraudulent activities based on similar characteristics.

A centralised capability collating data means data goes beyond a single customer’s data and looks at broader patterns of fraud. By bringing a number of companies together, a wider spread of fraud data can be detected and any nuances and overlays of fraud can be tracked and analysed. FIs can then better understand instances of fraud and use this information to help defend against future cyber-attacks.

By working together across geographies organisations can bring business and customer data from around the world together to provide a larger data set. The richer that pool of data, the more informed analytic models will become, therefore leading to more knowledgeable decisions on fraud prevention. This also means that data can be looked at through the lens of a particular industry. Fraud indicators derived from investigations of retail customers may differ from those of commercial customers, thereby enhancing the level of detail and knowledge in each industry.

Be prepared

With the threat of cyber fraud being ever present, it is vital that financial institutions prepare themselves for any possible situation. Taking a holistic, data-driven approach to combating cybercrime is required to offer the most robust defence. Leveraging historical transactional and non-transactional data and the outcome of previous investigations, to inform an analytic model, will help manage fraud risk.

Today’s banking customers demand services that fit seamlessly into their fast paced lifestyles and completely protect them from fraud. They expect fast, safe and reliable banking services, no matter what the payment channel they are using. FIs must meet these demands and stay one step ahead of cybercrime. By leveraging analytical protection methods which stop fraudulent transactions from even being processed, customers remain unaffected while FIs also stay one step ahead of cyber fraud. 

By Andrew Davies, VP, Global Market Strategy, Financial Crime Risk Management, Fiserv.

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