Fighting Fraud In A Payments Landscape

Stealing a person’s hard earned money is nothing new. However, in today’s world of almost instant payments, the methods used by fraudsters for payment fraud have evolved. While the digitization of payments has made making financial transactions more convenient for consumers and financial institutions, it has also made detecting fraud transactions increasingly difficult. After all, instead of days, transactions worth millions can now be completed in a matter of mere seconds.

On average, 12 million transactions are conducted via debit card in Canada each day. This makes Canadians the highest users of debit cards and hence puts the group at high risk for payment fraud.  Most Canadian banks offer zero liability fraud policies and in 2017, the banks reimbursed Canadian customers with over 700 million dollars incurred as a loss due to debit or credit card payment fraud. Thus, the need for fighting payment fraud is very apparent.

Common Types of Payment Fraud

With payments turning digital, fraudsters no longer need to be in the same geographical vicinity to steal a person’s money. Identity theft is the most common form of payment fraud. Given the ease with which information about a person is available on social media platforms, criminals can easily impersonate an individual and hack into their bank accounts.

Once they have access to the individual’s card details, they can use it for card-not-present transactions on online platforms. Other common types of payment fraud include false invoicing which relies on an individual not paying adequate attention to invoice details, scam emails and phone calls. According to a survey, up to two-thirds of all payment frauds involve deceiving an individual into disclosing their security details.

Fighting Fraud

As the payment industry evolves and the digital economy facilitates faster transactions between individuals, businesses, and banks, fighting payment fraud has become a priority. Existing security measures such as chip-based cards have already significantly reduced the extent of card-present fraud. Banks and financial institutions also advise consumers to follow simple strategies such as:

  • Inform suppliers after invoices have been paid
  • Verify requests for changes to supplier’s account details
  • Remove personal information from social media platforms that could be used to hack into your account
  • Do not divulge account and security details to anyone

In addition to this, machine learning technology and KYC norms also play an important role.

Two-Step Authentication

In many cases, thieves can conduct fraudulent transactions by hacking into a smart device. Introducing two-step authentication makes conducting these transactions more difficult as long as the second step of authentication is through a different mode. One-time passwords sent to a mobile number or email address are the most common form of two-step authentication.

Biometric Authentication

Biometric authentication uses an individual’s unique physical characteristics to verify an individual’s identity as an additional security layer. Fingerprints, voice recognition, iris recognition, and face recognition are the most common biometrics used. Biometric systems are difficult to fool and are easily accessible. Embedding biometrics in payment systems ensures that transactions are being made by the person holding the account and not by an imposter.

Stringent Know Your Customer (KYC) Procedures

A strong digital identity makes financial transactions secure without compromising on convenience. For this, organizations must have access to reliable data that can be verified across multiple sources. Once completed, KYC procedures must also be constantly updated. Accurate customer identification not only protects the consumers but also protects financial institutions from transactions involved in money laundering and thus protects their reputation.

Machine Learning And Behavioral Analytics

Machine learning uses historical data associated with an account and complex data analysis to understand patterns of legitimate payment transactions. Combining this with human insight, it can help identify and prevent potentially suspicious or unusual transactions that may be fraudulent. Neural networks and AI can also be used to spot suspicious or erratic card usage.

The Bottom Line

As financial institutions and criminals, strive to outwit each other, the combination of technology and human expertise will play a crucial role. Above this, it is also important for governments, law enforcement agencies and industry players to collaborate and work together to win the war on payment fraud.

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