Anti-fraud: The £3.89 trillion question

By Shane O’Neill, Horizon8

As online banking and commercial activity continue to rise at an almost exponential rate, so too do the opportunities to commit fraud. The global cost of fraud is a staggering £3.89 trillion, with a 56% increase in the last ten years, according to The Financial Cost of Fraud 2019. Fraudulent transactions impact consumers and merchants to the tune of billions, but banks take the biggest financial hit. 

Across the industry, there is little optimism as the costs continue to mount. KPMG’s 2019 Global Banking Fraud Survey says fraud costs are increasing faster than fraud risk management spend and suggests a radical rethink is required. Meanwhile, PWC’s Global Economic Crime and Fraud Survey describes fraud prevention as a never-ending battle where every dollar invested saves two when a fraudulent incident occurs.

It’s clear that as legacy banks undergo digital transformations and challenger banks arrive on the market, it’s crucial to keep fraud prevention at the heart of digital strategies. But with the eye-watering costs and effort involved, many banks and financial institutions are still holding back from making the substantial investments their anti-fraud efforts require. The types of fraud that are on the increase include identity theft and account takeover, cyber attacks, card not present fraud and authorised push payments scams. Surveys suggest that cyber attacks are the number one concern for banks.

KPMG reports that Open Banking is likely to be a major challenge in fraud risk, by shifting the ownership of account information from financial institutions to customers. It enables customers to share their account and transaction data with third parties. The technological innovations arising from its introduction are likely to lead to new channels for customers to do business. The potential for fraudsters to gain increased insight into a customer’s profile and behaviours increases the need for ever more sophisticated security and anti-fraud solutions. June saw digital banking app Revolut offer Open Banking services to its one million customers in Ireland, allowing them the opportunity to connect multiple accounts from major Irish banks so that customers have increased visibility of their day-to-day spending.

While the opportunities to commit fraud are becoming more widespread, the technology available to detect and combat it is also becoming more advanced. AI and machine learning are set to become the forefront of anti-fraud strategies. These technologies mean that algorithms can act in real-time to track evolving behaviours and allow for the development of dynamic anti-fraud modelling. While static rule engines provide a good degree of protection,  being able to incorporate machine learning models is justifiably becoming more popular.

As fraudsters become increasingly sophisticated, it is essential that banks and other regulated institutions do the same. Technology has a role to play in predicting and preventing fraudulent activity, but leadership teams must step up and recognise the need for its implementation.

Case study: Payment Fraud Prevention at UnionPay

UnionPay handles over $17 trillion worth of transactions annually. It is the world’s largest card processing company and it operates in 174 countries. UnionPay wanted to prevent fraudulent transactions at the time that a card was presented for payment. The organisation wanted to significantly improve their anti-fraud capabilities by preventing fraudulent activity immediately with a real-time detection and prevention solution.

Horizon8 leveraged its real-time data streaming analytics platform, known for its high-capacity, high-speed, and low latency capabilities, to deliver the solution. The solution uses a highly configurable rules engine to analyse data in real-time, allowing anomalies and outliers to be detected instantaneously.

We set up fraud detection models in the rules engine, which observed spending behaviours and patterns of cardholders. We identified scenarios and use cases and created over 200 dynamic models to detect fraudulent activity. The solution was easy to integrate within UnionPay’s infrastructure and operating environment.

In the first year of using the solution, UnionPay was able to prevent $million’s in fraudulent transactions. Horizon8’s valid8 Anti-fraud product offers clients unparalleled capability, real-time processing  and allows the development of dynamic anti-fraud models that is at the vanguard of financial crime solutions.

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