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Great Payments Transformation

The data blows the whistle: Using analytics to reduce fraud in China’s payments ecosystem 

By Alessio Marinelli and James McKeogh, KPMG China


Standing on the cusp of a payments revolution, China’s banks and regulatory authorities are keenly focused on enhancing their ability to identify and react to financial crime.

reduce fraud


For regulators, the need to eliminate fraud has never been more acute. In part, this is because the internationalization of the Renminbi (discussed in the previous article in this series) is forcing China's  government to renew their efforts to remove counterfeit notes and tackle fraud in order to enhance the currency's reputation on the world stage. Greater understanding of fraudulent activity within the payments sector will also help the government in its fight against corruption and organized crime – two top priorities for the country's leadership.


For China's banks and payments processors, the ability to monitor, identify and respond to fraud will make or break their international expansion plans. Indeed, with banking regulators around the world now paying close attention to payments transaction activity i n order to spot rogue trading, money laundering and fraud, China's banks will need to meet, and where possible, exceed the compliance requirements of foreign regulators. Penalties can range from steep fines through to blocked acquisitions and reputational damage.

Stepping up the scope

Ask most banking executives and they will likely tell you that they already use analytics to spot fraud and other illicit activities. While this may be true, most only do so in a reactive way by reviewing suspicious activity or identifying anomalies in patterns – arguably once the fraudulent activity has already occurred.


Moreover, the use of analytics to detect fraud has, to date, largely been focused on the retail market where the risks are relatively well-known. Today, however, China's banks are starting to recognize the real and material risk of fraud or rogue activity in their trading and investment management spaces as well. This is much more difficult to identify: insiders generally have a clear understanding of the systems and controls in place to identify fraud and are therefore uniquely positioned to circumvent them. As a result, anti-fraud measures in this space must be flexible, adaptable and conducted in real-time in order to identify and interrupt fraudsters' new permutations and tricks.


This is where data analytics really proves its worth in eliminating fraud. Modern data analytics is not only capable of simultaneously conducting monitoring and alert processes in real-time across a massive volume of transactions. It can also adapt to changes in patterns and incorporate important external data. For example, today's systems are able to monitor a trader's communication across email, telephone, text, social media and messenger services to spot suspicious activity, and then correlate that against the trader's transactional activity. It can also reach across publicly-available data from other payments parties to flag potential occurrences of inter-institutional or international fraud.

Turning data into action

It will, however, take much more than simply implementing the latest data analytics solutions to reduce or eliminate fraud; it will also require banks to develop appropriate processes and responses to allow them to proactively manage the resulting prompts. The activities of Nick Leeson in the 1990s and Jerome Kerviel in the early 2000s all went unnoticed causing significant exposure. More recent incidents have been identified earlier, but the reaction time taken to prevent rogue trading is still poor and timely responses do not occur. It is one thing to identify fraud; it is altogether another to be able to turn those prompts into immediate and effective action.


Moreover, these controls must be efficient enough to operate in real-time, particularly given the rise of SEPA in Europe and Singapore's G3 payments mechanism, both of which have effectively eliminated the 24-hour turn-around time on transactions that had traditionally acted as a buffer for financial crime analysts and investigators.


The point here is that financial crime analytics is not just about data and information. It is also about speed, efficiency, effectiveness, and the ability to embed the system into operational risk and management processes. Consequently, given all the changes that are now underway in China's payments ecosystem, this seems like the perfect opportunity for the country's banks to build these robust, real-time financial crime responses into their new operating models.


What to expect at Sibos

Those attending this year's Sibos conference in Japan will undoubtedly see a frenzy of activity related to the China market, with scores of new Chinese players busy building their networks and hunting for partnerships. Foreign players would be well advised to come to Sibos with a clear view of the value that they can bring to China and a strong mandate from their boards for exploring and establishing partnerships with local players.


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