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Data downpour

Banks need experts to make sense of flood of new information

It's a given that your bank probably knows a lot about you. Whenever a person opens a bank account or makes an application for a product, they provide personal details. such as their age, marital status, address and telephone number. On top of that, most banks will also have a good idea of clients' financial history and trends, such as income, purchase behaviour, risk appetite and spending propensity. They would also be able to predict possible fraudulent transactions. Based on this, banks calculate an individuals' current and potential profitability.

What has changed is the rise of the internet and social media, which has provided financial institutions with access to more information about their customers than ever, says Andrew Pitcher, senior vice-president and general manager for financial services and strategic industries at SAP Asia-Pacific Japan. These are some of the factors behind the phenomenon known as "big data" - a topic which applies to any massive collection of information, but which is of special interest to the banking and financial services sector due to the sheer volume of data it collects.

For banks, the modern challenge is to make sense of the growing mountain of information available for meaningful decision-making. They need to upgrade their computer systems to stay ahead of the information avalanche. For example, Pitcher says many banks still do not possess real time processing, or have it only in some business lines.

But just as important is the need to upgrade talent to match the evolving information landscape. One way is through appointing chief data officers, who are accountable for the how and where that data is captured, as well as how it is used. Typically, this senior manager creates a vision for data and its management.

"The trend is also to move away from IT programmers to managing the data on a business-analyst or data-scientist level - people who can use and extract information from the data to produce real business insights which can translate into action," Pitcher says.

He adds that while big data jobs have become less labour-intensive as a result of the move towards analysis, greater value has been created for organisations as a whole. "You could argue that the number of people who generate data-related insights could potentially be 20 or 30 per cent less than it used to be, but the value created is probably 50 to 80 per cent more, so you're actually producing a lot more with a little bit less," he says.

Looking ahead, Pitcher says that while big data has historically been used to manage risk, regulatory compliance and profitability, the financial services institutions which are best able to harness its growing power are those able to use it to improve customer centricity and, ultimately, the quality of living. The convergence of mobility with big data has empowered front-line banking personnel in servicing clients.

Stanley Lam, managing director of SAS Hong Kong, says that while Hong Kong's banking industry is conservative in nature, there has been a lot of recent interest in taking so-called "unstructured data" - such as call centre recordings - and transcribing, converting, and analysing it to generate useful information.

Lam says local and international banks in Hong Kong are continually on the lookout for data analytics talent. Most are typically positioned in customer relationship management roles. "But if you look at the banking sector overall, there's isn't a lot of hiring activity going on at the moment, so in terms of volumes it might not be all that noticeable," Lam says.

Pallavi Anand, director of recruitment firm Robert Half in Hong Kong, says a company survey found that one in five financial services industry respondents said they planned to leverage big data to develop strategy and boost growth. Meanwhile 13 per cent said they were planning to invest in IT infrastructure.

"As big data adoption increases steadily, there's a growing demand for business and data analysts. Data professionals can help front-, middle- and back-office operations, but the focus in Hong Kong has been on the latter two," Anand says. She adds that those with a strong maths and statistical analysis background and a familiarity with newer statistical programming languages stand to benefit.

Mark Enticott, Hong Kong managing director at recruitment firm Ambition, says that while there is interest in big data among financial services firms, many banks seem to have a wait-and-see attitude on hiring for now. "It's something that will be on the agenda and grow as we move forward, but often as trends happen the conversations tend to start first before recruitment takes place," he says.