The results are already paying dividends.

Whether it’s consumer banking, trade finance, audit, or HR, Singapore-based DBS has led the way in transforming its operations via data analytics in order to make better-informed decisions, distinguish trends and stay at the top of its game.

“Over the past few years, DBS has been embracing various forms of digital technology to help simplify and improve the customer experience,” says David Gledhill, group chief information officer at DBS. “Some examples of these technologies include cloud computing, artificial intelligence and data analytics.” Big data technologies with open source programming and integrated analytics allow the bank to glean stronger insights to improve decision-making and have a deeper understanding of customer behaviours and transaction flows.

Challenging norms in the consumer space

DBS has pushed the envelope in using data analytics to improve efficiency in consumer banking. One key example is how big data has completely changed the bank’s ATM system in its home market.

The bank’s ATM network is one of the most heavily utilized in the world, with more than 25 million transactions per month. DBS has leveraged its data analytics to understand the patterns of ATM cash flow and to predict when ATMs would run out of cash, resulting in almost zero cash-outs. A secondary effect has been the phasing out of the bank’s outsourced cash-replenishment service. As a result of the ATM evolution, time spent on ATMs has been cut by about 25 percent.

Trade Finance taken to the next level

The push into big data has also helped reduce errors in trade finance documentation. A traditionally paper-intensive industry involving manual processes, trade finance controls rely on the bank’s understanding of their clients, nature of transaction, documentary financing and credit monitoring.

To reduce trade anomalies, DBS has collaborated with A*Star, Singapore’s largest ICT research institute, and fintech company Cloudera, one of the leading providers of data management and analytics platforms. Through this partnership, they have created a groundbreaking program that detects abnormal trade finance transaction activities. A first for a Singapore bank, the system makes use of data analytics to detect fraud anomalies through transactional trends, red flagging odd trade flows for further analysis. It makes use of a broad range of trade data, including shipping data.

Applying big data to Audit

By applying big data innovations to the bank’s auditing processes, DBS can detect poor controls at branches and spot high-risk branches. Armed with over four years of data, the bank developed a system to find factors associated with mismatched cash balances against branch transactions. These findings help alert the teams and they are able to intervene at an earlier stage, as well as improve staff training. To that end, 15 per cent of branch audit processes have been automated.

Data-diving in the HR pool

The bank set up its Human Capital Analytics team within HR to evaluate trends and determine risk factors for early employee attrition. Some of these factors include poor performance, taking medical leave in the early months of employment and missing training courses. The data is then used to prompt managers to engage these employees early and provide more guidance. This initiative has lowered the attrition rate from 27 percent to around 18 percent.