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Information is king
Why big data is a game changer for treasury
Daniel Yu 21 Sep 2017
With the rapid advances in technology, financial information has become more prevalent and easier to access today than it’s ever been before. From FX rates to stock prices people are able to get information instantly and efficiently act upon it.
The progress in technology in particular has had a profound impact on the treasury professionals of companies who often work with large sets of data to set corporate financial policies and decisions. Due to the volume of such data, many companies are turning to big data computing technology as a way to quickly make sense of the information and discover key financial trends.
 
According to consultancy firm NewVantage Partners’ Big Data Executive Survey 2017, 95% of participants mentioned that they had undertaken a big data project over the past five years. Moreover, the report found that almost half of surveyed executives considered their big data project as highly successful.
 
“There is technology available to enable businesses and end users to actually make sense of the data in order to drive metrics KPIs and decision making,” says Philip Pettinato, CTO at Reval. “Data processing has always been there but it’s always been in fixed forms you can now do more with the various types of data you have.”
 
In terms of significant data for treasury professionals, Pettinato shares that most of them are looking to spot any potential risk factors and develop longer-term cash forecasting for their company. “A lot of companies will tell you that their forecasting is only so good in the short term but as you forecast, reforecast and measure your actuals, you can use those historical situations to do better forecasting in the next round,” he explains. “That’s where big data analytics jump in. In many instances companies are actually over hedging their exposures by doing them individually. But when they aggregate them they can actually hedge them more accurately.”    
 
Ranging from better cash visibility to logical hedging strategies, big data could be viewed as cutting-edge solution that gives a treasury department better control over a company’s finances especially in situations with multiple bank accounts and lack of professional staff. 
 
However, in order to get there treasury departments need to make sure their ERP systems are able to effectively funnel data into a centralized big data platform. This can be a challenge for some companies due to the fact that some of their entities may not use the same system or follow the same financial procedure.
 
“Treasurers don’t always have the right platform in place to be ready to use this data. Most important is to get the right treasury platform that allows treasurers to create the efficiencies and transparencies into the data so they can leverage the data going forward,” highlights Pettinato. “Sometimes there is a lack of understanding or a lack of appreciation of what else is needed.”    
 
Moreover, a common mistake companies make when approaching big data is looking at the information as a whole and studying what to measure. “Big data analytics isn’t about having a lot of data. Companies should instead figure out what their business problem is and solve for it using data,” notes Pettinato.
 
It’s a sentiment shared by Ng Peng Khim, head of institutional banking group technology at DBS Bank: “First, you need to know what data you have within your organization, as well as what is available in the industry. Once you have collected the data, it is important to set clear perimeters and objectives. Otherwise, you will get lost in the data,” he adds.
 
Alternatively some companies are utilizing their banking partners to provide significant datasets for them. Citi for example has its Working Capital Analytics tool which aims to analyze a company’s account payable process and find areas ripe for cost savings and efficiency enhancements.
 
DBS has its Working Capital Advisory Programme which like Citi’s platform reviews the financial supply chain for inefficacies and provides industry benchmarking services.
 
“We have conducted several experiments using algorithms to improve the predictability of cash flow projects and performance, we are in the process of developing them further as they have huge potential,” explains Ng.  
 
Conversation
Jennifer Lee
Jennifer Lee
managing director, head of large corporate, institutional banking group
DBS Hong Kong
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Conversation
Jennifer Lee
Jennifer Lee
managing director, head of large corporate, institutional banking group
DBS Hong Kong
- JOINED THE EVENT -
Exclusive roundtable
Unlocking the potential of sustainable supply chains
View Highlights