Why big data is a valuable treasury asset

What will it take to strengthen existing treasury infrastructure and technology set-ups? Data, Lesley Meall explains – more and more of it

The world in which we live and work is driven by data, in increasingly large amounts.

Billions of digital devices, objects and software applications are generating, capturing, exchanging and storing quintillions of bytes of data every minute of every day.

Our creation and consumption of data has become so vast and ubiquitous that the label ‘big data’ now seems like a misnomer; perhaps it always was (see ‘Why big data is a big deal’, below).

With each day that passes, it gets more difficult to draw bright lines around big data and other technologies, such as cloud, artificial intelligence (AI), machine learning and analytics, as they become more entwined and embedded into new and existing products and services.

 Specialist tools can automate the collection of vast amounts of data from a multitude of sources 

Behind the buzzwords and hyperbole, there is simply lots of data and lots of technology-enabled services and tools – and some that have the potential to benefit treasurers.

Some of them already are: the use of big data to improve decision-making around FX goes back years.

Specialist tools can automate the collection of vast amounts of data from a multitude of sources; use algorithms to validate that it is accurate, timely and complete; aggregate it and then analyse it; and treasury teams are increasingly using such tools to confidently and quickly make more informed FX decisions.

Managing currency risk

Until recently, the treasury team at Sanmina (a multinational manufacturer with operations in 23 countries) relied on a manual, FX balance-sheet process to identify and manage its portfolio of FX risks: collecting spreadsheets from 30 entities and using these to consolidate forecasts and manually execute trades.

Then it modernised its currency risk and management process by combining various tools that exploit big data, analytics and cloud technologies.

Sanmina has integrated FiREapps for Balance Sheet with Hedge Performance, with the company’s existing programme (which included interfacing with Sanmina’s enterprise resource planning data collection), as well as FX hedge programme-management software from Capella.

This connectivity enables automated, straight-through processing and allows treasury to quickly compare multiple trade adjustments, see if its forecasting is off, and adjust hedges if needed.

Ronnie Dang, senior treasury analyst with Sanmina, says: “We select what we want to trade, push a button and the trade is processed immediately. The connection eliminates unnecessary steps, as well as the risk that something may go wrong with the trade along the way.”

This approach also means that the treasury team can spend less time gathering, transcribing and consolidating data, and more time analysing exposures and calculating forecasts.

Exploring the options

Other areas where treasurers may benefit from a combination of big data and other technologies such as analytics include the management and/or monitoring of:

  • assets and liabilities;
  • cash flow and liquidity;
  • counterparty risk;
  • peer and performance benchmarking;
  • supply chain finance;
  • fraud detection and prevention;
  • compliance with laws and regulations around anti-money laundering (AML);
  • combatting the financing of terrorism; and
  • financial sanctions.

In asset and liability management, for example, treasurers can dip into information on FX, market-value assumptions, mark-to-market, bank data, rates and spread.

They can then use analytics tools to gain insights that may help to boost asset and liability matching, minimise costs, support stress testing, interest rate risk management and fund transfer pricing, balance-sheet strategy and multifactor behaviour models for consolidation.

Another area where tools that rely on very large amounts of data can assist treasurers (and others) is around risks and compliance related to AML management and screening controls for sanctions.

“I’ve not come across any violations of sanctions, but it’s a big thing these days, especially when you are dealing with certain jurisdictions where there could be concerns,” says Sunil Boorman, vice president and assistant treasurer with the learning company Pearson.

There are various options. ComplyAdvantage, for example, combines AI and machine learning with vast amounts of data from numerous sources – such as sanctions watch lists, politically exposed people and millions of articles – which it then sifts through, to determine information that may relate to or benefit those in its proprietary database of people and companies that pose financial crime risks.

SAS Visual Investigator is a more extensive ‘incident and investigation management solution’ that combines and analyses vast amounts of data from an even wider variety of sources.

Among other things, it can link financial transactions to relevant information that’s lurking in reams of social media posts – and according to SAS, more than half of the transactions that are flagged by its Visual Investigator result in the formal filing of suspicious activity reports.

Following the money

The technologies that are often used in combination with the varied and voluminous amounts of data (we sometimes call ‘big’) can also help treasurers to more effectively undertake some of their core responsibilities.

They’re useful with cash-flow management – and even tools that are aimed at small organisations are exploiting cutting-edge developments to automate related processes and improve decision-making.

Finance director Dan Jarrett at media start-up Born Social has been able to rapidly build out a finance function powered by an ecosystem of cloud-based resources that includes an automated, ‘intelligent’ cash-flow solution (from Fluidly).

“It’s live and updated as cash comes in. As soon as I log into the dashboard, it spits out metrics such as aged debts and highlights actions for high priority or high-risk clients,” says Jarrett. So far, so standard.

Behind the scenes, something more unusual is happening.

By applying AI and machine-learning technologies and techniques that were developed for use with ‘big data’, the cash-flow software can use Born Social’s financial data to identifying and learn from the patterns, trends and anomalies it contains, and suggest actions that will help users to better predict and optimise cash flow – and because Fluidly is learning, its accuracy improves as time passes.

Talking to the oracle

As treasurers strive to strengthen working capital, secure liquidity, manage risk and simplify processes, big data can combine with other technologies to support more efficient and effective decision-making.

Where this takes us in the future remains to be seen – or heard.

Big data specialist Emagia Corporation has developed a digital assistant, Gia, which can act on the sort of instructions and answer the type of questions that might typically come from treasurers.

Just as you might ask Alexa or Siri questions in your personal life, you may soon be asking Gia, What’s the total cash received this week from the North America region? Why is our euro exposure higher this year? How will Brexit affect our cross-border sweeps? What will happen if we rationalise our bank accounts across Asia?

And when you get an answer that’s in any way meaningful, you’ll have big data technologies and techniques to thank for it.

Why big data is a big deal

There is nothing new about using computers to capture, store or analyse large amounts of data. Businesses have been doing this since the 1950s when interactive, general-purpose computer systems first became commercially available.

Nor is there anything inherently valuable about the very many data repositories that contain the very large amounts of data (we now call ‘big’): they are just collections of ones and zeros.

However, big data is at the core of a global digital ‘infrastructure’ that’s being created by mutually reinforcing technology trends.

Cloud-based computing resources and internet-connected mobile devices enable massive amounts of data to exist and flow around with increasing speed; artificial intelligence and machine-learning techniques make it easier to collect, store, explore and apply sophisticated analytics to that data.

About the author

Lesley Meall is a freelance journalist specialising in technology and finance

This article was taken from the August/September 2018 issue of The Treasurer magazine. For more great insights, log in to view the full issue or sign up for eAffiliate membership

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