Data Driven Treasury: Time to Take the Quantum Leap
By Eleanor Hill, Editor
There’s something delicious about an exclusive interview – especially when it involves Ole Matthiessen, Global Head of Cash Management, Deutsche Bank, candidly discussing the eyebrow-raising results of the bank’s latest corporate treasury survey. This year’s report examines the technologies enabling treasurers to mine for ‘data gold’, as well as the hurdles facing treasury functions as they wrangle more data and aim to deliver greater insights to the business.
Eleanor Hill, TMI (EH): The results of the annual corporate treasury survey by the Economist Intelligence Unit, supported by Deutsche Bank, are hot off the press – and ready to be launched at EuroFinance in Copenhagen. Could you give us a ﬂavour of this year’s study?
Ole Matthiessen, Deutsche Bank (OM): I’m really excited to be able to share highlights of this year’s survey with you. The title of this edition ‘A Quantum Leap: Building a data-driven treasury’ reflects the fact that data is quickly being recognised as a corporate asset. As digitisation sweeps through businesses, the growing volume and depth of financial data available presents a strategic opportunity for the treasury function. Using this data wisely can help treasurers to generate timely cash and liquidity insights, and facilitate faster treasury decision making.
Simply ‘owning’ data is not enough, however; digital transformation is required in order to extract, aggregate, and analyse good quality data. As such, the journey towards data-driven treasury takes time. The survey results therefore enable treasurers to identify how far along they are on that journey, depending on the organisation’s size, complexity, and treasury team structure, for instance.
Bringing together responses from over 300 corporate treasurers across the globe, the report is structured in three sections:
1. The past – looking at the digitisation that has already taken place and the opportunities treasurers have harnessed in order to become more data driven
2. The present – focusing on the priorities when working on a data-driven strategy
3. The future – exploring emerging technologies to further treasury’s data intelligence
EH: Before we get into the meat of the survey findings, what are the potential benefits of a data-driven treasury? Why should treasurers take the time to look beyond the big data hype?
OM: Using data analytics to drive treasury decisions helps to reinforce treasury’s role as a profit centre – according to the survey principally through higher operational efficiency (39%) and improved return on investments (36%). Being a data-driven treasury function also has value when it comes to navigating complex regulations such as IFRS 9 and GDPR.
EH: Looking briefly into the past, what kind of technologies have treasurers been using until now to help them leverage data?
OM: Treasurers are using technologies such as big data analytics (45%), Treasury Management Systems (TMS) (43%) and cloud-based applications (42%) to manage their data. This marks a significant shift from our survey last year, where cloud technologies ranked close to the bottom (chosen by 30% of respondents in 2018 versus 42% in 2019).
Naturally, the extent of technology adoption varies significantly among treasury departments. And unsurprisingly, many continue to rely extensively on spreadsheets for core treasury functions. But the transition is underway from static technology tools to more automated systems, which is contributing to greater awareness of the value of data.
EH: What is driving the relatively rapid uptake of cloud solutions do you think?
OM: It’s a good question because cloud solutions for treasury first materialised just over a decade ago, when TMS vendors began to offer software-as-a-service (SaaS).
It has taken some time for risk-averse treasurers to accept the security and robustness of cloud-based solutions and I think that initiatives such as the Statement on Auditing Standards (SAS) 70, which scrutinises the data security and control of cloud providers, have led to a wider acceptance of more advanced analytical systems among treasurers. We’re also another 12 months into the cloud phenomenon now and treasurers feel generally more comfortable with the concept as a result of the passage of time, and more of their peers adopting such solutions.
EH: Thinking about what treasurers should do today to make use of the data these systems are providing, what are the first steps in building a data-driven treasury?
OM: The secret to becoming a truly data-driven treasury is crafting a data strategy upfront. Over half of treasury professionals (53%) surveyed already have a well-defined data strategy, but the remaining 46% say that their data strategy is only ‘somewhat’ well defined, suggesting that there is still a way to go in formalising this policy.
Creating a data strategy requires aggregating and visualising the data available, assessing data quality, and identifying specific treasury responsibilities that can be enhanced through data analytics. To give an idea on the latter, respondents suggested that those functions most in need of data assistance are investments (29%), cash flow forecasting (25%) and exposure identification and measurement (24%).
EH: You mentioned the quality of data there. How confident are treasurers in the data they are working with?
OM: Quality of data underpins the effectiveness of any data strategy.
Four in 10 survey respondents were very concerned about the poor quality of financial and other business data in their organisations. A further 27% were somewhat concerned and 30% were slightly concerned.
The survey also showed that those who are involved in compiling the data and/or looking closely at data-driven approaches have more serious trust issues about the quality of the data than others using the data.
Interestingly, unstructured data appears to be preferable to treasurers when it comes to improving the quality of their analysis. Pooled data from multiple ERP systems (among others) may be standardised to use across different parts of the business; such standardisation can counteract the data-driven treasury approach since key nuances in the data may be lost or hidden.
EH: What role does culture play in raising the quality of treasury data?
OM: You’re right that issues with the quality of the data may stem from the team’s culture and skillset. But finding treasury staff that understand the technologies required for a data-driven strategy can prove challenging. Training treasurers in the principles of data analytics is therefore important, so that they can communicate more effectively with IT about treasury data requirements.