‘Big data’ is not yet high on many treasurers’ agenda, but every organisation acquires a huge volume of data available on a continuous basis, both directly and through third party partners, such as banks, technology vendors and consultancies.
Artificial Intelligence (AI) and machine learning are increasingly being used to process and analyse large volumes of data quickly and objectively, with companies in many industries now employing highly sophisticated consumer analytics.
This trend is now emerging in treasury, so the question for treasurers is how to turn ‘big data’ into actionable information to help decision-making and refine processes. This will be manifested in different ways depending on an organisation’s treasury challenges and priorities, but there is particular value in areas such as cash flow forecasting where timeliness, accuracy and completeness of data continue to pose difficulties. Similarly, a growing number of treasurers are automating routine activities such as FX funding and hedging and daily cash investment.
Three tips in data analytics
- What data do you have available today, and where are the gaps?
- What are your key challenges in treasury, and what are your success criteria in addressing them?
- How can banks, consultants and technology vendors help to extract, manage, present and leverage data to meet these challenges?
Want to find out more? Do not hesitate to download the full Journeys to Treasury report.