Fintech has brought efficiencies and cost savings across many treasury operations but many believe that cash flow forecasting has lagged in sharing the benefits. Is that situation about to change?
Is cash flow forecasting the Achilles heel of fintech? As we get further into this autumn’s round of annual conferences it’s a question that regularly features as a topic of discussion. There’s a feeling that while potentially transformative new tech developments could take over many routine treasury tasks, introducing efficiencies and freeing up time for more valued-added work, there are still some activities where fintech could do better.
BNP Paribas is the latest to partner with a fintech with the aim of improving cash flow forecasting by digitising the process. The bank recently announced a collaboration with Cashforce and said that the partnership to offer digital forecasting services will “allow a cross-integration of corporate treasurers’ existing accounts and functions for a more holistic, streamlined view of cash positions.”
The solution is promoted as integrating with a range of enterprise risk management (ERP) solutions and the corporate’s other sources of financial data. “Forming agile partnerships with innovative fintechs, which leverage new technologies such as artificial intelligence (AI), helps us to significantly accelerate the digitalisation of our customer journey in the area of transaction banking,” said Jacques Levet, BNP Paribas’ head of EMEA transaction banking.
Accurate and efficient cash flow analytics and cash forecasting solutions also offered corporates and their treasury departments the opportunity to expand internationally, added Cashforce’s CEO, Nicolas Christiaen.
Among those optimistic that cash flow forecasting is about to make a major advance is Mike Zack, pre-sales manager for GTreasury, who believes that fintech will pave the way for greater progress over the next five years than has been achieved over the previous two decades.
“We’re living in interesting times as many fintech start-ups come to market and people become more comfortable with using the new technologies,” says Zack. “Convincing people to adapt to change is an important and necessary task – if you’re able to do it, life becomes much easier.”
One reason that many corporates have made only limited progress in transforming cash flow forecasting is the exponential rise in the total volume of data available. This makes treasury’s task of extracting what’s actually meaningful and relevant for forecasts ever more challenging.
“From a corporate perspective, you’re only as good as the data you have to hand for analysis and future use,” Zack suggests. “Fintech helps with collecting together all the data housed in different departments into one centralised location. The next task is to marshal that data into a prediction through employing different types of analytics. Fintech aims to solve each layer of that data and map it onto a common field through using application programme interface (API) technology.”
Rise of the CDO
“The proliferation of data means that a growing number of organisations are hiring a chief data officer (CDO). “Understanding data is more of an art than a science and you need to understand the data in your business before applying any API tools or robotics as otherwise it’s meaningless,” says Zack. “There has also been a growing tendency for people to spend more of their time attempting to validate data rather than actually analysing it.”
Have any industries or sectors made better progress in drilling down to the data most meaningful to their operations? Zack suggests corporates in the technology sector or whose business is data-driven such as the financial services sector.
“Insurance is one sector where companies are ramping up their infrastructure in order to better consolidate data. Banks are attempting to leapfrog over their competitors and big names such as J.P. Morgan are even rolling out their own blockchain technology,” he notes.
Digitising cash flow forecasting means that the fintech is primarily focused on the collection of data and making it easier to bring data together. It can then be leveraged by other tools such as AI, to explain the data. “Another benefit from tech is that it allows you to test your hypotheses and use the lessons learned,” Zack suggests. “You can afford to fail multiple times and learn from your mistakes.
“The problem with AI is that it’s not simply a case of pressing a button to provide an instant answer – you still need individuals providing high quality input. Some companies have purchased AI and robotic tools and summarily dismissed them as a wasted investment, simply because they haven’t allowed time for them to evolve and learn. AI is a powerful tool, but only as good as the individuals using it.”
Businesses are constantly shifting and changing, particularly those engaged in M&A activity. As data changes so do forecasts – and even needs time to adapt to and learn from the changes.
This also creates a need within organisations for a central unit to bring the activities of all its various departments together. Treasury can’t afford to work in a silo separate from all the other departments: in a siloed organisation, each department only understands its own data.
“The danger of silos was demonstrated a decade ago by the financial crisis, but the walls have yet to be fully broken down,” says Zack. “That’s why a CDO should be at the top of all these various activities and the data produced by each department – he/she will be one of the most important individuals within the organisations of the future.”
He believes this could create an environment within some organisations where Millennials are pitted against their older colleagues. “Younger workers have grown up with technology and adopted it much better.”
“This will have an impact on the organisations of the future as these individuals understand what the technology can do. The young take time to understand technology as they’re interested in it and its capabilities.”