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How to develop the ultimate Cash Flow Forecast

| 29-06-2020 | Cashforce

Cash flow forecasting has been called many things in literature. Ranging from the cornerstone of a finance & treasury department to the lifeblood of any organization; it’s fair to say cash forecasting is vital to get an accurate prediction of an organization’s health. Cash forecasting, at its core, is simply identifying all the various in & outflows over a given period in order to analyze and compare those estimations with your actuals. However, in reality, it’s not that simple and a lot of challenges arise in getting an acceptable end result, especially when complexity increases i.e. multiple systems, entities, currencies, etc. Additionally, it doesn’t stop at regularly getting the right information in a timely and efficient matter. Setting sensible assumptions and providing contingencies that offer flexibility in case of unexpected events are a few quintessential things to consider. Improving your forecasting results is more than relying on hard data, but bears fruit in the synergy of art and science. Don’t know where to start, or how to fill in the blanks on further optimizing your current process? Then follow this checklist.

1. Set your goals & requirements – getting to the why – decide:
  • Why are you creating a cash forecast?
  • Do you want to perform an indirect or a direct cash forecast e.g. focus on short term (direct) or longer-term (indirect), or a combination of both
  • What does successful (output look like? (formats, visuals…)
  • If you would like to combine both, choose how the reconciliation would work?
  • What level of granularity do you need?
  • What KPI’s will you be measuring?
  • Who will be the main users of the reports and analyses? (operational vs strategic or both)
  • Who will be contributing to generate the forecast?
  • How will the different contributors and users consume the outputs?
  • What other stakeholders will use the forecast? (e.g. shareholders)
  • Will you recognize forecasting performance? (e.g. remuneration)
  • What are your main cash flow drivers? (how do you define your business model?)
  • What will be the main process-steps?
  • To what extent your staff will be involved in the process? (vs. technology doing the work)
  • In case of exceptions, can the process be sidestepped? If so, what happens then?
  • What controls will be put in place?
  • Who will be in charge of setting up the process? (internal/external)
  • Who will be the main owner of the process?
  • How often does the data need to be updated?
  • How will data quality be ensured for new inputs?
  • What process will be put in place to clean the current data?
  • How will you flag and treat mis-allocated cash flows?
  • What will you use as a reporting currency?
  • How do you treat currency differences?
  • What data sources are most relevant for the forecast and what data you want to take into account:
    • Systems holding your (actual & future) payables and receivables?
    • What formats are your bank statements in? (MT940, BAI, EBICS, CODA…)?
    • Financial planning data. e.g. FP&A / budget / planning tools?
    • Do you have any Treasury & financing data, e.g. interest & FX payments on ongoing deals, residing in, e.g. a Treasury Management System or spreadsheets?
    • Do you need to take any other data into account, e.g. in data warehouses, other specialized systems for leasing, salaries, projects, etc.?
    • What manual input do you require? To what level?
  • How will you get the above data into the forecast? Is it possible to automate these processes?
  • How many forecast horizons do you want to define?
  • What cutoffs would you put in place to split the horizons?

How would you divide the short-mid- & long-term components of the forecast, see (e.g. different per data source below:)

An example of Cash forecasting horizons & their sources

  • What cash flow categories do you want to use?
  • Is there a template you can use as a basis of cash allocation categories, e.g. your current ERP, etc.?
  • How will you treat the unallocated transactions/cash flows?
  • Setting up accuracy feedback loops, e.g. regularly comparing actuals vs forecast & reviewing for improvement
  • Choosing which algorithms / logic – based on business drivers – can be integrated into your model to improve the forecast
  • Decide which contingencies to build in, e.g. revenue/cost/currency/… assumptions

Evaluate how you will you compare with and integrate industry best practices, e.g. staying up to date with the latest technology/peers/…

While creating an accurate cash forecast is not rocket science, getting an effective reporting process in place certainly requires a well thought out and reproduceable plan. Defining the who, the what, the when and the how is both a quantitative and qualitative exercise in building out a forecast. This checklist shows you how to combine the art and science of cash flow forecasting to get it done.


| 26-03-2019 | treasuryXL | Cashforce | Nicolas Christiaen

Cash is often labeled as the lifeblood of an organization as it enables a company to function. However, when it comes to forecasting cash, most companies face various challenges. Afterall, it starts with the uncertainty of the future, but more factors are at play. Decisions about risk vs reward, the essence of business, can be difficult. To learn more about the complexity of the topic from first-hand data, we initiated the first Cash Forecasting Survey together with the Financial Executives Consulting Group. This survey was focused on senior financial and treasury executives. The 225 respondents are active across a variety of industries (manufacturing, energy, retail, telecommunications, health care, …) that range from smaller businesses (35% under $50 million revenue) to big corporations (28% over $1 billion revenue).

This survey aims to dig a little bit deeper into the challenges that companies are currently facing, the underlying causes of these difficulties, as well as possible future trends and technologies that could ease these challenges. The results of the survey will be discussed in-depth during a webinar on the 27st of March, 2019 (11am EST / 4pm CEST). To lift the veil slightly we’ve distilled our top 5 key insights below.


A company’s ability to forecast the future with any degree of certainty is determined by external factors (i.e. competitor’s actions, market conditions such as interest rates and local tax rates) or internal factors (availability of funds, staff available, technology in use, access to data etc.). Regardless of whether one is a pessimist or an optimist there should be very little to argue about the fact that cash forecasting is one of the central pillars of treasury, and therefore has been on the radar for improvement for many companies for a decade. The graph below hints at the current focus: Given the opportunity to rank the most important issues over the next year, “cash forecasting” comes out on top (34%). Furthermore, we see in the answers that there is a big focus on the outcome as such, as well as on improving the current processes that are at play (such as management reporting, upgrading financial systems).



For the past decades, Excel has been integral to businesses everywhere. It’s embedded in countless processes throughout the company, including within finance and treasury departments. While spreadsheets remain popular as a tool to accomplish many tasks, even their users admit that they are error prone. Moreover, maintaining data integrity within spreadsheets can be a cumbersome and manual task since this type of technology was never meant to be an integrated solution to business issues (i.e. data from one spreadsheet almost never flows seamlessly into another spreadsheet).

Nonetheless, as the graphic below lays out, more than 9 out of 10 respondents continue to use spreadsheets for collecting/creating cash forecasts & making comparisons to actuals. 69% of respondents however find the process too time consuming. On top of that, the graph clearly shows that this is the case in all surveyed treasury/finance areas. Overall, we can state there is still a great over reliance on spreadsheets, from cash forecast generation to debt management. Combined, these insights indicate a dire need for a better solution in the area of cash forecasting and treasury management.




The following graph further illustrates how frustratingly long any spreadsheet driven forecast process can be. If we look at the distribution of respondents that spent more than 10% of their resources on creating/updating cash forecasts, we can see that 43% of respondents spend more than 2 hours a day on average on creating/updating cash forecasts. Naturally, with only limited resources available for processing, forecasts will be less than “perfect” until conditions are changed.  Investing in “better” technology has been shown to help the forecasting process, but technology alone (i.e. working faster) is not a substitute for working smarter (i.e. more strategically) as the following survey observation makes clear.



It cannot be said with certainty what the “perfect” allocation of resources devoted to processing vs planning / analysis should be in the forecasting process. As mentioned earlier there is a continued reliance on a disparate set of 1980s technology (i.e. spreadsheets) perhaps because they are easy to use and offer a certain degree of flexibility. However, basing your forecasting on technology that offers little in the way of scenario planning, ability to sum up / drill down through an organization or track change by date, user, etc.  may constrain a company’s ability to measure its success.

In response to the weaknesses of spreadsheet driven forecasts many companies over the last decade have implemented a large number of Treasury Management Systems (TMS). Yet, the adoption of a TMS for forecasting purposes has been slow to occur. As the survey results show, more than 9 out of 10 respondents still use spreadsheets for cash forecasting, even when using a TMS. It is a surprising statistic and may indicate that a TMS maybe better at processing (e.g. cash positions, payment execution, cash accounting, etc.)  than at planning / forecasting.



As seen in previous paragraphs, the processes involved in cash forecasting are mostly done manually and with error-prone tools and processes. As a result, companies frequently struggle to foresee unexpected occurrences that impact the livelihood of their business. Bridging these gaps can pose considerable risks and can be very costly to overcome. Consequentially, one would expect companies to put rewards in place for their business units in order to draw out valuable insights when it comes to cash flow. Yet, 3 out of 4 companies don’t reward their business units based on cash flow. Even among the large companies (i.e. revenue > 500MM) only 33% of companies reward their business units based on cash flows. It prompts the question: If cash forecasting ranks as the number one issue, how come it is rewarded as a by-product rather than a focal point?



As the survey shows, cash flow forecasting is an important tool used by businesses to peer into the future and work towards accomplishing previously set profitability, liquidity and risk goals.

Unfortunately, all forecasts will be “wrong” as the future is uncertain and forces companies to navigate through a seemingly infinite sea of scattered data that only increases over time and becomes prone to human error as it accumulates up and down the organization.

Though no forecast will be perfect, any forecast requires a certain amount of dedicated resources (e.g. staff time throughout the company, integrated sets of data and the technology to turn data into information). If too many resources are devoted to processing then there will be less time remaining, possibly reducing the quality of actual decisions made. Few companies should base their strategic decisions based mostly on time left over as it may harm, not benefit the company. Depending on the size of the company, the following trends can be seen:

  • At many large companies treasury departments have taken the lead on cash forecasting by beginning to replace their spreadsheets with more purpose-built applications such as a TMS, but even this type of system appears to have limitations, perhaps because it had its origins in processing transactions rather than comparing alternative futures and lacks real “what if” features.
  • At small to medium sized companies FP & A areas are often responsible for cash forecasting, but, as the survey shows, spreadsheets are not the best forecasting tool and ERP systems contain only historical data that is difficult to extract and project into the future.

There is no definite answer to what mix of resources should be employed to achieve success, but relying on the current mix of disparate technologies doesn’t seem to be the answer. Fortunately, advances in new technology available to users through out a company are paving the way towards a clearer future, one driven by analytics, visualization, automation and transparency of data across an entire company.

Curious about additional findings from our survey? Be sure to register here for the webinar on the 27st of March, 2019 (11am EST / 4pm CEST) where we will discuss these and other findings and learn more about the challenges and solutions of Cash Forecasting.

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Webinar: Cash Forecasting Survey Results 2019 – Too Much Processing, Not Enough Forecasting?

| 21-03-2019 | treasuryXL | Cashforce |

Even the most experienced treasury departments struggle to create accurate cash forecasts. By conducting the Cash Forecasting Survey 2019 we wanted to find out why companies face challenges that make the future uncertain.

In our upcoming webinar on the 27th of March at 16h00 CET (11h00 EDT), Nicolas Christiaen & Mark O’Toole will discuss the results, moderated by Bruce Lynn of  FECG.

By attending this webinar, you can expect to come away with:

• Current challenges that come with the process of generating cash forecasts
o Out of date technology?
o Overworked or undertrained staff?
o Conflicts between priorities and goals?

• The implications of inaccurate and inefficient estimates on the need for
o Maintaining “enough” liquidity
o Avoiding “too much” risk

• Insights into your peer’s cash forecasting methods

• Possible solutions to improve your current processes when faced with an uncertain future

Claim your seat here!

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Partnership Cashforce and BNP Paribas

| 03-10-2018 | Cashforce | treasuryXL |

BNP Paribas and Cashforce enter into a partnership to offer digital cash flow forecasting and working capital services to corporate treasurers. Through this partnership, BNP Paribas will offer to its clients Cashforce’s next-generation digital cash forecasting and treasury management solutions, focused on analytics, automation and integration. To further extend its commitment to this partnership, BNP Paribas also invested in Cashforce.

Pursuing the digitalisation of its Corporate clients’ user experience, BNP Paribas today announced it has sealed a partnership with Cashforce, a Fintech company that will allow the Bank to enhance client journeys within cash management and trade finance. Through this partnership, Corporates will experiment a digital, autonomous and cross-banking solution for their day to day transaction banking needs: by connecting its treasury department with other business and finance departments, and by offering full transparency into the cash flow drivers, accurate and automated cash flow forecasting and treasury reporting.

BNP Paribas continues to invest in its digital offering to treasurers and this partnership – which brings the transaction banking business another step closer to open banking – reflects its technology-centric focus and leadership. The platform is unique in its category because of the seamless integration with numerous ERP systems and financial data sources, the ability to drill down the transaction level details, and the intelligent AI-based simulation engine that enables multiple cash flow scenarios, forecasts and impact analyses.

“This partnership with Cashforce marks a new step in our digital transformation and illustrates our commitment to offering our clients the best-in-class solutions they deserve, wherever they come from. Forming agile partnerships with innovative Fintechs like Cashforce, who leverage new technologies such as AI, helps us to significantly accelerate the digitalisation of our customer journey in the area of transaction banking,” commented Jacques Levet, Head of Transaction Banking EMEA BNP Paribas.

“The partnership with BNP Paribas will further boost our international expansion and make more treasury departments work with accurate, efficient and best-in-class cash flow analytics and cash forecasting solutions. Also our working capital analytics engine will further strengthen the integrated banking and trade finance experience for BNP Paribas’s clients.”  added Nicolas Christiaen, CEO of Cashforce.

The platform will be available to clients through CENTRIC, BNP Paribas’ integrated digital banking platform that gives corporate & institutional actors instant access to the spectrum of BNP Paribas’ online financial services.

The full article can be read on the Cashforce website.

BNP Paribas also posted an article about the partnership which can be found here:

Cashforce – Cash forecasting & Smart Treasury

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Best read articles of all time: Do treasurers really need instant payments? some implications.

| 03-08-2018 | Patrick Kunz | treasuryXL



Per 13 January 2018 we have a new payments service directive (nr. 2) live in the European union, PSD2 for short. One part of PSD2 is the possibility for banks to offer instant payments between banks in the EU. Within max 10 seconds money flows from one bank to the other, also on weekends and on holidays. In this paper I want to discuss the implications for treasurers of instant payments.

Cash flow forecasting

Forecasting is an important part of the daily/weekly routine of a treasurer. He/she needs to predict the future to know his cash/risk/financing position. On the ultra-short term spectrum of this forecast a treasurer might use intraday bank statement (MT942) to take into account the incoming funds during the day. These are often updated hourly. With instant payments a treasurer can have a look at their bank account and the balance that is showing is the real-time balance with all incoming transactions being settled. As said before a treasurer might already have intraday statements but there is (1) a time lag in those and (2) there might be transactions not processed yet. Bottom line this difference amounts to several hours lag. Depending on the size of the company and the amount and size of transactions there is some impact but not very sizeable. Furthermore, those treasurers that do not use intraday balances for their forecasting have no impact of instant payments. However, how about the due payments on non-working days? In the future these are normal payments dates. Previously due payments on weekends are either set on Friday or Monday depending on the terms of the contract. These could now be forecasted on the exact day. But that depends, payments are often done during business hours, so it is possible that nothing changes. Depending on the size of the transactions there is importance to check this with your suppliers and clients. This also depends on bank processing of yourself and your client/supplier.

Bank processing

Instant means instant in time but also in days. In the past we were dependent on the opening hours of the banks and later of the ECB. That could mean that if we send money just after close on Friday and there was a public holiday on Monday we would only see the money coming in on Tuesday. The money was “lost in translation” in between. This is not very modern in an age where we send an email from Tokyo to South Africa in minutes but not money. We could literally fly there with cash and be faster. After all banks have implemented PSD2 money flows 24/7. So also in the weekend and on holidays. This has an impact on the processing of your bank statement. You now receive bank statement for Saturday and Sunday. Most accounting/treasury departments do not work on the weekends so there is a chance that these statements are not processed. This means you must process 3 statements on Monday. Some companies have automatic processing of bank statements, so the weekend statements might be processed but not (automatically) consolidated leading to more open positions on Monday. Ok big deal, there is more work to do on Monday due to more bank statements. But there is more: not necessarily for treasury departments. Think about customer services (helpdesk) departments. If a client with an overdue payment calls it would be great if the helpdesk employee is able to verify statements of the customers if the says he has paid or will pay immediately. This however only works if processing is automatic or if the helpdesk employee can access/search the incoming payments on the bank account (which might not have processed in accounting). Not all companies will have this yet. Overdue calculations might be faulty in some ERP systems as only working days are considered. If a payment is due on Sunday, you can pay on this Sunday and not necessarily on the Friday before.


Instant payments are only a fraction of PSD2 which is often not very interesting for most treasurers. They get some information faster but that does not really help them too much. There is however more to it. Since payments can now arrive and be made in the weekends the cash flow forecasting should now contain 7 days in a week instead of 5. Payment can be spread out more but also receipts will be. Bank processing is more work; 7 daily statements per bank account per week instead of 5. Extra processing or extra automation needed. The extra information might be needed by other departments too even though the treasury/accounting department is not working.

Overall the implications could be bigger then you might think and are different for every company and depending on their existing (bank) processing.
Most bank are planning to introduce weekend reporting by H2 2018 while instant payments are due beginning 2019. For business transactions this might even take until H2 2019.

Some time left but a good time to already think about your current processes in comparison to the new reality under psd2. Treasury is moving to a 24/7 information economy. It’s about time.Time will tell if there will be fintech’s stepping in helping with above issues with direct connections to the bank, which is another important part of PSD2 but not within the scope of this article.

If you need help with automating your bank statement processing or with your cash flow forecasting, then look at this author and other Flex Treasurers on this website for answers.

Patrick Kunz

Treasury, Finance & Risk Consultant/ Owner Pecunia Treasury & Finance BV



Data analysis – pros and cons

| 18-04-2018 | Lionel Pavey |


With the advent of computing and ever more powerful processing capabilities, we are living in a time where there is more and more data available within a company. Advocates of data mining speak of the advantages that can be obtained by analysing all the data and discovering trends within the data. But there is also the risk that we end up being swamped by the data overload – so much data, so little time. If we want to analyse all our data, what is it that we truly want to find? How can we interpret all the data and arrive at beneficial conclusions?

Treasurers and cash managers are long time users of data analysis – it is used to go from a macro level to a micro level for individual transactions. When designing a cash flow forecast it is essential to take the micro approach. There will always be peak days for outflows – wages are paid, normally, on 1 specific day of the month; on the last working day of the month there is large expenditure relating to taxes and social premiums. Additionally, if the company works with monthly subscriptions, there will be peak days for inflows as all the renewals take place. These “exceptional” items need to be input as hard data on the relevant working days to assist in presenting an accurate forecast.

Another application of data analysis is to interrogate the actual Days Sales and Days Purchasing Outstanding – DSOs and DPOs – that make up the cash conversion cycle. A lot of unnecessary working capital can be tied up in this process. Understanding the transactional characteristics of individual debtors and creditors can be very beneficial to freeing up working capital. Furthermore, it allows the company to review their relationships – is it worth maintaining certain contacts if they do not meet the agreed terms and conditions on their trade transactions.

It is also possible to conclude that certain clients could benefit from a more advantageous pricing policy. Rewarding those that comply leads to better relationships and the improvements in cash flow can help reduce external borrowing requirements.

When attempting to analyse data, it is imperative to first understand what you are looking for. Obvious metrics could be month on month sales or purchases, seasonal effects on turnover, new products, promotional offers etc. The act of analysing data, together with the awareness within the company that the data is being analysed, can lead to anomalies caused by people’s actions. Data input could be subject to a form of “window dressing” – entries are made before the end of the month and then corrected in the following month.

It is possible to conclude that there is a trend in the data – some people even look for these – that could lead to a false sense of conclusion. There is also the danger that 2 different streams of data are linked to each other because they show the same trends. When analysing data is it necessary to be open minded about the expected outcome. If people start analysing with a preconceived idea of what the outcome should be, human nature can intervene and the data is interpreted in a way that justifies the preconceived idea.

Data analysis is a technical discipline that can overlook the fundamentals. Before the CDO crisis of 2008, most banks agreed with the interpretation of the underlying data within the systems, without challenging the reality of the scenarios being presented. Even after the crisis started, the banks were unable to foresee the severe impact that it would have on the whole financial market. I have a curious leaning to analysing long term interest rates – I have collated data on Interest Rate Swaps since the inception of the Euro. Whilst I am able to spot long term trends, I have failed in ever calling the top or the bottom of the market.

When analysing data, it is imperative that the basic fundamentals of a company and its products is never forgotten, If sales are down, a more fundamental approach needs to be undertaken. Are our competitors cheaper, are their products better, is the economy in a downturn, are our products obsolete?

Analysis should always be undertaken, but the results must always be weighed up against the reality of the marketplace. It is too easy to draw conclusions – it gives the illusion that the analysis is good.

A lot of good things can come from data analysis, but it must not exclusively determine the actions that a company takes in its quest for growth and survival.

Lionel Pavey

Lionel Pavey

Cash Management and Treasury Specialist


Forecasting the future by looking at the past

| 25-7-2017 | Lionel Pavey |

A key role within the Treasury function is providing forecasts to the directors and management. The most obvious would be the cash flow forecast, but others would include foreign exchange prices, interest rates, commodities and energy.

A forecasts is a tool that helps with planning for the uncertainty in the future, by analyzing data from the past and present whilst attempting to ascertain the future.

Internal – cash flow forecast

We would like our forecasts to be as accurate as possible – that the values we predict are close to the actual values in the future. This requires designing a comprehensive matrix to determine the variables needed for the data input. Data has to be provided by all departments within a company to enable us to build a forecast. This data needs to be presented in the same way by all contributors so that there is consistency throughout.

We also have to see if the forecast data is within the parameters of the agreed budget. We also need to check for variances – why is there a difference and how can it be explained.

External – FX and Interest Rates

A more common approach is to read through the research provided by banks and data suppliers to try and see what the market thinks the future price will be. Also we need to include data from the past – we need to know where the price has been, where it is now and what the expectation is for the future.

Extrapolating forward prices is notoriously difficult – if it were simple, we would all be rich in the future! But, by including past data, we can see what the price range has been, both on a long term as well as a short term basis.

When attempting to find a future value there are 2 common methods used – fundamental and technical.

Fundamental Analysis

Use is made of economic and financial factors both macroeconomic (the economy, the industrial sector) and microeconomic (the financial health of the relevant company, the performance of the management). The financial statements of a company are analysed in an attempt to arrive at a fair value. This leads to an intrinsic value, which is not always the same as the current value.

The value is normally calculated by discounting future cash flow projections within the company.

Technical Analysis

Use is made of the supply and demand within the market as a whole and attempts to determine the future value by predicting what the trend in the price should be. This is done by using charts to identify trends and patterns within the data. This assumes that the market price now is always correct, that prices move in determinable trends and that history repeats itself. Technical analysis uses the trend – this is the direction that the market is heading towards.

Whilst these 2 approaches are independent of each other, they can be used together. You could take a fundamental approach to value a company or asset, and then use technical analysis to try and determine when you should enter and exit the market.

Fundamental analysis is more of a long term path and technical analysis is more short term. The most important thing to remember is that markets only really experience large movements based on changes to the fundamentals. Predicting the long term future only via technical analysis is likely to be incorrect. All the major movements over the last 50 years in the prices of shares, bonds, foreign exchange and interest rates have occurred because of a change in the fundamentals.

In the next article, I will look at various methods of calculating averages to determine the trend.

An economist is an expert who will know tomorrow why the things he predicted yesterday didn’t happen today.

Lionel Pavey


Lionel Pavey

Cash Management and Treasury Specialist


The Corporate Treasurer and Blockchain

| 17-08-2016 | Carlo de Meijer |



While it has been widely reported that – despite its disruptive character – the majority of banks think that innovations such as blockchain technology will positively impact their business and are exploring how they can use blockchain to their advantage, it is still largely a grey area for many corporate treasurers. But given the various challenges that corporate treasures are facing today, they also need to pay attention to this ‘cutting-edge’ blockchain technology. 

Complex environment

Today’s business environment for corporates that are internationally active can be highly complex from a treasury point of view. The treasury includes basic tasks like cash management, bank relationship management, payments, and corporate investing.

The corporate treasurer strives to achieve optimal working capital utilization to ensure that the financial supply chain efficiently and effectively supports the physical one. It does this by monitoring global cash positions and managing credit facilities across all bank accounts of the group companies to move cash to where and when it is needed.

“Cash management and forecasting are more challenging because of increasing business complexity.  The level of complexity is likely to get worse over the next two years”

In the digital era, real-time insight into a company’s global cash positions and cash requirements and the ability to move monies intraday is increasingly needed to support this changing business environment.

Today’s model of international correspondent banking however does not easily facilitate the ability to manage cash in a real-time environment.


Corporate treasurers thereby face various challenges.

A first one is to obtain in a timely manner consolidated information of group-wide multi-currency positions across a fragmented banking network. This is needed to optimize the financing mix and duration of funding against expected and actual enterprise cash flows.

A second key challenge is optimizing the automation of “order-to-cash” and “purchase-to-pay” cycles with an optimal rate of straight-through-reconciliation (STR) of cash to accounting.

Need for …..

Cash management and forecasting are more important than ever for a company’s financial success, but they have also become more difficult to execute. And the pressure to provide insightful and proactive cash reporting and forecasting is only likely to grow. Management outside of treasury needs a better understanding of a company’s cash positioning and forecasts.

To execute in this environment, treasury functions will need to find ways to provide management with information on cash positions and cash forecasts faster and with deeper insight.

So where should treasury start, in order to improve forecast quality despite increasing internal and external forces that adverse impact reporting?

Blockchain enters the stage

But there is a technology available to take the pressure off the modern cash management professional: Blockchain. This technology could fundamentally affect the various areas of corporate treasury  as it could transform how financial transactions are recorded, reconciled and reported.

The potential applications of blockchain technology for the treasury are vast. They may  range from cash management and correspondent banking, to trade finance and documentation, supply chain management, commodity financing and account opening.

Especially for treasury relevant payments, when applying blockchain, these could be executed instantly between the various participants. As the ownership and provenance of transactions can actually be embedded in the blockchain data, blockchain has the potential to be used for mainstream payments, thereby providing  a robust and secure framework for verifying transactions.


Blockchain  could have a number of positive impacts on the transparency, efficiency, cost and risk issues currently associated with corporate treasury. This may bring them various benefits.

  • It will allow for improved liquidity management. Blockchain has the potential to enable real-time/instant insight in a corporate’s liquidity position and how quickly they can provide liquidity to their corporate.
  • The transparency brought about by blockchain technology between the various players could bring benefits especially for those activities that need multiple controls such as transfer of payments. Such transfers can be done much quicker and in some instances even instantly.
  • It will also allow for improved risk management. As the credibility of debtors and creditors is supposed to be known at all participants blockchain will also contribute to more security.
  • Treasurers are nowadays under pressure to reduce costs. Blockchain may allow much lower trading costs for banks because much less parties are involved for reconciliation purposes. Some even say it could save banks billions of euros. And if banks could provide their services to corporates at lower costs that might be of great help for treasurers.
  • And what about the use of smart contracts, in which lawyers and accountants essentially act as coders. When two parties enter into a transaction together, the accountant/lawyer/coder inputs into the blockchain what the event they have all agreed on. This event will occur automatically. That might contribute to much greater efficiency.
  • But also from a financial and business strategy issue, blockchain could bring great benefits. Having a clear picture of assets and cash flows, finance has the ability to make strategic investments in shorter period of time, helping to capitalize on potential investment opportunities and evaluate important future transactions.

Take a longer view

Blockchain has the potential to fundamentally change the treasury function at corporates. For some blockchain is even going to be a game-changer for treasury. The change might not be here yet, but it is coming, and treasurers need to take the long view on it.




Carlo de Meijer

Economist and researcher