Career calibration meetings with Treasurer Search
01-04-2020 | Treasurer Search | treasuryXL
You can contact Kim Vercoulen directly with below contact details.
01-04-2020 | Treasurer Search | treasuryXL
You can contact Kim Vercoulen directly with below contact details.
| 17-03-2020 | Erna Erkens | treasuryXL
In this blog, our Expert Erna Erkens, discusses the past events and their consequential effect on currencies. Erna Erkens is owner of Erna Erkens Valuta Advies, a consultancy firm specialized in currencies.
After 35 years of work experience in the financial markets at 2 different banks, Erna wanted to work as a self-employed person. For many companies, the topic of “currency risk” is on the agenda, but often does not reflect the effect that currency movements can have on organisational results. Erna noticed that there is a great need within SMEs for knowledge and support with regard to currency risks, among other things. With EEVA, Erna shares her knowledge in different ways to meet this need.
(Blog is in Dutch)
EUR/USD: Gisteren geen cijfers uit de Eurozone, maar wel een ingelaste vergadering van de EU ministers van Financiën. Uit de VS was gisteren de NY Empire State index veel lager dan verwacht en vorige maand. Vandaag de Ecofin vergadering en de ZEW index uit Duitsland en de Eurozone. Verder nog de kosten van arbeid en de productie uit de bouw van de totale Eurozone. Uit de VS de detailhandelsverkopen, de industriële productie, het gebruik van de capaciteit, de zakelijke voorraden, de openstaande vacatures en tot slot de NAHB huizenmarkt index. Maar de ogen zullen toch vooral op de financiële markten gericht zijn deze dagen. Alles is in mineur behalve de USD. Dus EUR/USD moest toch weer een cent prijsgeven gisteren. Als de vlucht naar de USD aanblijft houden kunnen we wel weer wat verder naar beneden. Tot de paniek over is. Toch zal dit gelimiteerd zijn door de verkleining van het renteverschil tussen de EUR en de USD. Dus als er maar een beetje vertrouwen terug komt zal de EUR/USD flink stijgen. Maar nu lijkt de USD nog een flinke veilige haven. Toch is de EUR/USD een stuk hoger sinds de laagste koers van 1.0790 van een paar weken geleden.
WTI Crude Oil: USD 29.58 (olie voor de VS, gisteren USD 31.12) Brent Oil: USD 30.08 (olie voor Europa, gisteren USD 33.66). Olie uit Shanghai Yuan 241.30 = USD 34.47 (contract is van april 2020). Het verschil tussen de Brent en de WTI Crude Oil is bijna helemaal verdwenen. Dat is best heel bijzonder. En dat is ook een teken voor mij dat de beweging bijna voorbij is. Maar de USD 50 komt niet zo snel terug. Pessimisten zien het naar onder de USD 20 gaan. Zou kunnen, maar ik ben minder pessimistisch. Maar de komende maanden lijkt Saudi Arabië de oliekraan vol open te draaien. Althans dat zeggen ze nu,maar dat kan zomaar weer veranderen. Als dat blijft zal er een gematigde stijging komen denk ik. Maar als er toch weer gesprekken met Rusland en overeenstemming zal zijn dan kan dit onmiddellijk weer helemaal omslaan. Ik acht dat ook niet onmogelijk. De opslag voor olie is nu schreeuwend duur. Ik denk dat we de komende tijd nog te maken houden met lage olieprijzen,maar dat dit wel op een iets hoger niveau zal zijn. Ik heb het al vaker gezegd, maar ik schat de ruimte om verder te dalen vrij beperkt in. Standard Chartered verlaagd zijn gemiddelde verwachting van de olieprijs voor de Brent van met -USD 29 maar USD 35 voor 2020.Ik ga mijn lange voorspelling ook naar beneden aanpassen volgende week. Maar niet zover denk ik. Het is alweer dalende.
Barrel / vat olie = 158.99 liter
Gallon = 3.7854 liter
USD 1483.0 (gisteren USD 1514.00). De goudprijs is in USD per troy ounce (=31.1 gram). Goud heeft zijn glans als veilige haven op dit moment helemaal verloren. Iedereen gaat voor cash. Dus is de USD,Japanse Yen, Zwitserse Franc in trek. En zelfs de Euro lijkt wat veilige haven glans te krijgen. De bodem van het goud lijkt overigens wel ongeveer bereikt. Cash is King!!! Maar dit zal snel weer terugkomen. Als de echte paniek wegebt of als je aan de nieuwe situatie wennen. Mooi moment om te kopen zou ik zeggen. Een analist sprak de woorden: De traditionele regels zijn op niet meer aan de orde en er is niets dat als een veilige haven kan worden geclassificeerd. Zelfs het goud niet. Dat komt snel weer terug is mijn gevoel.
USD 12.35 (gisteren USD 13.10). De zilverprijs is in USD per troy ounce (=31.1 gram). Zilver is helemaal in de kaartenbak verdwenen. Ongelofelijk. Zilver op een laagterecord sinds 2009. Ongelofelijk. Wat voor het goud geldt is voor het zilver nog meer van kracht. Wat een koopje. iedereen komst echt wel weer bij zinnen. Dan zal het zilver weer snel stijgen, Maar dit is wel een enorme klap. die had ik niet eens een beetje aan zien komen. Tja.. Ik kan me een turbo of call optie goed voorstellen.
De Europese beurzen zijn gisteren gemiddeld -4.2% lager gesloten. De AEX is gisteren -3.10% lager gesloten op 419.83. De AEX is vanmorgen 3.6% hoger geopend op 431.65. Weer bijgekocht gisteren. De beurzen in de VS zijn gisteren gemiddeld -12.5% lager gesloten. (Dow Jones, Nasdaq en S&P). Azië: De Japanse Nikkei is vanmorgen 0.06% hoger gesloten. Chinese beurzen zijn vanmorgen gemiddeld -0.5% lager gesloten. De beurs in Hongkong is vanmorgen 0.85% hoger gesloten.
In deze tijd komt echt leiderschap naar boven. Ik zie op de tijdlijn op twitter van Trump alleen maar geretweete berichten. Een soort doorsturen. En het eerste bericht op Twitter van hemzelf gaat over de journalisten van The Times. Tja… Verder terug op de tijdlijn roept hij Amerikanen op elkaar te steunen en geeft hij aan dat er genoeg voedsel is in de supermarkten voor iedereen. Hij is positief over de beurzen. We gaan na de crisis de beste beurzen ooit zien. Dat is makkelijk voorspellen na een daling van 30%. En tot slot nog goed nieuws. Hij zal de luchtvaart en bedrijfsleven steunen. Dat geeft rust op de beurzen zo lijkt het.
Gaat Rusland de rente verhogen om de Roebel te ondersteunen? Zou bijzonder zijn in deze tijden van renteverlagingen. Turkse Lira’s ook helemaal in de kaartenbak. Zweden gaat ook weer verruimen door de aankoop van obligaties.
Als het er echt op aan komt, willen mensen toch nog steeds cash geld hebben en is de USD nog steeds in trek, samen met de Japanse Yen en de Zwitserse Franc en in mindere mate de EUR. Ik vind de woorden van de Europese Ministers wel groot, maar nu de daden nog. Het gaat allemaal traag. de FED is daar wel beter in. Dat heeft niet met Trump te maken overigens. De FED/overheid in de VS heeft totaal USD 2200 miljard beschikbaar gemaakt. Dit is voor 330 miljoen inwoners ongeveer. Dat is USD 6.666.67 per inwoner. Wat stellen wij daar als Europa tegenover? En met welk tempo?
Bund contract: 171.40 (contract per juni 2020, gisteren 172.49). Een verschil van 0.15 punten in de Bund is ongeveer 0.01% in de 10 jaars IRS (Bund omhoog = lange rente omlaag en vice versa). De Bund is de meest verhandelde langlopende Duitse obligatie en geldt als leidraad voor de obligatiemarkt en IRS prijzen. De IRS prijzen zijn de basis voor onze hypotheekrentes. De lange blijven ineens stijgen. De rente in de VS is met 1.5% verlaagd en de lange rente’s stijgen? Raaarrrrr
10 jaar Staats Duitsland -0.41% (gisteren -0.48%). Verschil met VS 1.24%.
10 jaar Staats Nederland -0.08% (gisteren -0.22%) Verschil met VS 0.91%.
2 jaar Staats VS 0.40% (gisteren 0.38%) Verschil met 10 jaars VS 0.47%.
3 maands rente VS 0.27% (gisteren 0.25%). Verschil met 10 jaars 0.60%.
10 jaar Staats VS 0.83% (gisteren 0.85%)
10 jaar Staats VK 0.51% (gisteren 0.41%) Verschil met VS 0.32%
10 jaar EUR IRS -0.05% (coupon 6 maanden en 30/360). Gisteren -0.08%
Owner at Erna Erkens Valuta Advies (EEVA)
| 13-03-2020 | by treasuryXL | Yvonne Wijnberg
The Vrije Universiteit (VU) Amsterdam is proud to announce that they honored 13 new Register Treasurer (RT) graduates. The graduated RT’s of March 2020 were part of the 22nd class. One of the graduates is Yvonne Wijnberg. Yvonne is Treasury Manager at the fast-growing, international non-food discounter, Action. She shares her story with us about her RT experience from start till end.
The Treasury Management & Corporate Finance post graduate programme is 1.5 years of investing in yourself and your career. For sure if you have been out of school for as many years as I have, it is not easy to get back in the process of studying for exams, but once you are back in the routine, it brings you so much more than you expected.
After a career in Corporate Accounting I decided that I needed a change, so 12 years ago I made the switch from Corporate Accounting to Treasury. It was not easy to start from scratch again after working for over 10 years already, but I have never regretted the change a single day.
My career has never been a speedy process and I have made a few sidesteps along the way, but in the end it got me to where I am today. In March 2020 I finished the post graduate programme for Treasury Management & Corporate Finance at VU university Amsterdam.
When I started in September 2018, I was worried I might be the oldest there, fortunately this was not the case. The group was a pleasant mixture of sexes, ages, experience and disciplines. Not only people who work in corporate Treasury joint the programme, but also consultants, bankers, controllers and tax professionals were part of the group. This is one of the reasons why the programme is so interesting. Getting to know my fellow students and interact with them was an enrichment to my development and network. But also the lectures from professionals over a wide spread of topics is something that has added value to my daily operations.
The programme is diverse. Some courses focus on cases, while others are more theoretical. But the complete programme gives a solid basis of all subjects that can cross your path in Treasury. And as always, one course will appeal more to you than another. If you’re working in groups on assignments the learning point is not only the assignment itself, but also in broadening your view and making you more aware of other options then the once that seems most logical to you.
Part of the programme is also that you need to write 2 academic papers. For me this was the biggest challenge. But in the end this was a good way to broaden my knowledge on 2 subjects that will help me in my work.
The reason for joining the programme was maybe a little different for me than for most. With more than enough practical experience I found myself lacking the theoretical basis which made me insecure at times. The programme has given me broader theoretical knowledge that helps me in my daily practice. This allows me to make decisions more easily and with more confidence.
During the programme at times it was hard, not only for yourself but also for your loved ones. And you always have the challenge of dividing your time between work, family and study. But in the end it is all worth it!
Yvonne Wijnberg
Treasury Manager at Action
Being a RT opens doors to new challenges more easily. Are you looking for an interim or a permanent position? Do you want to work in a small business or rather prefer a big corporation? If you want to make a switch in your career and you are open for a new adventure than I would highly recommend to contact our partner Treasurer Search. Treasurer Search is a successful treasury recruitment company, founded 10 years ago with consultants that have experience in treasury recruitment up to 20 years.
Do you have any questions about the RT programme? Are you a RT who want to share your career development via an interview? Or do you have any other related questions or remarks about the RT topic? You can contact me directly via:
Kendra Keydeniers
Community & Partner Manager at treasuryXL
| 03-03-2020 | treasuryXL | Cashforce |
Not too long ago, AI seemed a distant dream for creatives in Hollywood and sci-fi movies such as Blade Runner. Today it is all around us. We carry it in our pockets, it harnesses the technology in self-driving cars and it teaches itself how to solve a Rubik’s Cube in under a second. As this technology matures, every company must ask itself the central question: Will artificial intelligence disrupt my industry? And how can it benefit me? While the world of finance may have a conservative ring to it, it is rapidly modifying to a digital future. We can already see artificial intelligence being used in many applications.
Just as Blade Runner was an artistic catalyst for future-noir narratives, so is machine learning essential for the narrative of treasury automation.
For example, machine learning algorithms are incredibly good at recognizing corrupt financial activities or identifying bank fraud since it can handle information thousand times faster than we can blink. Algorithms analyze user actions and distinguish between various types of transactions by gathering a huge amount of data (Big Data). By pointing out odd behavior, it learns over time and becomes even better at it. Another way Big Data is being used, is through credit scoring. By deciding who is eligible for a credit card and who isn’t the algorithm takes over the role of a human analyst.
Not only for analysis purposes but also for saving costs you will find different applications. Today we see customer care or cold calling getting replaced by talking bots, almost indistinguishable from human interaction, helping enterprises save a lot of time and money.
Finance is a fundamental aspect of everyday life for everyday people, all around the world. The endless potential is mesmerizing and what we now see is only the tip of the iceberg. However, the sudden shift is already delivering tangible business benefits. So where does this sudden shift come from? First off, as we’ve seen in part 1, the shift has been going on for well over a decade, silently emerging. The market is becoming more and more electronic, due to the explosion of the amount and speed of data in- and output. Secondly, the cost of running high powered computing networks came down drastically. These two key factors resulted in a trend that has never been seen before.
So what exactly is true of the hype? I’ll be the first one to admit that the proclaimed revolution is often widely exaggerated and ungrounded. When it comes to stock market predictions, a monkey with a dartboard still has the upper hand compared to powerful AI tools in many occasions. Success in human-imitative AI has in fact been limited due to the complexity of human intelligence. It has layers of nuance still to be grasped. In addition, to answer on a human intellectual level is not the same as understanding the meaning behind it. Thus, the challenge of creating humanlike intelligence in machines remains greatly underestimated.
So where is the line between the crystal ball that knows all and digital snake oil? So far, the limiting factor lies in automated and repetitive processes. The basic approach only works in a closed domain with strict rules, such as chess or Go. Now if you add in the word ‘tedious’ to ‘automated’ and ‘repetitive’, you will have the perfect recipe for what is a monotonous task in finance: Managing & updating spreadsheets.
Plumbing the depths of the seemingly infinite sea of spreadsheets is still a known task in treasury, although the negative consequences are common knowledge among business departments. According to our survey, still more than 90% of companies use Excel spreadsheets for their day-to-day operations. Yet, technology doesn’t suffer from some of the dilemmas humans may face in finance which could affect people’s ability to make good decisions: Computers don’t need vacations or sleep, they are less biased and they can do the job more precise. These are obstacles in which AI, in comparison to managing spreadsheets manually, can excel.
Another factor that heavily influences the conversion to artificial solutions is the huge amount of data spread over different branches in a company. Though every department has its own responsibilities, it still has useful data. This untapped information, called Dark Data, has the potential to create a bridge between treasury and other branches, leaving more room for actual analysis between departments within. It goes without saying, AI is remarkable for finance and the promises of this technology, including Big Data, are starting to enter the realms of possibility.
A great example in which artificial intelligence has become an especially important asset is effective cash flow forecasting, one of the essential components of treasury which requires a varied skill set. Despite our best intentions, no human being has the cognitive prowess to deliver a fully accurate prediction of the future. As cash forecasting is in most cases still manually managed through spreadsheets, this often results in forecasting errors. Now, technological improvements are quickly reshaping current business strategies. AI algorithms can be of help in this case to complement the human industry expertise and business acumen, while effectively using historic data to paint a more accurate picture.
So how does this work in practice? One possibility is by analyzing a vast amount of data from your ERP and TMS system and attributing certain weights to time-based (day, week, month, …) or amount-based (customer’s payment behavior) parameters. Through variance analysis, the AI system can continuously learn and adapt to new data and expose hidden patterns, making cash flow forecasts become more accurate over time. This can be combined with statistical methods such as linear regression or time-series analysis to create synergies for accuracy.
Not only will AI help with the processing of data, but it will also change the role of the treasury department altogether. Cash forecasting administrators will be better placed to direct their time to the greatest effect, draw out valuable insights from the AI-produced forecast and tailor the process over time to address any variances. The combined intelligence, in which humans and machines have vastly different thought processes, produces superior results. In the future, AI will become as important as the human component for financial decision-making. Collaboration is key, a crystal clear future is the aftermath.
With the help of an AI-based algorithm, a cash forecast with a considerable accuracy can be constructed.
So Do Androids Dream of Electric Spreadsheets? To dream you need neurons which, until we’ve reached further, are only present in the brain and controlled by the principles of nature. It’s safe to say no blade runner will hunt down your Cash forecasting system (at least for now). But surely the world of finance will be disrupted by the unprecedented AI revolution, one night at a time.
Movie references aside, the better question would be ‘Can my company benefit from this emerging technology?’. Sitting still and letting your corporate competitors gain the first advantage through AI is a risk that every industry should consider for every relevant department involved. For now, we can only know for sure that this unfinished scenario could lead to all sorts of directions. With all these changes happening, you probably do want to be a part of it when the new script on AI in treasury is being written.
| 25-2-2020 | by Kendra Keydeniers |
Cash Management is one of the three primary disciplines of Corporate Treasury. (Risk Management and Corporate Finance are the other two.) Cash management is often described as monetary logistics management. This analogy works quite well. It is the discipline of Treasury that is devoted to the management of planned expenditures, so it is highly focused on operational efficiency and process optimisation. It is about optimising the flow of money coming in from customers, some money going into savings, and other money going out to pay the bills. Since this is such a vital process to any organization, it is not hard to understand how cash management can make or break a company.
Historically, large companies have used multiple bank accounts to gain insight into the activities of their local subsidiaries. In an extreme example, a retail chain might have held a different bank account for each local shop, so that a large retailer could easily hold over 500 accounts! Today, such unnecessary complexity is considered unprofessional. Insight into local activities can be achieved through proper bookkeeping, and extra bank accounts cost extra money. Modern bank accounts also tend to feature more extensive payment capabilities than in the past. A single European bank account, for example, will allow you to send payments within most European countries. Nevertheless, the operations of global businesses still often require multiple bank accounts. In addition, many companies like to hold accounts with banks that are widely recognized by customers in the local market.
In small companies, cash management need not be separate from bookkeeping. The two activities may be done within the same department. In larger companies, though, these activities are specialised. This is because the skill set required for bookkeeping is different from that of cash management. Furthermore, in larger companies it is important to segregate duties for purposes of operational control: the one sending the invoice should not be the one who processes the related payment. Lastly, it is important to mention that in larger companies a distinction is made between cash flows, on the one hand, and income and expenses, on the other. In the financial accounts of a large corporation, revenue is booked when a sale is made. However, it might take some time before this revenue actually reaches the company in the form of cash. Until it does, booked revenue is generally irrelevant to the cash manager. The same is true for expenses. An expense may be booked, but from a Treasury perspective, until an expenditure is disbursed, it is still considered cash on hand.
In smaller companies, cash managers also manage foreign exchange, but FX management is a separate field of expertise. It might be the role of a cash manager to set up bank accounts in various currencies. By doing this, the cash manager lowers operational costs by preventing repetitive transactions between the same currency pairs, which can generate unnecessary fees; but, this is not FX Management. (The FX Manager researches market developments that have an impact on Treasury operations, and often plays a more analytical or strategic role.)
When the IBAN was introduced a few years ago, this new standard for bank account numbers made international electronic payments easier. In theory, it allows companies to work with fewer bank accounts, making cash management easier and cheaper. However, some companies argue that doing local business requires having a local bank, so they maintain multiple international bank accounts, despite the convenience of the IBAN.
Read more about Cash Management and check out these treasury topics as well:
| 24-02-2020 | treasuryXL | Cashforce |
Do Androids Dream of Electric Sheep by Philip K. Dick, adapted to the movie Blade Runner in 1984 (yes, it’s that old), ponders the question whether technology can replace humanity in every aspect of life. Whether advanced technology could attain a comprehensive cognitive interpretation of dreaming is a philosophical conundrum that I’ll leave for the brightest among us. However, while this doomsday scenario in Hollywood movies in which robots rise against their human creators is far from happening, the reality is that a computer has already surpassed the level of strategic thinking of a human being. This rise of artificial intelligence carries the potential to disrupt any industry, including treasury, but often leaves you wondering if the hype lives up to reality.
[Spoiler alert] In the dystopian world of Blade Runner, the protagonist called Deckard, a bounty hunter or “blade runner” hunts outlawed androids or “replicants” while feeling no remorse due to them being machines. An interpretation endorsed by the iconic unicorn dream sequence hints that his human memories might have been artificially implanted, implying he might be an android himself. Is this the course artificial intelligence will eventually take us to?
In 1997 IBM’s computer Deep Blue beat Gary Kasparov, the world champion at that time, in a game of chess. Deep Blue was able to analyze thousands of high-level chess games that were stacked into its system. When proposed with a move, it would choose the best outcome out of different scenarios. By basic number-crunching it was picking out the move that would lead to the best position on the board. This milestone was heralded as a boon for technology and viewed as almost exclusively disruptive for many industries.
Go, an abstract strategy board game invented in China, has simpler rules than chess, but many more moves at each point in the game. Just to give you an idea, the size of possible outcomes is larger than the number of atoms in the universe. Looking too far ahead in the game, or considering all possible moves and counter-moves is therefore nearly impossible. In 2016, distinguished Go player Lee Sedol was put up for the task to beat the next high-tech invention, named AlphaGo. Created by the sharp minds at Google’s DeepMind, its intelligence is based on its ability to learn from millions of Go positions and moves from previous games. Once again, machine triumphed over its human equivalent when it came to strategic thinking.
AlphaZero, released in 2017, is a version of the same program that takes it a step further. It can play chess, Go and other games and is only given the rules of the game, nothing more. By playing millions of games against itself without any previous knowledge of plays, tactics or strategy, it was able to master these games on its own. So how much time went by from the moment they launched AlphaZero to the moment where it achieved a superhuman level of playing Go? Less than 24 hours. Even more baffling is, while humans have been playing it for the past 2500 years, it came up with brand-new strategies that have never been seen before. While it is ‘only’ about fun and games, this sheds a new light on technological concepts that seemed at first like far-out fiction.
Artificial intelligence systems can dazzle us with their game-playing skills and lately it seems like every week there is a baffling breakthrough in the field with mind blowing results. It is almost unthinkable that the finance sector would be untouched by the rise of AI, any sector for that matter. Nonetheless, with the present hype around it, many of the used concepts and terminology seem to be used carelessly, which makes it hollowed and deprived of any meaning. You have probably heard of the terms “machine learning” and “deep learning”, sometimes used interchangeably with artificial intelligence. As a result, the difference between these concepts becomes very unclear. To understand this distinction and why AI will disrupt current technologies, we have to understand where it comes from.
Simply put, AI involves machines that can perform tasks that are similar to human tasks. A very broad definition which can go from simple solutions such as automated bank tellers to powerful and complex applications such as androids, which inspired the movie Blade Runner.
Surprisingly, the script on AI arises from a time when James Dean was rocking the screen and Elvis was celebrating his first “Blue Christmas”. While the statistical framework is based on the writings of French Mathematician Legendre from 1805, most AI models are based on technology from the 50’s.
1950, the world-famous Turing test is created by Alan Turing (who will soon be commemorated on the new £50 note). The test reflects on the question whether artificial intelligence is able to appear indistinguishable from a human in terms of thought and behaviour.
1951, the first artificial neural network was created by a team of computer scientists: SNARC (Stochastic Neural Analog Reinforcement Computer). They attempted to replicate the network of nerve cells in a brain. It imitated the behaviour of a rat searching for food in a maze. This was largely an academic enterprise.
SNARC computer
In the same way, 1952 rouses the birth of the first computer learning program or machine learning by Arthur Samuel. The program played checkers and improved at the game the more it played. Machine learning, a subset of AI, is defined as the ability to learn without being explicitly programmed what to “think”. It enables computers to learn from their own mistakes and modify to an altering environment. Machine learning also includes other technologies such as deep learning and artificial neural networks. Nowadays this technology can, among other things, use data and statistical analyses to predict possible future scenarios such as for Cash flow forecasting.
The Dartmouth Summer Research Project was a 1956 summer workshop and widely considered to be the starting point of artificial intelligence as a scientific field. With this uprising of technology there came a lot of excitement for the potential of automation in finance and treasury. It was believed to help accountants and bankers speed up their work. But if wishes were horses, beggars would ride. And in this case, androids would be riding along with them. Unfortunately, a reduced interest in the field and many failed projects leave artificial intelligence stranded in what is called the ‘AI winter’.
Luckily humans are not one trick ponies, so our story doesn’t end here. After a period of economic & technological proliferation in the 1980’s, Expert Systems found their way into the world of finance. These are computer systems that are capable of decision-making on the level of a human expert having been designed to solve complex problems. But when push came to shove, the technology wasn’t mature enough and didn’t meet client’s demands.
In 1991 the World Wide Web was opened to the public. It’s the start of the data revolution. In 2005, it reached 1 billion people and today more than half of the world’s population is connected to the internet.
Coming back to our first example, it was in this period (1997) that Deep Blue challenged the capacity of the human brain and proved it could think more strategically than a human being.
Today AI is demanding so much computing power that companies are increasingly turning to the cloud to rent hardware through Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) offerings. That’s why around 2006, players such as Amazon Web Services (AWS) opened up its cloud environment to broaden the capacity of AI even further.
In the same year, Geoffrey Hinton coined the term “deep learning”, helping the progress of operating AI applications in the real world. This brought the world one step closer to bridging the fuzzy gap between humans and androids.
2015, AlphaGo is introduced to the world. Two years later in 2017, its successor AlphaZero sees the light of day.
2019, the first picture of the black hole M87 the constellation Virgo is rendered through artificial intelligence opening the door to new knowledge in the universe. The path of AI took us a giant leap forward, but we’re far from the finishing line. Roughly 90% of the universe exists of dark matter or dark energy that leaves us in confusion. Accordingly, a similar percentage of untapped dark data, the fundamental building block to understand a company’s future, isn’t being used.
29-01-2020 | Treasurer Search | treasuryXL
The Treasurer Front Office is part of a team of three (Treasury Operations), in this team he will be the medior and take the lead in front office activities such as:
Our client offers a market level salary, the expected annual base salary will be about €65K. For interested candidates who qualify, a more elaborate job description is available. The Treasurer Test might be part of the recruitment process.
| 28-1-2020 | treasuryXL | Cashforce |
We are very proud at our partner Cashforce. What a year it has been for Cashforce! From opening new offices, to processing millions of transactions, Cashforce successfully round up 2019. More specifically last year, Cashforce:
| 7-1-2020 | treasuryXL | Cashforce |
For many multinational corporations, effectively managing their working capital across numerous regions can be a significant challenge. Additionally, optimizing cash streams in a complex data environment can be a time-consuming process. The same issue goes for Dawn Foods, a global B2B bakery ingredient supplier with multiple entities & finance departments. With more than 50 locations worldwide, serving products in 106 countries and 40.000 customers served globally it is one of the main players in the food industry.
Starting 2015 the company started a change management process to turn Dawn Foods into a more cash orientated company. A taskforce was created supported by Bart Messing, European Treasury Manager and Marc Kersten, European IT director, sponsored by the VP Finance & IT Michael Calfee.
Their key objective was a 10% year-over-year reduction of Net Working Capital Days.
One of the essential building blocks of this plan was implementing a 24/7 working capital tool whereby the KPI’s could be reported into several dimensions that are relevant to the different business units and functions. The different dimensions are important, as the business will only support improvement processes and accept targets unless the KPI’s are measured in relevant dimensions.
After careful comparison based on an extensive survey under key business people between internal/external tools on quality requirements, costs and potential benefits, Cashforce, a ‘next-generation’ cash & working capital analytics solution, came out on top. By designing a proof of concept, in cooperation with the internal IT department, a successful solution was reached. After the implementation the results were already significant in a short time: an instant working capital dashboard that provides 24/7 insights, as well as with simulations in different dimensions that are relevant for each department.
By providing the right technology, in combination with an unmatched cross-departmental cooperation, Dawn Foods was able to build a bridge between its finance department and the rest of the departments, thus reducing complexity and increasing visibility and insights.
This led to millions of dollars saved since setting up the new project (over a three-year period). The cash that was freed up has in the meantime been used to finance a strategic acquisition.
6-1-2020 | by Kendra Keydeniers | Arnoud Doornbos | Ilfa Group
On January 23rd, 2020 Ilfa and Global Reach are organising a masterclass on foreign exchange risk management. FX experts Michael Jansen of Global Reach and Arnoud Doornbos of Ilfa will guide you through the design of a FX risk management program and demonstrate which opportunities a program like this has for your organisation.
Go to event and register for the masterclass. Places are limited so we recommend to secure your spot today.
treasuryXL is delighted to share our exclusive interview with one of the organizers and FX specialist, Arnoud Doornbos of Ilfa.
Foreign exchange risk management strategy or FX hedging strategy are terms used to define all the measures devised by businesses or investors to protect the value of their cash flows, assets or liabilities from adverse fluctuations of the exchange rate.
Hedging is used by companies to manage their currency exposure. If a company needs to buy or sell one currency for another, they are exposed to fluctuations in the foreign exchange market that could affect their costs (or revenues) and ultimately their profit.
By booking a hedge, companies protect an exchange rate against a specified sum of currency for a desired timescale, providing companies with certainty.
There are a range of products that can be used for hedging, depending on the companies objective and the exposure they are trying to protect.
Typically, a company would hedge their foreign exchange (FX) exposure to protect its profit margin from market volatility. Hedging is most common in companies that have an exposure to a secondary currency and have fixed prices on their products or services.
Foreign Exchange exposure is classified into three types:
Currency risks can have various effects on a company, whether it operates domestically or internationally. Transaction and economic risks affect a company’s cash flows, while transaction risk represents the future and known cash flows. Economic risk represents the future (but unknown) cash flows. Translation risk has no cash flow effect, although it could be transformed into transaction risk or economic risk if the company were to realize the value of its foreign currency assets or liabilities. Risk can be tricky to understand, but by breaking it up into these categories, it is easier to see how that risk affects a company’s balance sheet.
Businesses that operate internationally or domestically must deal with various risks when trading in currencies other than their home currency.
Companies typically generate capital by borrowing debt or issuing equity and then use this to invest in assets and try to generate a return on the investment. The investment might be in assets overseas and financed in foreign currencies, or the company’s products might be sold to customers overseas who pay in their local currencies.
Domestic companies that sell only to domestic customers might still face currency risk because the raw materials they buy are priced in a foreign currency. Companies that do business in just their home currency can still face currency risk if their competitors operate in a different home currency.
One of the critical elements of the currency risk that are overlooked is the correct identification of the type of FX risk. A distinction must be made between certain and uncertain cash flows in FX. With certain cash flows, the company has to deal with a linear risk that must be covered with a linear financial hedging instrument, an FX forward. With an uncertain cash flow, risk profile is not linear and it is dangerous to use FX Forwards to hedge. FX Options are better financial products to hedge.
If the company does not include FX Options in its Treasury policy, the second best option is to use FX forwards for, for example, 50% of the principal sum of the underlying risk.
Anticipated and committed exposure cycle
There are many ways to measure foreign exchange risk, ranging from simple to quite complex. Sophisticated measures such as ‘value at risk’ may be mathematically complex and require significant computing power.
Register of foreign currency exposures
A very simple method is to maintain a register of exposures and their associated foreign exchange hedges. Basically the details of each hedge are recorded against its relevant exposure. This type of approach may also assist with compliance with accounting standards.
Table of projected foreign currency cashflows
Where the business both pays and receives foreign currency, it will be necessary to measure the net surplus or deficit for each currency. This can be done by projecting foreign currency cash flows. This not only indicates whether the business has a surplus or is short of a particular currency, but also the timing of currency flows.
To properly determine the FX risk, account must be taken of the differences in sensitivity of the incoming and outgoing FX cash flows.
Sensitivity analysis
A further extension of the previous measure is to undertake sensitivity analysis to measure the potential impact on the business of an adverse movement in exchange rates. This may be done by choosing arbitrary movements in exchange rates or by basing exchange rate movements on past history.
Value at risk
Some businesses, particularly financial institutions, use a probability approach when undertaking sensitivity analysis. This is known as ‘value at risk’. While it is useful to know the potential impact of a given change in exchange rates (say a USD one cent movement) the question will arise: how often does this happen? Accordingly, we can do a sensitivity analysis using past price history and apply it to the current position. Then, given the business’s current position, and based on exchange rates observed over the last two years, it can be 99 per cent confident that it will not lose more than a certain amount, given a certain movement in exchange rates. In effect, the business has used actual rate history to model the potential impact of exchange rate movements on its foreign currency exposures.
Transaction risk is often hedged tactically (selectively) or strategically to preserve cash flows and earnings, depending on the companies treasury view on the future movements of the currencies involved. Tactical hedging is used by most firms to hedge their transaction currency risk relating to short-term receivable and payable transactions, while strategic hedging is used for longer-period transactions.
Translation, or balance sheet, risk is hedged very infrequently and non-systematically, often to avoid the impact of possible abrupt currency shocks on net assets. This risk involves mainly long-term foreign exposures, such as the firm’s valuation of subsidiaries, its debt structure and international investments. However, the long-term nature of these items and the fact that currency translation affects the balance sheet rather than the income statement of a company, make hedging of the translation risk less of a priority for management. For the translation of currency risk of a subsidiary’s value, it is standard practice to hedge the net balance sheet exposures, i.e., the net assets (gross assets less liabilities) of the subsidiary that might be affected by an adverse exchange rate move.
Translation risk is for a large part a Finance issue. Within the framework of hedging the exchange rate risk in a consolidated balance sheet, the issue of hedging a companies debt profile is also of paramount importance. The currency and maturity composition of a firm’s debt determines the susceptibility of its net equity and earnings to exchange rate changes. To reduce the impact of exchange rates on the volatility of earnings, the company may use an optimization model to devise an optimal set of hedging strategies to manage its currency risk.
Foreign exchange risk management is thus fundamental but it is often considered to be too complex, expensive and time-consuming. Nonetheless, with a simple, tailored monitoring activity, it can neutralise currency fluctuations and bring the following benefits: Securing marketing margins. Optimising cash-flow estimates.
This Forex market is open 24 hours a day, 5 days a week and with a daily volume of $ 6.6 trillion the most liquid and largest financial market in the world. For most companies, FX risks are non-core risks The objective of most companies is not to be an FX trader. By correctly identifying and quantifying the FX risks and then neutralizing them with the correct financial FX hedging instruments, companies will have little or no trouble with currency fluctuations on the financial FX markets. The implementation of the correct procedures forms the basis of good FX risk management and will make opportunistic behavior of management disappear.
Associate Partner Ilfa
FX specialist