Cash management – Mandatory truck system

| 9-8-2017 | Douwe Dijkstra |

As an interim treasurer, several times when I commence a new assignment at a new client for a cash management implementation the bank selection for the cash management solution to be implemented has already been done. Not by the treasury (or any other) department, based on a request for proposal or any other selection criteria but as a result of the mandatory truck system (“verplichte winkelnering”).

The bank, or in case of a syndication the banks, already defined in the (syndicated) facility agreement which bank(s) will operate the borrowers cash management.

It goes without saying that this obligation means that not always the best choice for the company has been made. The “best cash management bank” can be different for each and every company (although some banks may pretend to have the best solution in all areas for all companies). Important criteria are whether a company is centralized or decentralized, what specific products the client requires from the bank, the price list of the bank, the foot print of the bank etc. etc.

It’s my observation that officers negotiating the (re)financing consider cash management as the way it is described e.g. “side business”. Banks try to make the decision makers for the facility agreement believe that they do not earn anything on it. Thus, the circle is complete.

Douwe Dijkstra

 

 

Douwe Dijkstra

Owner of Albatros Beheer & Management

 

 

SWIFT Blockchain POC: Enhanced cross-border payments

| 8-8-2017 | Carlo de Meijer |

Early July SWIFT announced that 22 global banks recently joined its Blockchain proof of concept (PoC) initiative introduced in January this year in collaboration with six leading correspondent banks (ANZ, BNP Paribas, BNY Mellon, RBC Royal Bank and Wells Fargo). The PoC is part of SWIFT’s ‘gpi’ (global payments innovation) service, the new standard for cross-border payments, aimed to “re-arm the correspondent banking system for a new age of technological disruption”. 

This Blockchain PoC initiative is designed to explore whether blockchain technology can help banks to improve the reconciliation of their international nostro accounts in real-time, optimising their global liquidity. If so, that would be a break through event for both SWIFT and blockchain.

Present state

Currently, banks cannot monitor their account positions in real-time due to lack of intraday reporting coverage. The present pain points banks currently experience when making cross-border payments center around a lack of visibility into the end-to-end transactions lifecycle. Under the current correspondent banking model, banks need to monitor the funds in their overseas accounts via debit and credit updates and end-of-day statements. The maintenance and operational work involved represents a significant portion of the cost of making cross-border payments.

“Cross border payments are like a black box for us. We don’t know when the funds will be credited, we don’t know what fees will be charged and we also have problems with reconciliation”. states Martin Schlageter, head of Treasury Operations at Swiss healthcare conglomerate Roche.

As such, the POC recognises the need for banks to receive real-time liquidity data in order to manage funds throughout the business day.

SWIFT GPI service

The PoC is being undertaken as part of SWIFT gpi, a new service that “may revolutionise the cross-border payments industry by combining real-time payments tracking with the speed and certainty of same-day settlement for international payments”.

The SWIFT gpi should be seen as SWIFT’s response to the problems they faced after a series of attacks events that showed that “all was not as secure as everyone believed”. SWIFT gpi initiative was first announced at the annual Sibos conference in 2015. The project went into live production in January this year to address core problems related to speed, transparency and traceability of cross border payments.

SWIFT gpi not only delivers a much-needed improvement in the speed of transaction, but also improves overall customer experience by creating predictable settlement times and clear statuses, through additional (unaltered transfer of) information on remittances and transparency around the FX rates and fees applied throughout the payment cycle.

“The ability to deliver enhanced remittance information alongside the payment will help customers make better decisions along the payment chain, while also creating better efficiency opportunities. The decision to make gpi available in the “cloud” is also exciting, and we anticipate this will lead to the development of entirely new services, that combine SWIFT gpi with capabilities provided by banks, clients and vendors.“ says Tom Halpin, Global Head of Payments Product Management, HSBC Global Liquidity and Cash Management

Key features

Key features of the SWIFT gpi service include a secure tracking database in the cloud accessible via APIs, and enhanced business rules.

Cornerstone of SWIFT gpi is the highly innovative new cross-border TRACKER, a special tracking feature that enables international payments to be traced real-time. It allows banks to provide corporate treasurers with a real-time, end-to-end view (visibility) on the status of their payments, including confirmations of the amount credited to the beneficiaries’ account. The Tracker is available via an open API, making it compatible with proprietary banking systems worldwide – helping to ensure maximum impact of gpi benefits at a greater adoption speed.

A second key feature is the OBSERVER, a quality assurance tool that monitors participants’ adherence to the gpi business rules. Gpi’s transparency ensures that remittance information such as invoice references, is transferred unaltered to recipients.

Gpi uptake

Membership is open to any supervised financial institution that agrees to comply with SWIFT’s business rules. But also non-bank organisations can join SWIFT gpi initiative. The SWIFT gpi service has received considerable bank support across the globe. And the number of global transaction banks that are actively using SWIFT’s gpi service is continuously growing. Since its launch the number of banks that are live with SWIFT gpi has risen beyond 100, and hundreds of thousands GPI payments have already been sent across 85 country corridors. This represents more than 75% of all SWIFT cross border payments.

“The increasing number of banks going live on this service addresses the demands of corporate treasurers. Hence, banks cannot afford to not join the initiative and go live as soon as possible. Our expectation is that all of our cross-border payments will be end-to-end Swift gpi payments in the future.” Group of Swiss corporates

SWIFT expects that numerous additional banks will join the gpi initiative in the coming months. The ambition is for all countries to be live by the end of 2017.

Phased approach

Next to the design of the second phase of SWIFT gpi, that is already underway focusing on additional digital capabilities and further enhancements such as ‘a rich payment data service’, for its third gpi phase SWIFT started exploring the potential of new technologies such as Distributed Ledger Technology (DLT), including blockchain, through a Proof of Concept (PoC).

SWIFT Blockchain PoC

Launched in January 2017 with six founding banks the SWIFT Blockchain PoC initiative, designed to validate/explore whether blockchain can be used by banks to improve the reconciliation of their international nostro accounts (these are accounts that a bank holds in a foreign currency in another bank to handle international financial transactions for their customers) (these are accounts that a bank holds in a foreign currency in another bank to handle international financial transactions for their customers) in real –time, optimising their global liquidity. At its core, the PoC builds on SWIFT’s rulebook as part of the intraday liquidity standard gpi.

This SWIFT Blockchain PoC initiative aims to help banks overcome significant challenges in monitoring and managing their international nostro accounts, which are crucial to the facilitation of cross border payments.

“Whilst existing DLTs are not currently mature enough for cross-border payments, this technology, bolstered by some additional features from SWIFT, may be interesting for the associated account reconciliation,” “This PoC gives us the opportunity to test DLT and determine if it can be applied to this particular use case.” Wim Raymaekers, Head of Banking Market and SWIFT gpi at SWIFT

Characteristics

In developing the POC, SWIFT is leveraging the Hyperledger Fabric v1.0 technology, and combining it with key SWIFT assets, to bring it in line with the financial industry’s requirements.

“SWIFT will leverage its strong governance, PKI security scheme, BIC legal identifier framework and liquidity standards expertise to deliver a distinctive DLT PoC platform for the benefit of its community.” Damien Vanderveken, Head of R&D, SWIFTLabs and User Experience at SWIFT 

The PoC application will use a private permissioned blockchain in a closed user group environment, with specific user profiles and strong data controls. User privileges and data access will be strictly governed. This to ensure that all the information related to nostro/vostro accounts is kept private. Only account owners and its correspondent banking partners will see the details.

Collaboration

SWIFT gpi member banks can apply to participate in this Blockchain PoC. Next to the 6 founding banks, another 22 banks have recently joined the SWIFT blockchain PoC. They include include:

ABN AMRO Bank; ABSA Bank; BBVA; Banco Santander; China Construction Bank; China Minsheng Banking; Commerzbank; Deutsche Bank; Erste Group Bank; FirstRand Bank; Intesa Sanpaolo; JPMorgan Chase; Lloyds Bank; Mashreq Bank; Nedbank; Rabobank; Société Générale; Standard Bank of South Africa; Standard Chartered Bank; Sumitomo Mitsui Banking Corporation; UniCredit; Westpac Banking Corporation.

“Collaboration is the cornerstone of innovation,” “This new group of banks allows us to greatly extend the scope of multi-lateral testing of the blockchain application and thus adds considerable weight to the findings. We warmly welcome the new banks and look forward to their insights”  says Wim Raymaekers, head of banking markets and SWIFT gpi at SWIFT.

Process

Moving forward, the SWIFT PoC Blockchain application will undergo testing, with the results scheduled to be published in September and presented at Sibos in Toronto in October. Working independently of the founding banks, the 22 institutions will act as a validation group to test in a deeper way the PoC’s Blockchain application, that is currently under development by SWIFT and the group of six founding banks. They will evaluate how the technology scales and performs.

Benefits

For banks

The potential business benefits ensuing from a successful SWIFT blockchain POC may be significant. If it proves to enable banks reconcile those nostro accounts more efficiently and in real time, that may lower costs and operational risk.

“The potential business benefits ensuing from the PoC are clear,” “If banks could manage their nostro account liquidity in real-time, it would allow them to accurately gauge how much money is required in each account at any given point, ultimately enabling them to free up significant funds for other investments.” Damien Vanderveken, head of R&D, SWIFTLab and UX at SWIFT.

It brings together banks worldwide who want to offer an enhanced cross-border payments experience to their corporate clients. By being part of SWIFT gpi, banks may improve the quality of their correspondent relationships and networks, helping to reduce risks and management costs and improve compliance.

“Transparency is key to a good end-to-end client experience. SWIFT gpi is a significant step in the evolution of correspondent banking, which remains the primary means through which cross-border payments are delivered worldwide. Bank of America Merrill Lynch is pleased to be working with like-minded institutions around the world to better serve each other and our respective customers.” states Greg Murray, head of Global Product Management for High Value Payments and FI/NBFI Products in Global Transaction Services at Bank of America Merrill Lynch.

For corporate treasurers

SWIFT gpi may enable corporates engaged in international trade to get paid for services, or delivery of goods, in a more timely fashion, enabling a faster supply chain process. It also enables a more accurate reconciliation of payments and invoices, optimizes liquidity with improved cash forecasts and reduces exposure to FX risks with same-day processing of funds in the beneficiary’s time zone.

“Being part of SWIFT gpi, and working with our industry counterparts, is giving correspondent banks a platform to examine and refine current processes, and to collaborate and explore different, more efficient ways of doing things. Ultimately, our clients will benefit most from this initiative,” Kent Marais, head of TPS product management at Standard Bank SA.

SWIFT and the banks have designed the gpi services so that banks have flexibility in how they offer the new services. They can deliver the gpi service in very different ways. Services could potentially include enhanced invoice presentment and reconciliation to facilitate financial supply chains, exchange of supply chain documentation to improve global trade, exchange and interactive enquiry of account and processing conditions to improve end-to-end straight through processing, and providing additional party and transaction information to support compliance and sanctions screening of cross-border payments.

Enhanced cross-border payment service

“SWIFT has addressed several of the pain points corporates have had with cross-border payments,” “Changes to existing corporate payments infrastructures should be very limited, if any. So hopefully, corporates won’t need to make any major investments to benefit from smoother cross-border payments.” says Magnus Carlsson, AFP’s manager of treasury and payments

Given the size of the number of banks and corporates participating in SWIFT gpi, the SWIFT Blockchain PoC may face the challenge of scalability. If that could be solved in a successful way it may be another prove of the viability of blockchain and DLT to enhance cross-border payments.

 

Carlo de Meijer

Economist and researcher

 

 

 

More on blockchain from this author:

Blockchain: accelerated activity in trade finance

Blockchain and derivatives: Re-imagining the industry

The digital trade chain: The blockchain train is rolling

Please feel free to visit the treasuryXL/articles page to see more articles.

 

Graphs with no time line – why and how

| 7-8-2017 | Lionel Pavey |

A key role within the Treasury function is providing forecasts to the directors and management. Graphs are a frequently used tool of course.
When constructing graphs it is normal to put time on the horizontal x axis and read the prices from left to right – from old to new. Visually, this appeals to us as we normally read from left to right. However, when the price does not change much for a long period of time the graph no longer looks fluid – there is a period of activity, followed by a long period of almost standing still, followed by another period of activity. To try and eliminate this period of inactivity whilst still presenting the data requires an approach where sequential time is removed from the equation. This brings us to the last article in this series.

The following two graphs ignore time and focus purely on changes in the price that have been filtered to meet specific criteria.

Renko Charts

 

Prices are represented by blocks – hollow for upward movements and solid for price falls.

Every block has a predefined value – if we were showing interest rates a block could represent 5 basis points. If we had an upward price movement this means that the following upward block can only been drawn once prices have risen more than 5 basis points from the last block. If the price moved up 4 basis points and then dropped by 3 basis points, no additional blocks would be added to the graph.

Blocks are plotted at a 45 degree angle showing upward and downward sloping price changes.
Price reversals are shown when prices have moved more than 2 blocks in the opposite direction. Yet again if we had an upward slope and the price was 1.25 (our blocks are set to 0.05 or 5 basis points) we would require a downward movement of more than 0.15 (15 basis points) to 1.10 to draw 2 solid blocks downwards.

What remains is a very smooth representation of price movements with a uniform value for every block, whilst filtering out smaller movements that have been filtered out by the conditions set on block size.

Point and Figure Charts

Price changes are represented by vertical columns – X’s for rising prices and O’s for falling prices.
As with Renko charts, the X’s and O’s have a predetermined size and a price reversal is shown when prices change by 3 boxes as opposed to 2 on a normal Renko chart. When direction changes a new column is drawn to the right of the present column. Otherwise, the same criteria is applied to both charts except point and figure show true vertical columns as opposed to 45 degree lines.

So why would someone look at prices in this particular way? Such a chart does not necessarily show the latest price – the predefined filters ensure that only price changes that meet the criteria are shown.

The main advantages include:

  • A constant filter that reduces the noise associated with normal time charts
  • Analysis is based only on movement – not on time
  • Perceived support and resistance levels are easier to see
  • The current trend is very clear to see

All the techniques shown in this series are applicable to everyday analysis and everyone has their favourite approach. Some like to see all data, whilst others prefer to see filtered, smoother data. The eternal question when looking at charts and seeing the current trend is to ask “where will the price go?” Initially, the immediate answer is that price will follow the current trend until such time as it does not anymore. This might seem a cheap flippant answer, but it is the truth. We have firmly established that we need to know the price in the past to determine if the present price movement is in a clearly established trend. If we knew nothing about the price in the past it would be pure guesswork to say which way the price would go?

We could still be wrong however, but at least we can establish why and how we made our opinion.

No chart or charting system can clearly determine what the future price will be with 100 per cent accuracy. By following the trend we can at least say what the current market direction is, without being able to clarify, purely on price, when the market will change direction.

Charts that eliminate time make it easier to see where the top and bottom of the market prices have been established. Therefore, if we are in an upward trend and approaching a market high that has been reached twice before, we can state with a reasonable amount of confidence that we are approaching a level that the market has tested twice before but not been able to break above. This would imply, on a technical analysis, that there is perceived resistance in the market to taking the price above the previous high.

However, a word of caution when using charts.
The best analogy I have ever heard for not relying 100 per cent on charts is as follows:

Would you sit behind the steering wheel of a vehicle and drive forward whilst the windscreen was blacked out and only have the rear view mirror to show you where you have been and only have that information to decide when you had to steer?

There is no system that can guarantee telling you what the future price will be. Analysis has to be taken with a pinch of salt but, any market professional should be able to perform analysis. If you can not analyse then you can not predict.

Lionel Pavey

 

Lionel Pavey

Cash Management and Treasury Specialist


You might have missed the first two articles of this series and can find them here:

Treasury for non-treasurers: Data analysis and forecasting – seeing the future by looking at the past (Part I)

Treasury for non-treasurers: Data analysis and forecasting – Seeing the future by looking at the past (Part II)

 

Payment Processing in 2017: FX-MM’s survey and the results

| 4-8-2017 | treasuryXL | FX-MM |

For almost 25 years, FX-MM  publishes about the issues that bankers, corporate treasurers, fund managers, traders, brokers and technology vendors face in the international financial markets. With a focus on treasury, trading and technology, FX-MM serves all of these sectors effectively with their magazine on a monthly basis. Earlier this year they asked their community to take part in their payments processing survey, which they had conducted together with Accuity. 215 senior professionals involved in payments processing from the banking and corporate sector, ranging from the largest multinationals to SMEs, responded.
FX-MM now published a summary of the results online, which we summarize for you.

According to FX-MM’s editor Peter Graham the survey shows the ‘critical importance of payments data accuracy for banks and corporates as they seek to grow their businesses and increase their presence across the world.’

FX-MM made a difference between financial institutions and corporations in their survey. To be categorised in the corporate category, the respondent must work for a non-banking organisation that makes a substantial amount of payments through their daily operations. Typically this includes a range of payroll, supplier, and partner transactions and was referred to as ‘corporates’.

95 top-level corporate respondents from a wide range of industries took part in the survey, with the majority either being treasurers or chief financial officers.

The 120 respondents from the banking sector represented individuals working in all areas of payments processing, from corporate banking, payment operations, and electronic payments, to remittances, settlements and operations. Much like the corporate respondents, the banking respondents represented a wide range of organisations, .

Global reach

Geographically, respondents to the survey were mainly based in Europe and North America. 25% of bank respondents, and 20% of corporate respondents, however, were based outside these mature markets and featured representatives from all regions across the globe.

The majority of banks – 39% – are active in at least 15 regions, and at least 20% serve more than 50 geographic markets. Since only 21% of the banks only process payments domestically, these results highlight the need for accurate payments data across a range of regions. The survey highlights the frequency in which banks today are operating in emerging markets. Indeed, 61% of banks said they often or always route payments through Eastern Europe, 56% through Asia Pacific, 37% through Africa and 35% through Central and South America.

The need for global reach, and the increasing internationalisation of today’s business world, is also reflected in the corporate world. While just 9% of corporate respondents to the survey only send or receive payments domestically, 72% send or receive payments to up to 50 countries.The rest % send payments to more than 50 countries.

It seams that corporates are even more likely to expand their operations internationally than banks, with 64% saying they intend to enter new geographic markets. That implies that a wide scope of payments data is critical as corporates plan for the business needs of the future.

Why does payments data accuracy matter more in today’s market landscape?

Sarkis Akmakjian, Senior Director, Product Management at Accuity, explains: 

‘Evolving business strategies combined with the demand to send payments into emerging markets drives the need for accurate payments that go through every time and in any location. Yet, underpinning each successful transaction is critical financial and routing data. It is not surprising, then, that many financial institutions and multi-national organisations have become more concerned with ensuring this critical information is kept up to date.’

For multi-national corporations, accurate payments data is becoming a key factor in achieving strategic objectives. As the survey highlights, a growing number of global corporations (64%) are expanding their supply chain, customer base and workforce into new markets. However, this cannot be fully achieved if payments cannot be processed with certainty into those countries.

Many respondents (61%) acknowledge that their business could take advantage of new opportunities if it was less of a challenge to process payments. Therefore, they are most helped when payments data is delivered through tools that enable efficient processing.

For financial institutions, accurate routing data drives metrics like straight-through-processing (STP) rates and client satisfaction. In fact it takes fewer delayed payments which damage relationships with clients in a  financial market that is growing more competitive.

For both financial institutions and global businesses, the ability to overcome global payments challenges grows more important. Both types of businesses are looking to the accuracy of their bank and routing data to meet the pressure for accurate payments.

Mission critical for corporates

Significant consequences for corporates arose from not having complete and accurate payments data for their suppliers and vendors. 58% said it led to too much time spent on manual research to correct data errors, while 31% said it led to a lack of trust and posed a reputation risk with vendors.

The survey revealed that there are clear challenges for corporates as they onboard and maintain payments data for their suppliers and vendors. The corporates indicate that problems arose when vendors did not keep them up to date when their payments data changed, or when vendors did not supply all the information they needed. Corporates also stated that their onboarding process was too arduous and that they did not catch errors in vendor data.

Despite these challenges, the importance that corporates attach to payments processing should not be underestimated. 82% of respondents said the ability to process payments accurately had a direct effect on their organisation’s current success and future growth, while 62% said their organisation could take advantage of more new business opportunities if processing payments were less challenging.

The survey revealed the biggest challenges corporates face in keeping bank and payments up to date, namely  manual entry of data that led to errors in their master database and ensuring that payments met complex country-by-country requirements and language requirements.

Bank STP concerns

For banks, 57% said their straight-through-processing (STP) rate for payments was less than 95%. Clearly, this is a cause for concern. The most common cause of payment failure or delay at banks was incorrect or missing beneficiary details, missing or incorrect clearing system details or missing or incorrect account numbers.

The survey also revealed bank priorities for payment processing in 2017. . More than half of the respondents said reducing cost, time and effort was a priority. 42 % cited the need to minimise the risk and exposure of failed payments. A larger group mentioned the automating of data and workflow to save time. 33% of the banks in the survey wanted to protect organisational reputation and existing customer relationships.

It became obvious that banks are feeling the pressure as far as payments processing is concerned.

Without doubt payments are a vital instrument to keep the global economy running. Banks and corporates face challenges. Inaccurate data is clearly an obstacle to increase straight-through-processing and to realise the full benefits of payments automation. Overcoming these inaccurate data issues will reduce costs for banks and corporates and also place them in a better position to take advantage of business opportunities as they expand into the global markets.
(Source: FX-MM)

You can read the complete article about the survey results on FX-MM by following this link.

Annette Gillhart – Community manager treasuryXL

 

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Re-inventing treasury workflows: Smart Treasury

| 3-8-2017 | Nicolas Christiaen | Cashforce | Sponsored Content |

While the role of the treasurer is changing, it becomes increasingly challenging to maintain the current workflows and simultaneously take on new demanding tasks. One of these often manual and time-consuming tasks is risk management. As seen in, among others, this year’s Global Treasury Benchmark Survey of PwC, the registration and management of financial instruments stands among the top 3 challenges on the agenda of the surveyed treasurers. In this article, we take a more in-depth look at possible optimizations in some key treasury workflows.

 

 

 

 

 

 


Example FX management workflow

Hedging your FX exposure risk made easy

A common problem is the lack of visibility on the existing (global/local) FX exposure risk.
In order to calculate the FX transaction risk, transactional data from the TMS & ERP systems need to be consolidated effectively. Typically, this happens to be a (very) painful exercise. With Cashforce, however, using our off-the-shelf connectors (for ERP & TMS) and our full drill-down capabilities, you have all FX exposures at your fingertips.

 


FX Exposure Management – Current positions & exposures

 

But there is more to it. Imagine that linked to your FX exposure, an automated proposal of the most relevant FX deal would be generated to properly hedge this risk. A grin from ear to ear you say?


FX Exposure Management – Suggested hedge

 

And what about forecasting FX exposures? It’s now all within reach!

FX Exposure Management – Future positions & exposures

 

Whether you choose to take on an intercompany loan, a plain vanilla FX forward or another more exotic derivative product, chosen deals could then be automatically passed on to your deal transaction platform, to effectively execute the deal without any hassle. After execution, deals will automatically flow back into the system. Consequently, a useful summary/overview will be generated to effectively manage all your financial instruments.


Workflow integrated cash forecast

Finally, integrated cash management

New financial instruments / deals will generate a set of related cash flows. Ideally, these are directly integrated in your cash flow forecasts. In Cashforce, this data is automatically integrated within the cash flow forecast module, and will be put into a dedicated cash flow category. Learn more one how to set up an effective cash forecast in this article or this webinar.


Cash flow forecast overview

 

The analysis possibilities are now limitless, thanks to the ability to drill down to the very transactional-level details. The real number crunchers strike gold here: the analysis features open doors to unlimited in-depth analysis and comparison of various scenarios (E.g. the simulated effects of various exchange rate movements).


Drill-down to the transaction level

 

Using our big data engine, the delivery of rich and highly flexible reporting is facilitated. It’s fair to say that the typical SQL server (which currently 95% of the TMS systems use) can’t hold a candle to this. Through an advanced ‘self-service’ interface, users can drill down completely into respective amortization tables, historical transactions and effortlessly create customized reports and dashboards. We’ll talk more about why we believe Big Data engines are crucial for any Treasury software in our next blog.

Integration with ERPs & payment platforms

Next to this, Cashforce will automatically generate the accounting entries (in the format of your ERP/accounting system) related to your deals. The appropriate payment files will be generated in a similar fashion.

So…

As might be clear after reading this article, we strongly believe that integrated data flows & a Big Data engine are the foundation of a new type of Treasury Management System that runs like clockwork and can serve effective treasury departments, but also renewed finance/controlling/FP&A departments.

You are curious to hear more about effective treasury management? We’ve recently recorded a webchat on how to set up an efficient cash flow forecast process.

 

Nicolas Christiaen

Managing Partner at Cashforce

 

Bitcoins or banks, who is taking care of the business?

| 2-8-2017 | Hans de Vries |

Banks have long been target of wild spread ideas that their role as facilitator in the (inter) national money transaction industry will soon be overtaken by new Fintech initiatives like PayPal, Bitcoin and recently Ethereum. The idea behind these new technologies is that the Trusted Third Party (TTP) role of the conventional banks which is crucial for the operational day to day operations of the economic systems can be overtaken by the new block chain technology. Main advantages are clear: transactions are no longer limited by timing (no dependency on the operational boundaries of clearing houses, cut-off times of banks per currency, immediate processing etc), account opening procedures at the banks, the costs involved in maintaining accounts and transactions themselves etc.

The recent Ransomware attacks, that had an enormous impact on numerous companies and governmental institutions at a global level, showed however a less favorable aspect of this new technology. Due to its lack of control on the specifics of account ownership, Bitcoin proved to be the ideal means to collect the ransom money the victims have to pay to free their systems. This piracy trend will in my view also seriously hamper the future development of these sort of bank independent transaction mechanisms. Even more threatening for the Bitcoin development are the recent crypto robbery cases in which millions of dollars’ worth balances were stolen from the accounts. These incidents show the vital role of the banks as TTP since most banks are obliged to deliver their services according to the rules and regulations of their national and super-national banks. As indicated before, this means that for opening accounts lots of formalities have to be endured (the KYC rules are in some countries stretched to the absolute max). At the same time., due to the international regulations the control on international transactions are very extensive and therefore at the same time very costly for the banks. Every violation of the international code book on transactions to banned countries can have severe financial consequences for the banks involved. An last but not least banks have to maintain an international network of correspondent banks to make sure that the international transactions reach their beneficiaries in a reasonable timeframe and at reasonable costs.

This whole system has of course been developed to gain maximum control on transaction flows locally and worldwide. However it also provides the trust needed to be able to deal with (inter) national trade flows crucial to our economic day to day operations. As long as there are no ways to secure your transactions and balances in a bitcoin like environment as most transaction banks are providing today, Bitcoins remain a very interesting technological experience but will in no way replace the role of banks as TTP shortly.

 

 

Hans de Vries

Treasury/Cash Management Consultant

 

 

More articles of this author: 

Will the European banks strike back?

The Euro from a treasury perspective

New norms in banking: More than 30 new areas emerging. Pick your fights!

Moving Averages – how to calculate them

| 1-8-2017 | Lionel Pavey |


In the second article in this series we will be looking at different types of moving averages. Moving averages are used to determine the current trend of a price. They filter out the extremes within a range of data and present a smoother picture. They are almost exclusively calculated using the arithmetic mean. Some studies have been done using the median, though no advantages have been discovered. The following 3 methods are the most common approaches. In all following examples we shall assume an average calculated over a continuous series of 10 data points.

Simple Moving Average (SMA)

We take 10 consecutive values and calculate the simple arithmetic mean. When we calculate the next value we drop the oldest value in the series and add the newest value. We are constantly using the most current data in our calculation. Every data point receives the same weighting i.e. 10 per cent of the complete series. Whilst being very easy to calculate criticism is levelled at the fact that all data points receive the same weighting. This can distort the average when the market is volatile – more recent data is closer to the true market price.

Weighted Moving Average (WMA)

Here the 10 data points are assigned different weights, usually based on a simple mathematical progression. The 10th data point (most recent data) would be multiplied by 10; the 9th data point (second most recent data) would be multiplied by 9; etc. The product of these calculations would then be divided by 55 to produce a weighted average. This weighted average applies more importance on the most recent prices and, therefore, more closely match the current price.

Exponential Moving Average (EMA)

This is another form of a weighted average, but the weighting factors decrease exponentially. As such, whilst the older data points decrease exponentially in value, they never stop. Therefore, this average encompasses considerably more data than the previous 2 examples whilst still being an average calculated with only 10 data points.

The results

EMA is more responsive than SMA. An EMA graph will accelerate faster, turn quicker and fall faster than a SMA graph. This is due to the weighting given to the most recent data. However, these are all lagging indicators – they will always be behind the price. Furthermore, if a market is trapped in a very small trading range the averages will not be as smooth as the actual data. One of the main goals of using averages is to see if prices break out of a range and start a new trend.

Moving averages can be used simply to see what the current trend is. They can be further used by applying different 2 moving averages (one for 10 days and another for 50 days) to ascertain the change in momentum by 2 different time lines. But they all lag the market data.

Most of the time prices will tend to concentrate in a small area, with occasional larger movements up or down establishing the next area of consolidation. Is there an alternative way to design moving averages that take this into consideration?

Adaptive Moving Average (AMA)

Instead of just weighting the data, AMA also look at the price volatility. When prices are in a small range AMA will notice this lack of volatility and provide a trendline that is almost flat. As prices break out of the range AMA will move quickly up or down, depending on the change in prices. The advantages of AMA are that, visually, when prices are reasonably flat (little volatility) a clear flat line is shown so that even if the actual market price is lower than the AMA, it is clear that it is still within a range. As AMA is more sensitive to volatility, it can contain more data about the current trend. An initial breakout from a tight range will result in a very steep line for AMA. The trend can continue, but AMA will clearly show earlier than other averages when the trend is weakening. The only basic problem with AMA is the calculation – it is far more complex to calculate and is not so intuitive when you come to explain it to someone who does not know it.

As stated earlier, all moving averages suffer from lag – they are behind the actual price curve. Our last example is an average that attempts to remove this lag, whilst being more reactive to the current price.

Hull Moving Average (HMA)

Initially, a WMA is taken for 10 data points. Then a WMA is taken for half this period (5 data points) and is calculated with the 5 newest data points. The difference between these 2 is then combined with the WMA for the shorter period to arrive at a new average – the HMA.

The HMA is faster, smoother and eliminates most of the lag that is present in the other moving averages. In fact, it most closely resembles the actual market data.

All these averages are used to attempt to show what the trend is in the actual price, whilst filtering out the noise from all the prices, and presenting the data in a smooth form. Yet again, as previously mentioned, a change in the underlying fundamentals of the price will always have more impact on the price than any form of technical analysis.

However, if we concede that for a large majority of time prices are just trending, a moving average can be used to try and predict when the prices have moved out of their range and are on a new path with fresh momentum until that slows down and the following range is established.

When charting data we need to appreciate the amount of data we will be producing. Even if we just use the price at the start of the day, or the end of the day, we will accumulate at least 255 data points every year. If prices are in a small range, then more data is added to the chart series to provide a more dynamic picture. But this can make the visual data more cluttered once we include the actual data and 1 or 2 moving averages. Would it not be better if we could eliminate time and just look at price?

Read also my first article in this series where I tell you more about several types of forecasts.

In the last article in this series I will look at 2 common methods of showing price data devoid of timelines.

Lionel Pavey

 

Lionel Pavey

Cash Management and Treasury Specialist

 

Preparing the roll out of instant payment services: testing EBA’s RT1 platform

| 31-7-2017 | Jan Meulendijks | Finextra |

Instant payment services become more popular. UniCredit is testing the EBA Clearing’s RT1 real-time platform and preparing for the roll out of this service to 30 banks in Italy and Germany. Last week Finextra published an article about this development. Our expert Jan Meulendijks gives his opinion about the EBA Clearing’s RT1 real-time platform.

EBA’s RT1 is a probably a life-saving step for the banking/financial world as we know it today. SEPA was of course a major improvement in speeding up cross-border EURO-payments, but still the clearing process and therefore also the required processing time, was rather something from the 20th century and not up to today’s technical standards.

Without RT1 (and maybe similar developments yet to come) the banks are about to lose their payment processing activities and the related profits to other parties, mainly in the public domain (Blockchain) and ITC-sector. Microsoft, Google and Apple are names that will be appearing in this industry.

Remarkable: Italian banks seem to be fore-runners in joining RT1. Italy has always been infamous for the archaic infrastructure of their local and cross border payment systems. The slogan “what is backward will become forward” seems to apply here.

Jan MeulendijksJan Meulendijks – Cash management, transaction banking and trade professional

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More articles that might be interesting to read:

SEPA Instant Payments – a catalyst for new developments in the payments market (part I)

Instant payments for treasurers

Instant Payments: the SEPA Instant Payments rulebook is published, what’s next?

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The Digital Trade Chain: the blockchain train is rolling

| 28-7-2017 | Carlo de Meijer |

Trade finance is increasingly becoming the number one use case for blockchain with the greatest potential to benefit from this technology. In previously blocks I already showed the accelerated activity in this area (see: Blockchain and Supply Chain Finance: the missing link May 7, 2017 and Blockchain: accelerated activity in trade Finance, January 26, 2017).

End seven European banks, forming the so-called Digital Trade Chain consortium, announced their plans to develop in collaboration with IBM a trade finance platform based on blockchain technology. This is said to become the first real-world application of blockchain technology and might become the start of more of the blockchain train.

What is the Digital Trade Chain consortium?

In January this year seven European banks (Deutsche Bank, HSBC, KBC, Natixis, Rabobank, Société Générale and UniCredit) signed a Memorandum of Understanding (MoU) in Brussels to create the Digital Trade Chain consortium. Under this MoU the banks intend to collaborate on the development and commercialisation of a shared supply chain management and trade finance platform for small and medium-sized companies (SMEs) using blockchain technology. That platform, called the Digital Trade Chain (DTC), should make domestic and cross border commerce easier for European SME business.

The aim of the project is to simplify trade finance processes for SMEs by “addressing the challenge of managing, tracking and securing domestic and international trade transactions.

Read the full article of our expert Carlo de Meijer on LinkedIn

 

Carlo de Meijer

Economist and researcher

 

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