What’s new at TIPCO?

  • Best-of-breed is becoming the “new normal”
    in Treasury Management

    Best-of-Breed: Corporate Payments, Cash Management and Treasury Solutions byTIS and TIPCO

    Corporate payment provider TIS (Treasury Intelligence Solutions GmbH) and treasury experts TIPCO formalize their collaboration to best serve their clients’ needs

    Wien, September 29, 2020 – TIS, a leading cloud-based platform for corporate payments, and TIPCO, a best-in-class treasury solutions provider announced today that they have formalized their long-standing cooperation through a strategic partnership agreement.

    Over the past years, TIS and TIPCO have built an impressive track-record of successfully providing market-leading solutions to European clients.

    The two companies are recognized leaders in bank connectivity and payments, cash forecasting, risk management, bank relationship management and analytics. TIS and TIPCO share a joint mission to provide corporate treasurers with the best possible solutions through a seamless end-to-end cash management process. The components are tailored to the clients’ specific needs, without the need of costly IT implementation.

    Joerg Wiemer, co-founder and Chief Strategy Officer of TIS, is very excited about the prospect of this new partnership: “TIPCO is a top-of-the-line provider with an excellent solution. Formalizing our partnership is an important step towards building a best-of-breed cash management ecosystem based on cloud and API integration. This will provide our customers with a better experience that includes faster innovation and more strategic agility for future growth.”

    Alexander Fleischmann, Head of International Market Development and responsible for the collaboration on behalf of TIPCO summarizes: “Good systems should save a company time and money. Digitalization, however, can also be at the cost of flexibility if you rely on rigid one-fits-all solutions. The seamless integration between TIS and TIP combines two systems to offer the best of both: state-of-the art technology and extremely high levels of flexibility. We are convinced that we can offer numerous companies a perfect solution as a result.”


    About TIPCO

    The Austrian software provider TIPCO has made TIP the solution of choice for some of the leading companies in Europe across various industries. Over 130 clients – including Deutsche Telekom AG, Deutsche Post DHL Group, Fresenius, Merck, REWE Group, STIHL and many more – trust in TIP and in TIPCO’s ability to provide market-leading treasury innovation. The Treasury Information Platform TIP stands for state-of-the-art solutions for cash visibility, cash flow forecasting, risk management, guarantee management, bank fee analysis and reporting. TIP empowers Treasury departments to digitalize their processes and do away with manual data capturing and endless e-mail exchanges thanks to flexible and smart workflows.

    Go to to gain access to case studies and on-demand webinars and to schedule your custom online demo!


    About TIS

    TIS (Treasury Intelligence Solutions GmbH), founded in Walldorf, Germany in 2010, is a global leader in managing corporate payments. The Financial Times named TIS as one of “Europe’s Fastest Growing Companies” for 2019 and 2020.  Offered as Software-as-a-Service (SaaS), the TIS solution is a comprehensive, highly-scalable, cloud platform for company-wide payments and cash management. The TIS solution has been successfully used for many years in both large and medium-sized companies, including Adecco Group, Hugo Boss, Fresenius, Fugro, Lanxess, OSRAM and QIAGEN. More than 25% of DAX companies are already TIS customers.

    Your world of Payments. ONE Login.


    Press contacts



    Sophie Halfmann

    Am Belvedere 8

    A ­– 1100 Wien


    Treasury Intelligence Solutions GmbH

    Liang Fang

    Altrottstrasse 31

    69190 Walldorf

  • Cash flow forecasting at Lufthansa:
    How do you navigate through a global crisis?

    Cash Flow Forecasting at Lufthansa

    “If Lufthansa can do it, so can we.” This could be the motto in all treasury departments at the moment given that there is hardly any other German corporate currently facing greater challenges in terms of cash flow forecasting. So, how does Lufthansa forecast its cash flows and how is its treasury department dealing with the new demands?


    Europe’s largest aviation group has been using the TIP treasury information platform for the past 18 years and has already established long-term forecasting over a period of 27 months during this time. A very reliable approach under ‘normal’ conditions which nonetheless had to be reconsidered and re-evaluated due to the massive declines in cash flows as a result of COVID-19. TIP is a particularly flexible solution which has been designed to also respond and develop fast to changing requirements. This is one of the reasons why Lufthansa decided to also manage this task with TIP: “The COVID-19 crisis has redefined cash flow forecasting. TIPCO immediately understood the situation we are facing, grasped our requirements and swiftly implemented them. This was extremely important and helpful for us.” summarises Thomas Linnert (Head of Corporate Treasury Operations).


    We were able to demonstrate just how flexible the software really is in less than two weeks. An impressive performance on both sides given that the goal was not only to set up a short-term, week-by-week, currency-differentiated cash flow forecasting system, but also a significantly more detailed forecasting structure which still needed to be easily understandable in terms of its scope and remain user friendly. Working together with the team at Lufthansa responsible for cash flow forecasting, our treasury consultants developed practical forecasting tools which make TIP a reliable and effective crisis management tool for both the parent company and the subsidiaries.


    One of these tools is an Excel upload feature which enables local users to upload data from their own templates into the forecast. This allows the forecasters to easily and quickly import existing data and also avoids manual transfer errors. With the same goal in mind, a mirroring function was also implemented which automatically ‘pre-fills’ internal cash flows on the other side of the equation (sellers’ rule) so that existing data don’t need to be entered twice. Carlos Scheeren, the project lead for the implementation of the week-by-week forecast at Lufthansa: “The quality of the forecasting done by our subsidiaries is extremely important. The forecasting tools in TIP provide us with a way to support the local units in their work and at the same time to improve data quality at the group level.”


    As a result of the action taken in response to COVID-19, the main focus of many large corporates around the world in on the quality of their forecasting data. To ensure that all users capture their data as accurately and reliably as possible, they need to be able to regularly check their forecasting quality in a timely manner. Both subsidiaries and corporate finance therefore have the means to view deviations from the last forecast entered using a data analysis tool based on the TIP database so that they can better estimate their forecasting behaviour and learn from the past.


    From the action plan to the implementation and the go-live, all Lufthansa needed was ten days and was already able to forecast its global liquidity at the beginning of April. An impressive performance on the part of everyone involved despite the challenging deadline. We would like to thank Lufthansa for the trust placed in our team and our software, and to wish our client all the very best for the coming weeks and months.




    Cash Flow Forecasting with TIP: Download our Webinar!

    This webinar shows you how cash flow forecasting can learn from your historical data, rely on existing data in your systems and combine both to deliver dependable cash flow forecasts. We will also show you how user friendliness and immediate responses on the quality of cash flow forecasts can win over your subsidiaries. This not only improves the quality of forecasting but also your communication with subsidiaries.

    Webinar Liquiditätsplanung

  • The treasury information platform TIP
    in use at thyssenkrupp Elevator

    Treasury at thyssenkrupp Elevator

    Following the carve out of thyssenkrupp Elevator, this global provider of elevators and escalators also needed an independent treasury reporting system. The treasury information platform TIP was already well established within the thyssenkrupp group and was therefore well received by the new treasury team.

    The flexible structure of the software in particular, which allows specific modifications to be made at any time, was key to convincing this group with annual revenues of around eight billion euro (2018/19). The contract was awarded in March 2020 and the integration of financial status, guarantee and derivative reporting in the new corporate organisation followed just a few months later. In order to also be able to perform its own forecasting in future, the TIP cash flow forecasting module and the Excel Cube were also launched to allow thyssenkrupp Elevator to directly access its financial data and prepare ad-hoc reports for Management.

    Dennis Schwinning, Head of Treasury Front Office at thyssenkrupp Elevator:

    “TIP allows us to set up our treasury reporting to exactly reflect our requirements; from cash flow forecasting to ad-hoc reporting. TIPCO had already demonstrated its flexibility and high degree of customer orientation during the carve out process.”

    We are delighted about the positive feedback, the success of the carve out process and would particularly like to thank our new client for the trust they have placed in us. 


    Cash Flow Forecasting with TIP: Download our Webinar!

    This webinar shows you how cash flow forecasting can learn from your historical data, rely on existing data in your systems and combine both to deliver dependable cash flow forecasts. We will also show you how user friendliness and immediate responses on the quality of cash flow forecasts can win over your subsidiaries. This not only improves the quality of forecasting but also your communication with subsidiaries.

    Webinar Liquiditätsplanung

  • Predictive Analytics with TIP:
    A completely new level of cash flow forecasting

    Predictive Analytics mit TIP

    Predictive Analytics with TIP allows you to significantly automate your cash flow forecasting and standardise predictions and all of the underlying assumptions. This provides you with amazingly accurate forecast data and saves no end of valuable time.


    A new procedure for predictive analytics

    It goes without saying that a computer is capable of processing enormous volumes of data and performing highly complex analyses that you couldn’t manage with Excel alone. Computing power and statistics alone, however, are simply not enough when it comes to generating reliable forecast data.

    That’s why we have developed a multi-level procedure which significantly improves the precision of predictive analytics and therefore makes this concept fit for everyday treasury use. The treasury information platform TIP relies on this procedure to individually determine the best calculation method for every one of your forecasting categories in order to deliver amazing results. In combination with the expertise of your treasury department, this allows you to highly automate your forecasting and to improve the quality of your forecast figures.

    During this process, simply use TIP to define and calculate information about all the influencing factors relevant to your cash flow development (Fig. 2) and therefore digitalise your cash flow forecasting. This is the key not only to flexibly tailoring your forecasting to various requirements throughout your corporate group but also to making it independent of specific individuals. The value of this becomes clear when personnel leave the company or are on vacation or parental leave.

    This digitalisation of the process is the greatest advantage offered by predictive analytics. Why? Because it enables you to simultaneously take numerous influencing factors into account in your forecasting. This is nearly impossible to do manually. Statistical models and machine learning methods, however, can do this and therefore also generally make more accurate forecasts possible. Read the following article to find out more.


    What is predictive analytics?

    Many treasurers rely on Excel to analyse the cash flows of previous years in order to identify trends and patterns as a basis for being able to predict future developments. Predictive analytics is based on the same principle but on a far more technologically advanced level and with a significantly higher level of automation.

    The most important ingredient for accurate predictions is your historical data. These data are analysed for trends and patterns using a statistical computation model and projected into the future. For this to work, the system needs to calibrate the model in advance so that it can categorise recurring events (e.g. the impact of public holidays) and ignore data outliers (Fig. 1).

    While this might sound simple, it is actually a complex process during which the system needs to consider numerous variables and parameters and to both review and update these at regular intervals. There are also nearly twenty different statistical models available for the calculations and the suitability of these models varies significantly depending on the forecasting category and data quality. The selection of the right model is therefore equally as important as its modelling and needs to be reviewed just as often so that the calculations can improve, in terms of accuracy, over time.

    The principle behind predictive analytics

    Figure 1 | Patterns in the past provide insights into the future: A drastically simplified explanation of predictive analytics.

    From theory to practice: Start by clarifying the parameters and making the underlying data available

    The first step is for us to jointly analyse which data are relevant for your predictions. These data need to span a period of at least three years if they are to be used for predictive analytics. As soon as the data landscape has been clarified, TIP automatically integrates these data from existing upstream systems into its cash flow forecasting.

    In addition, it of course has to be defined which currencies, over which forecasting horizon (on a daily, weekly or monthly basis) and for which future period the forecasts are needed for every forecasting category.


    Defining and modelling general and specific influencing factors

    An in-depth understanding of your group’s business model is fundamental to the analysis. Which external and internal factors influencing your cash flows will you need to calculate in treasury in the future? The assessment of these factors is ultimately the key to reliable and robust forecast data. That’s why our data scientists discuss all known influencing factors (Fig. 2) with you at the outset, how these can be modelled, and everything that needs to be taken into account. This initial step is decisive because statistical methods can only deliver meaningful results if they have ‘learnt’ in advance not only how to identify only one-off data outliers but also regular dependencies on other factors.

    General influencing factors exist which, even if they may be very different in terms of their impact, are felt in every industry and every company. Public holidays, for example, vary not only internationally but also nationally, from state to state, and their impact on the retail sector is completely different from that on the tourism industry. The same of course also applies to seasonal variations and trends. There is one thing however that all of these factors have in common: they are relevant to nearly every company, have massive impacts on cash flow developments and, therefore, have to be modelled before the first test run. While the effects of public holidays can be easily modelled by uploading a calendar, seasonal effects and trends are mainly identified by analysing historical data. This step is handled automatically by TIP in an analysis of whether seasonal effects, trend shifts and catch-up effects after public holidays exist in the various forecasting categories.

    Specific influencing factors impact your industry or even just your company. The data landscape and the preparation of the data for modelling purposes therefore also need to take these factors into account. TIP models external facts using general economic data, such as exchange rates, which can usually be sourced from data providers. We upload internal factors, such as fixed payment deadlines, so that these can be integrated into the computation models. Many specific factors are initially not even known or the data landscape is insufficient in order for these to be modelled. The longer you use forecasting, however, the greater the reservoir of data which can be used for re-adjustments. This means that your forecasts will become even more reliable over time.

    Predictive Analytics & Cash Flow Forecasting – Influencing Factors

    Figure 2 | General and specific influencing factors: Influencing factors give rise to patterns which are identified by the models but which cannot be projected 1:1 into the future. These factors need to be modelled in order to improve the quality of forecast data.

    Which statistical model is right for which forecasting category?

    The key challenge in dealing with predictive analytics is determining which statistical model is suited to every single forecasting category.

    Statistical Model Groups for Predictive Analytics

    Figure 3 | Statistical model groups used by TIP for predictive analytics: There exist numerous statistical models but they are not all suitable for cash flow forecasting purposes. TIP relies on the following eight model groups.

    We currently rely on eight model groups, each of which has different strengths and weaknesses. Regression models, for example, are able to deal easily with missing data, which are a challenge for models based on ARIMA. Neural networks are very good at identifying patterns but require a large volume of data as a starting point; data which don’t exist for a forecast on a monthly basis. An automated analysis of the existing data is all it takes to identify which models can immediately be rejected and don’t even need to be subjected to a test run. This is extremely important since numerous forecasting categories and models, as well as their modelling, require considerable computing power, meaning resources both in terms of computation capacity and money. Minimising the scope in advance to promising models is key to the efficiency of this procedure.

    The data analysis generally delivers a pre-selection of five to six models for the test run. TIP calibrates the models using the influencing factors already identified and then calculates a test forecast for the most recent existing twelve months on the basis of actual historical data (at least three years’ data are necessary for this). Deviations of this third year to the actual data are subsequently analysed for every model and the best model is then selected.

    Historical Data for Predictive Analytics – test run and analysis of best model

    Figure 4 | Test run with historical actual data and analysis of the best computation model: The first two actual years are used to validate the suitable computation model. The model which most closely reflects the results in the third year (red line) is then selected as the basis for calculating the forecasting data.

    An overview of the implementation

    As soon as the parameters for the forecasting and the necessary data have been defined, the entire process, from the analysis of the data to the pre-selection, calibration and validation of the models as well as the ‘final’ selection of the model and the calculation of the first forecast, is largely automated. Only data outliers need to be considered individually and adjusted for in order to improve the accuracy of forecasts. You can change the selection of the best model automatically based on even minor deviations or adjust this manually based on tactical considerations. This might make sense if, for example, the historical data are dominated by extraordinary influencing factors (e.g. an economic crisis, natural disasters or pandemics) for longer periods and therefore do not represent normal developments. In such cases, it is possible that a particular model performs well while another one would nonetheless be better in the long term.

    Predictive Analytics: From preperation work to the first forecast

    Figure 5 | An overview of the process: from preparation work to the first forecast: The first step involves tasks which the system later performs itself.

    The first automatically generated forecast

    The forecasting data generated provide a sound basis for Treasury to leverage its specific expertise to swiftly prepare a professional cash flow forecast. For some forecasting categories (e.g. salaries), this works so reliably that TIP can even directly generate a cash flow forecast if wanted. For categories which are often dominated by exceptions, it makes more sense to display the calculated figures in the standard forecasting screen as proposals. In this case, the existing data act as a guide for manual fine-tuning and save no end of time (Fig. 6).

    Proposed Figures in Forecasting Module for Manual Forecasting

    Figure 6 | Proposed figures for manual forecasting: Particularly at the outset, manual adjustments are important but they also remain standard in certain categories. In such cases, predictive analytics provides a baseline which can then be adjusted manually.

    Not only the forecast data themselves but also the estimates and observations based on these are extremely important. TIP gathers all of the relevant information in a report which is generated along with the forecast data:

    • Predictions broken down into individual components per influencing factor (Fig. 7)
    • The scale and statistical significance of the individual factors
    • The granulation of seasonal modelling
    • Identified breaks in trends
    • The distribution of residuals (estimation errors)
    • Statistical test results (e.g. heteroscedasticity, autocorrelation, etc.)
    • Automatic pre-identification of potential outliers
    General Influencing Factors broken down by Component for Cash Flow Forecasting

    Figure 7 | General influencing factors broken down by component: A visual illustration of each factor can make sense for evaluating the individual effects

    This information can help every treasurer to quickly understand how the forecast figures were generated. This can be helpful not only in swiftly identifying forecasting errors but also in understanding which factors are responsible for a sudden change. This delivers not only transparency but also makes it easier to perform checks.

    Ongoing optimisation leads to constantly improving forecast data

    The first run still requires some attention and manual tasks but, as soon as these have been performed, the system takes over more and more of these steps itself. And the calculations become increasingly accurate over time as further actual data in the right degree of granularity become available. That’s why TIP checks before every new forecast whether the model selected is still the best option or whether another model would deliver better results. The selection process here essentially remains the same, with the only real difference being that previously modelled influencing factors are applied for the calibration completely automatically which, in turn, means that the test calculations become increasingly accurate over time. It goes without saying, however, that Treasury can calibrate the models with additional or better influencing factors at any time to improve the predictions.

    Predictive Analytics: finetuning before every new forecast

    Figure 8 | Ongoing fine-tuning before every new forecast: The longer the system is in use, the more precise the predictions become. The availability of new actual data compared to the previous prediction means that the data basis for calculations constantly improves.

    Who is predictive analytics right for?

    The more volatile the cash flows of a company become, the less likely it is that the models will be able to identify useful patterns in the historical data. That’s why this procedure is best suited for the B2C sector and for subsidiaries with a broad customer base since the development of cash flows in these cases is not dominated by major one-off payments. Nonetheless, this procedure also offers advantages for small subsidiaries with major B2B projects. Even if the data in such cases need to be carefully checked and manually adjusted, this procedure provides the advantage of digitally documenting known influencing factors and can therefore be easily referred to, making forecasting digital. Even when key personnel leave, their knowledge stays and the quality of predictions is safeguarded.


    Any questions?

    The aim of this summary is to as transparently as possible set out and explain the advantages of predictive analytics. We know that the process as a whole is detailed and therefore complex, which is why we would welcome the opportunity to discuss the issue and advise you personally. Hit us with your questions and we can then clarify together whether predictive analytics could also pay off for you.


    Contact TIPCO

  • Best-of-breed treasury system landscape:
    Corestate at the 8th Cash Management Campus

    The 8th Cash Management Campus of DerTreasurer was held digitally for the first time as a result of the COVID-19 restrictions but was nonetheless well received by participants. Hardly surprising given that it is currently more important than ever to inform yourself about developments in the market and, not least, about solutions for system-based cash flow forecasting. Our client Corestate was also among the presenters. During his presentation, Tobias Wriedt (Head of Treasury) explained how Corestate has reorganised its treasury system landscape and which factors were important here. Corestate Capital Holding S.A. is a publicly-listed real estate investment manager and co-investor with around €28bn in assets under management and is therefore one of the leading providers of integrated real estate investment solutions in Europe.

    Among other factors, it was important for Corestate that the new treasury system landscape be able to ensure the smooth exchange of data both internally and externally. The aim was to integrate upstream systems which were already deployed, as well as third parties, without complex workarounds. It soon became clear to Corestate that neither an SAP-integrated solution nor an all-in-one solution fitted the ticket.

    “We decided against an SAP-integrated solution from the outset because we work with four different ERP solutions and committing to SAP would have excluded the others,” says Wriedt summarising the decisive argument. For similar reasons, they also opted not to go for an all-in-one solution. While one of these might be a good option in the long term, it would have required very carefully conceived and therefore time-consuming specialist concepts during the preparation phase in order to implement all of the requirements in terms of cash flows, forecasting, reporting and credit management in order for the various areas of treasury to be fully integrated. Corestate wanted fast, reliable results, and that’s why they decided to rely on experts in the various areas of treasury.

    The treasury information platform TIP is responsible for reporting and cash flow forecasting and is closely integrated with data captured by TIS. Both systems have ‘known’ each other for several years and are closely aligned. The TIS interface allows Corestate to access its group-wide financial status and cash flows in its forecasting at the click of a button in TIP. Besides this, daily ECB exchange rates can be imported and any cash flows which haven’t been captured in upstream systems can easily be imported via Excel.

    Cloud-based or on-premise solution? Wriedt explains why the cloud-based solutions offered by TIS and TIPCO were important for Corestate: “In addition to issues such as data protection and data security, a major advantage is the fact that a cloud-based solution means that we don’t need to reserve any in-house resources for support, administration or the like.” His assessment is one which many of our clients share and which has been proven in practice many times.

    TIP went live at the end of 2019 and has since been used intensively. A short-term cash flow forecast had already been planned even before the COVID-19 outbreak and was quietly implemented at the beginning of the year.

    Wriedt summarises:

    “From our point of view and in terms of what we need, we opted for the best providers you can get for these three areas of treasury.” A great compliment and one that we are delighted about and happy to share with TIS and our Austrian colleagues at LANG Finanzsoftware.


    The full version of the presentation on YouTube:

  • Setting up a short-term cash flow forecast
    in just two days!

    Short-term cash flow forecast

    Most of our clients have been reliably forecasting their cash flows with TIP for years. In stable economic times, all you need for this is long-term forecasting horizons; but in time such as the COVID-19 pandemic, there needs to be a rethink. In this context, increasing numbers of clients are supplementing their previous forecasting with a short-term cash flow forecast covering 14 days and/or 13 weeks.


    The volatile economic situation at present leaves little room for manoeuvre and, at the outset of our first such project, it was soon clear that a solution was needed ASAP, and one delivered from home office to home office. Since 16 March, Austria has been in lockdown and we of course have also sent our staff home. The question of how such an ambitious project could work without face-to-face meetings was one we had to first clarify by means of a dry run. The outcome of this was clear: it hardly makes any difference. The only thing that several colleagues missed was the office cookie jar.


    But why did it work so well? TIPCO supports over 130 corporates worldwide, the majority of which are based in neighbouring Germany, but also in the UK and even in the UAE there are also group treasurers who enjoy the benefits of TIP on a daily basis. Online meetings with our clients are the rule rather than the exception, which is why we are so well versed here. On top, there are also perfectly configured hosting environments which we not only use internally but which are likewise offered to our clients.


    As a result, the first home-office implementation of a short-term cash flow forecast went like clockwork. The parameters were quickly and efficiently defined with the client in an online kick-off meeting, after which a forecasting grid was prepared and immediately made available to the client’s various subsidiaries. These subsidiaries, based all around the world, were able to enter their forecast data just 24 hours later, which the majority actually did, and therefore automatically reported these to the parent company. Even the group treasurer was surprised by the high degree of compliance.

    short-term cash flow forecast

    The current circumstances present major challenges for our clients. The situation is serious and, even if they don’t wear their business outfits when working from their home offices, they are nonetheless fully committed to and concentrated on the task of safeguarding their subsidiaries’ liquidity in the coming weeks and months. That is why we fully understand our client’s decision not to be identified by name in this case study. We are delighted with the success of this project but nonetheless are aware that our software is mainly being used at the moment to manage the ongoing emergency.


    We would also like to say a big “Thank You” to all those colleagues who cooperated so well from their home offices. We are convinced that there are many other companies out there that we can help to expand their cash flow forecasting, and working from home offices isn’t going to get in the way. In fact, we are already working on other implementation projects.


    If you have any questions on this, please get in touch, we’ll be happy to help.



    Cash Flow Forecasting with TIP: Download our Webinar!

    This webinar shows you how cash flow forecasting can learn from your historical data, rely on existing data in your systems and combine both to deliver dependable cash flow forecasts. We will also show you how user friendliness and immediate responses on the quality of cash flow forecasts can win over your subsidiaries. This not only improves the quality of forecasting but also your communication with subsidiaries.


    Webinar Liquiditätsplanung


  • eBAM at SCHOTT
    fully automated account confirmations become reality

    TIP Workflow Kontenbestätigung

    Workflow Webinar TIPCO

    How this leading international manufacturer of speciality glass and glass ceramics is automating its bank account management and breaking new ground in treasury. A success story in cooperation with Deutsche Bank and TIPCO.


    Bank accounts under the microscope

    Bank accounts are the crux of every treasury department; central to every key process. At the end of the day, every financial transaction is reflected on a bank account. Which is why large corporates generally have dozens if not hundreds of accounts which their head offices and subsidiaries have to manage and check. These accounts are distributed around the globe, denominated in various currencies and held at numerous banks. Retaining an overview is therefore no easy task. What about the number, status and purpose of accounts? Are the account signatory permissions still up-to-date? Dieter Worf, Head of Treasury at Schott AG, is very familiar with these challenges: “With over 60 group entities and more than 200 bank accounts, managing these accounts takes a lot of time. That’s why our top priority is for as much work as possible to be dealt with by our IT systems.”

    Attention to detail has always been a core element of SCHOTT’s DNA. This technology group is currently manufacturing glass-ceramic segments for the Extremely Large Telescope (ELT) which is being constructed in Chile’s Atacama Desert. It is therefore no surprise that SCHOTT also insists on maximum transparency when it comes to managing its bank accounts. The group is playing a pioneering role here because, what may sound logical is still rare in practice: an automated reconciliation process that forms a bridge between treasury departments and banks. The challenge here is enabling corporate IT systems and those of banks to automatically communicate with each other in a standardised language.

    SCHOTT AG eBAM account confirmations

    Fig. 1: An image of the Extremely Large Telescope (ELT) which will be searching for extra-terrestrial life from 2024. SCHOTT is supplying 798 hexagonal glass-ceramic segments which will be combined to form the 39-metre diameter primary mirror.

    SCHOTT implemented the treasury software TIP as early as 2002; a solution which is designed specifically for integrating different systems. In the course of a brainstorming session with the software developer TIPCO, the treasury team at SCHOTT decided in 2018 to manage the first element of its bank account management processes by means of a workflow and to handle bank communication via automatically generated messages. The idea behind this: completely automatically checking whether certain accounts at the bank are active and which individuals have signatory rights to these accounts.

    Jochen Alt, Treasury Manager at SCHOTT, highlights the biggest advantage: “We liked the idea of being able to automatically check the status of our accounts at the bank not only because of the time-savings. The option of checking who has signatory rights to an account at the press of a button also helps us in terms of compliance with our policies.”


    The right bank as the key to moving from BAM to eBAM

    While the idea is not a new one, in the past, one of the reasons why implementations failed, was a lack of willingness on the part of many banks to get to grips with the issue. The treasury information platform TIP meant that a suitable tool was already available in which all of SCHOTT’s bank accounts had been captured. The only thing missing was to find a banking partner who was prepared to allocate resources to the project. The treasury team at SCHOTT, however, was able to convince Deutsche Bank; one of its core banks for many years. The trio was therefore complete and the project could be launched.


    Request, status message and account report: from concept to workflow

    The first step was for the project team to jointly define the target process for account confirmations. Why? Because only processes which adhere to clear rules can be translated into a workflow. Given that this was literally a greenfield project, it was necessary to precisely coordinate everything on the drawing board. TIPCO moderated the drafting of flow diagrams in order to clearly define the end-to-end process. This is where years of experience in the areas of system integration and data exchange really paid off. Dieter Worf: “We liked the fact that TIPCO focussed not only on its own system but on the entire process. And Deutsche Bank was totally committed from the outset to jointly implementing this solution despite a few minor stumbling blocks along the way.”

    TIPCO Workflow account confirmations eBAM

    Fig. 2: Flowchart illustrating account confirmation process. The exact reconciliation of the messaging process and the resulting, various workflow statuses formed the basis for implementing the project.

    After several rounds of coordination, the process steps had been defined and TIPCO was able to set up the first prototype of the workflow. The first acmt messages were generated and sent to Deutsche Bank to be checked. After some fine-tuning, Deutsche Bank achieved a breakthrough: its system was able to receive and respond to a request captured in the acmt format and transferred via the SWIFT network in a fully automated fashion.


    The outcome: More automation and more transparency

    The TIP workflow and the automated exchange of data now mean that SCHOTT can have its active accounts checked and confirmed by the bank at the press of a mouse button. An error message is generated if the bank cannot identify the accounts delivered in its systems. If the accounts can be identified but the signature authorisations aren’t correct, then the accounts are flagged in the workflow for clarification with the bank. If all the data are 100% correct, the status of the accounts changes to ‘confirmed’ and the date of the confirmation is added.


    Treasury Software TIP by TIPCO GmbH

    Fig. 3: Confirmation workflow in TIP: The confirmation for the relevant accounts can be initiated on an overview screen by means of a simple mouse click. After being transferred to Deutsche Bank, the import of both acknowledgement and account report takes place completely automatically. Accounts with discrepancies in terms of signature authorisations are flagged for further processing while successfully confirmed accounts are moved to the status ‘confirmed’.

    When the entire workflow goes live as planned in February, the treasury software TIP will forward the account report request to Deutsche Bank fully automatically via the SWIFT network and the acknowledgement, any rejections and as well as the account reports will be processed without any manual inputs. This will make sending emails redundant and avoid any communication and transfer-related errors as well as any security loopholes.


    The next steps?

    With the aid of the workflow, SCHOTT will initially be able to reconcile account numbers, currencies and signature authorisations. A further aim is to automate the annual account balance confirmation process which is part of annual closings. In future, it could also be possible to check the lower and upper amount limits of authorised signatories. The enormous potential of this solution, however, lies elsewhere: the technical basis and the experience gained in the course of this innovative project can be leveraged to automate other processes related to opening, amending and closing bank accounts. Features which are currently only available in connection with Deutsche Bank accounts in Germany will in future also be available for international accounts. As Dieter Worf concludes: “This project in cooperation with TIPCO and Deutsche Bank has successfully digitalised an important area of bank account management. We are also convinced that far more is possible. We aim to keep focussing on this and invite all others working in treasury to do as we have done. This is the only way that completely digitalised bank account management can become reality.” The vision for the future is for other banks to do what Deutsche Bank has done and to make their systems ready for eBAM so that corporates can soon check and manage the majority of their accounts, both domestic and international, at the press of a button. Jochen Alt summarises the outlook from the perspective of SCHOTT: “We have made a start and now further steps can be taken. By the time the Extremely Large Telescope enters service in 2024, our view of our bank accounts will also be a lot clearer.”

    About SCHOTT AG

    SCHOTT is a leading international technology group in the areas of speciality glass and glass-ceramics. The company has more than 130 years of outstanding development, materials and technology expertise and offers a broad portfolio of high-quality products and intelligent solutions. SCHOTT is an innovative enabler for many industries, including the home appliance, pharma, electronics, optics, life sciences, automotive and aviation industries. SCHOTT strives to play an important part in everyone’s lives and is committed to innovation and sustainable success. The parent company, SCHOTT AG, has its headquarters in Mainz (Germany) and is solely owned by the Carl Zeiss Foundation. This is one of the oldest private and one of the largest foundations supporting scientific research in Germany. As a foundation-based company, SCHOTT assumes special responsibility for its employees, society and the environment.

    Its more than 15,500 employees worldwide, of whom 5,500 are based in Germany, most recently generated revenues of EUR 2.08bn, 86% of which was generated abroad.


  • Automated bank fee analysis with TIP
    in five steps


    Save money and gain an overview of your payment processes

    Bank fee analysis is for treasurers with too much spare time.” – When Treasury departments need to get by with scarce resources, there are more important things to do than chasing banks for missing fee statements, querying unclear charges or dealing with a lack of standardisation in statement formats. It is also understandable that checking bank fees was often a bone of contention. Even those treasurers who could find enough time to deal with this mammoth task needed to first negotiate hard with their banks and then tediously work their way through mountains of data. The value of the information obtained as a result rarely warranted the effort, which is why bank fee analysis was soon shelved at most corporates.

    Fortunately, these times are over. As a result of pressure from corporates, most banks have in the meantime created the basis for automatic bank fee analysis. TIPCO has been on the forefront of this issue from the outset and, with its treasury information platform TIP, has developed a tool which can efficiently process, interpret and analyse electronic fee statements. This article explains exactly how bank fee analysis works and why it can even be fun.


    Step 1: Call your bank and organise your data

    A bank is a supplier like any other. This means that a bank needs to ensure that what it charges is in line with what was agreed and has to regularly provide a transparent invoice (statement) setting out all of the services it has provided. While we have admittedly never heard of a bank that proactively provides its corporate clients with detailed fee statements, most banks are willing and able to do this if requested. In times of blockchain technology and autonomous cars, it also goes without saying that banks need to provide you with electronic fee statements. The following formats exist as options:

    • camt.086 (the most up-to-date and recommended format)
    • TWIST BSB (the predecessor of CAMT.086)
    • EDI.822 (used in North America)

    These formats contain bank fee information in the form of codes which are initially difficult for a layman to decrypt and which can vary from bank to bank. In most part, however, they all contain the same information:

    • Which account is involved?
    • What type of service has been provided?
    • Which fee was charged for this service?
    • How often was a fee charged for this service?
    • How high are the total costs?


    The total costs associated with all services provided in connection with and charged to your accounts within a month are equivalent to the monthly fees associated with your payment transactions and other cash management services. If you automate and reliably monitor the billing of these services as part of your bank fee analysis process, you can reduce your costs by 10% to 20% while at the same time optimising your internal processes.

    You might well ask what bank fee analysis has to do with internal processes. The answer is easy: Besides monitoring the application of the fees you have negotiated, the information you obtain by fully checking your banks’ fee statements also enables you to investigate your accounts and the nature of the services you source. Are there any unnecessary accounts which could be closed? Do certain subsidiaries make unusual numbers of cash transactions or are expensive services such as fax-based transfers frequently used that are really unnecessary? The findings delivered by bank fee monitoring can quickly lead to major savings, improve your compliance and considerably optimise your payment processes.


    Step 2: Get your accounts in order

    Bank fee analysis depends on numerous working steps which need to be systematically applied. The easiest way to do this is to set up a clear workflow which guides you step-by-step through all of the tasks and even learns from your past inputs. Over time, the manual work necessary decreases and the goal of largely automated monitoring gets closer and closer.

    The first step is making sure that your bank and your system understand one another when identifying your accounts. Based on the fee statements submitted in the electronic formats mentioned above, the identifiers the bank uses for your accounts need to be mapped to the account identifiers in the system. In the case of existing accounts, this step only needs to be performed once. After this has been done, the workflow will only ask you to take action if a new account has been opened or an existing account closed.

    Our clients are often shocked at the results once this ‘account mining’ process has been completed. It is not uncommon for accounts to crop up which have been forgotten and which urgently need to be dealt with.

    Workflow: Mapping unknown and new accounts

    Workflow: Mapping unknown and new accounts

    The workflow provides an instant overview of all accounts which require your attention and automatically proposes the appropriate working steps. If you first need to discuss a ‘new’ account internally or with your bank, you can also automatically set up a task list for this.

    How is an account mapped?
    In the simplest case, an account will already exist in your system and the only thing you need to do is to map the previously unknown code used by your bank to the existing account on your internal list of accounts. In future, this account will be automatically identified by the system and the issue is done and dusted.

    Things get more interesting however if an account contained in the bank’s fee statement cannot be found on your internal list of bank accounts. Either it dawns on you why this account exists, then simply set up the account in the system using the data provided (such as the bank name, currency, account number or IBAN). Other systems such as your ERP or TMS will also be automatically informed about the existence of this previously unrecorded account during this step. This allows you to gradually complete your portfolio of accounts in all your systems. A pleasant side effect of bank fee analysis.

    But what if the account is entirely unfamiliar to you? For example, the general manager of a local subsidiary may only recently have opened it. Just add it to your task list to be clarified during your next internal meeting. Another plausible scenario: fees continue to be charged for an account which you thought had been closed a long time ago. By marking the account for discussion with the bank, you put it on the task list for your next bank meeting.

    As soon as it is clear how you need to proceed with the account, then the status of this account is changed and it is therefore documented what needs to happen in the next step.


    Discuss this account

    An account is updated with the status “Discuss this account with bank“. The four-eyes principle can also be applied if necessary for compliance reasons.

    Step 3: Check services and validate fees

    Once you have identified all of your accounts, the next step entails checking all of the services and the associated fees charged. Due to the considerable number of services which could be contained in the bank fee statement, it is particularly helpful that the system facilitates an easy and efficient process.

    This working step essentially revolves around two key questions:

    • Has the service provided been agreed with the bank?
    • If so, has the right fee been charged for this service?


    Checking new fees

    New fees are checked in the workflow with regard to their being correct and can either be marked for internal clarification or external discussion with the bank in question.

    A glance at the workflow is all it takes to identify that the latest statement of fees includes services which haven’t been charged in the past and which therefore require attention. Again, manual intervention required will decrease over time: While all of the fee positions will initially be flagged as ‘new’, with each subsequent round of analysis the number of these positions will decline until only those items for which the bank has not previously charged you will be highlighted.

    How to allocate the correct fee to a service:

    If the details included in the statement are correct, i.e. the fee agreed and the fee charged correspond, the service charged on the statement can be imported into the list of agreed fees at the click of a button. The next time, the system will identify this fee automatically thus ensuring a swift and reliable analysis.

    If the service has been agreed with the bank but an incorrect fee has been charged on the statement, you can allocate the correct fee yourself in just a few mouse clicks. Once this one-off procedure is completed, the system takes over again.


    Fees can be allocated, newly set up and modified in the system in just a few mouse clicks.

    During this working step, you can also flag fees which should in future be avoided within your corporate group. These fees generally relate to services in connection with unwanted payment methods (e.g. express payment services, fax-based payments, manual transactions, etc.) and point to processes which need to be internally discussed and optimised. Once flagged, these positions no longer go unnoticed, generating unnecessary costs or security risks. Instead, a press of a button will be all it takes for you to check the status of your payment processes in future.


    Unwanted Services

    Unwanted services can be flagged as such with one click.

    And in case you stumble across unknown or unjustified fees: A click is all it takes to mark these positions and automatically shift them into the task folder to be discussed at the next opportunity. It’s as easy as that.


    Step 4: Bank fee analysis at the press of a button 

    The system can now fully automatically interpret and check your bank fee statements. It knows the relevant account and fee codes and the correct rates which the bank is entitled to charge. That’s all that is necessary to monitor your statements on a monthly basis. Once again, workflows are best suited to support you with this recurring task because even if there are only a limited number of accounts to be analysed, the amount of manual work necessary to do so would be excessive. The workflow, however, ensures that only those statements which warrant a closer look are actually scrutinised:


    Bank Fee Analysis

    The workflow only lists those positions for which the system has identified discrepancies. Simply mark them for discussion or request refunds immediately.

    The list only contains positions where the workflow has identified deviations between the agreed fees and the fees delivered in the statement. This way you can speedily analyse how the deviations arose. Also, the expected total volume of fees, computed as items charged times agreed fee per item, is displayed and contrasted with the actual total volume of fees charged. The next step lets you either directly generate a list of refund requests at the click of a button or set up a task list of items to be discussed at the next internal or external meeting.

    As total costs charged could also be incorrect due to the volumes (i.e. number of items) charged being incorrect, the last step also entails determining the actual volumes of transactions and services initiated and contrasting these with the volumes delivered in the statement of fees. The best data source for the number of payment transactions is your electronic account statements. This is also where the total amount of charges deducted from your account can be found and contrasted with the total amount of charges included in the fee statement.


    Step 5: Get your money back!

    As soon as a discrepancy has been confirmed, the system automatically generates an entry in the ‘refund’ workflow. This is where all refund applications are ‘parked’ and subsequently marked as ‘done’ once the bank has re-credited the account. This ensures that nothing gets overseen and allows you to see how your bank fee analysis really pays off. At the moment, it is still necessary to apply for refunds manually since banks are not yet offering any standardised messages which would also allow this process to be automated.



    Even for automated bank fee analysis, the old adage still applies: No pain, no gain. An in-depth mapping of accounts and fees is initially necessary due to the fact that the different codes used by both corporates and banks hinder automation of this process. As standardisation increases, however, so the workload involved decreases. The internal codes used by the banks will nonetheless always need to be mapped manually. Thanks to the clearly structured workflow, this task, while still time-consuming, is no longer insurmountable and the process also delivers new insights into your account landscape and your payment processes.

    Our clients all agree: bank fee analysis offers them far more than just a means of demanding refunds for unjustified bank fees. It allows them to rapidly compare banking terms and conditions across various banks and countries, and supports them in identifying dubious payment processes throughout their corporate groups. The detailed overview of all services, fees, volumes and incorrect fee statements bolsters their position in negotiations with banks and subsidiaries, and is therefore the ideal basis for tapping latent cost savings.

    To find out which banks in which countries already support electronic fee monitoring, simply send an email to We look forward to hearing from you.

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