How SAAS companies get burned by exchange rates
This article is a contribution from one of our content partners, Bound We 💜 finance teams from tech companies We spend a lot of time here at Bound talking with finance teams from venture-backed tech companies. Like most of the work conversations you probably have, our conversations follow a general outline like this: “Hey, Where you calling in from in the world?” [insert your favourite location]. Oh cool, my cousin lived there for a few years. She always said nice things. …… Wait for it…… here comes the obligatory weather comment… “Well, you’ve got better weather than us right now. I’d switch [weather-related complaint] for your [generic weather compliment that is, at best, loosely accurate].” Then the conversation turns to foreign cash flows–which some people might find boring, but we get pretty excited about here at Bound. After all, this is what we do. Why these finance teams talk about Bound Finance teams at growth-stage tech companies use Bound’s app to take foreign cash flows that normally bounce around with exchange rates and make them more stable and predictable. Classic use-cases for using Bound: Companies with these use-cases, use Bound’s technology to make these foreign cash flow streams more stable and predictable almost overnight. How exchange rates can hurt SAAS companies 🔥 One situation that comes up a lot with SAAS companies is the headache of foreign revenue contracts. Here’s an example of how exchange rates can potentially burn saas companies with a lot of international customers. THE SETUP Let’s pretend we’re a UK-based SAAS company with European customers. We report our finances in GBP. This is a fictional example roughly based on 2022 and 2023, but also includes simulated exchange rates into the future. We invoice monthly in arrears and recognize revenue evenly over the contract. THE SALE We sign a new contract with a new customer. Yeah! European customers don’t like paying in GBP, so we price European customers in EUR. The new contract is worth EUR 25,000/month for 24 months–EUR 600,000 total. Let’s pretend we sign the contract in Jan of 2023. The GBP/EUR exchange rate is about 1.125 at the time of contract signing. That’s roughly where the rate was for the first half of 2023. We’ll expect GBP 22,223.80 per month in revenue. Based on that rate, the sales team just booked GBP 533,371.26 . Nice work team! THE FIRST INVOICE 30 days later, we invoice the customer EUR 25,000 and record our GBP 22,223.80 in revenue. Of course, over the course of the month the exchange rate didn’t stay perfectly stable. We’ll pretend the GBP/EUR rate moved a little. Let’s say it’s now 1.127. Not a big deal, GBP 22,178.85. Whatever. GBP 44.95 isn’t a big deal. I can just write down our revenue a little, take a small currency loss or maybe I’ll just shrug this off. THE PAINFUL GBP RALLY But now let’s run a GBP-strengthening scenario for the remaining 23-months. At the time of writing, in early December 2023, GBP/EUR is up to 1.17. (This is mostly the true story of GBP/EUR over 2023) I’ve also thrown historic GBP/EUR data into a statistical rate simulator and told it to run a realistic GBP-strengthening scenario. Let’s see how our company does here for the rest of the year. So, that GBP 44.95 problem in the first month, that we brushed past, ended up being a GBP 63,525.13 problem over the course of the contract. That figure is harder to ignore, especially when you figure we have 50 customers with similar contracts. If the same scenario with all 50 of our European customers, we’re looking at currency losses or revenue write downs in the ballpark of GBP 3,000,000. And remember, currency losses aren’t just paper losses. This has a real impact to our GBP cash flow. THE MESSY RENEWAL One last problem. The renewal. The rate at renewal time was all the way up to 1.19. The customer is happy and wants to renew at EUR 25,000/month for another 24 months. Seems great, but that’s only going to be GBP 504,201.68 at this new exchange rate. So, I need to fight for a 6% price increase just to stay steady with the figures from our last contract or I realize revenue contraction from a happy customer. ;( Again, multiply that by 50 European customers and I’ve got a material renewal problem to deal with. We love this sh*t, so you don’t have to 😉 These are the types of problems that Bound helps SAAS-companies deal with. Reach out to see if you can make your foreign cash flows more stable and predictable. Recommended Reading Join our Treasury Community Treasury Masterminds is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click [HERE] or fill out the form below.
Franklin
Treasury and Fintech: Collaborating for Innovation and Automation
In our dynamic finance space, Treasury departments are increasingly looking to fintech companies to drive innovation and enhance financial processes. This collaboration is not just a trend but a strategic necessity, as it offers numerous benefits, including improved efficiency, enhanced risk management, and better customer experiences. Here, we explore how Treasury departments can effectively collaborate with fintech companies, drawing on relevant examples and references. The need for collaboration Treasury departments have traditionally been seen as back-office functions focused on managing cash flow, liquidity, and financial risk. However, the role of treasury is evolving. Modern treasury departments are now expected to provide strategic insights and drive value across the organization. This shift requires advanced technology and innovative solutions, which fintech companies are well-positioned to provide1. Benefits of collaboration Examples of successful collaborations Key considerations for collaboration Conclusion The collaboration between treasury departments and fintech companies is a powerful driver of innovation in the financial sector. By leveraging fintech solutions, treasury departments can enhance efficiency, improve risk management, and offer better customer experiences. As the financial environment continues to evolve, these collaborations will become increasingly important for achieving strategic goals and maintaining a competitive edge. Recommended Reading Join our Treasury Community Treasury Mastermind is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click [HERE] or fill out the form below to get more information. Notice: JavaScript is required for this content.
Jessica
Natural Hedging Vs. Financial Hedging: Navigating Currency Volatility
This article is written by GPS Capital Markets When we talk about managing currency risk, two approaches often come up: natural hedging and financial hedging. At their foundation, they are two different strategies for tackling the same problem: protecting your business from fluctuating exchange rates. Here we’ll break them down, using some real-world scenarios to help illustrate how companies deal with this challenge. Whether you’re running a multinational or a small business expanding overseas, understanding these tools is crucial to managing your bottom line. What is Natural Hedging? In simple terms, natural hedging is when businesses adjust their operations to minimize exposure to currency fluctuations naturally. In one example, a US-based company with substantial European sales might opt to open production facilities in Europe. By earning and spending in the same currency, the business reduces the impact of exchange rate volatility. In another example, a US clothing manufacturer sells heavily in the Eurozone. Instead of producing everything in the US and dealing with perpetual USD-to-EUR exchange risk, they open a factory in Germany. Now, they can pay their local employees and suppliers in euros while also receiving their sales in euros. This natural hedging strategy shields the company from exchange rate swings between the dollar and the euro, ensuring their costs and revenues are in the same currency. Interestingly, a recent poll we conducted showed that 23% of respondents rely on natural hedging to manage FX volatility. This approach is particularly appealing to companies expanding into new markets and needing to align revenues and expenses in the same currency. How Financial Hedging Works In contrast, financial hedging involves using financial instruments, like forward contracts or options, to lock in exchange rates for future transactions. While natural hedging adjusts business operations, financial hedging focuses on leveraging market tools to mitigate risk. Let’s say there’s a UK-based electronics company that imports components from Japan. They have a large payment of ¥50 million due in six months. Rather than risk potential yen appreciation against the pound (which would make the payment more expensive), the company uses a forward contract to lock in today’s exchange rate. With financial hedging, they secure a fixed exchange rate, ensuring their future payment won’t exceed their budget due to unfavorable currency movements. A recent poll revealed that 54% of companies actively use FX hedging programs, reflecting a clear preference for financial hedging when it comes to managing cash flow in uncertain times. These tools offer flexibility, especially in unpredictable markets. The Federal Reserve’s Role in Hedging Strategies Speaking of market unpredictability and their role in hedging strategies, it’s impossible to ignore the role of central bank policies. A recent poll asked, “How many base points do you think the FOMC will cut at the next meeting?” with 72% predicting a 25-bps cut. However, on September 18, the Federal Reserve surprised markets by cutting rates by 50 bps—something that was not predicted by our LinkedIn audience. This underscores the importance of having an expert with their finger on the pulse to make predictions and revise strategies at a moment’s notice. Using the advanced automated features of FXpert, businesses can also react faster than humans to market changes. FXpert’s ability to monitor markets and lock in trades across time zones far exceeds manual capabilities, providing businesses with an edge in managing currency exposure. The Dollar Index and Hedging Considerations Another factor businesses must consider is the performance of the U.S. dollar. With the Dollar Index trading near 2024 lows, companies relying on natural hedging or financial hedging need to keep a close eye on these trends. A recent poll indicated that 75% of participants expect the Dollar Index to close lower than it did in 2023. A weaker dollar can lead to higher costs for businesses that import goods, making financial hedging a key strategy to safeguard against such volatility. Choosing Between Natural Hedging and Financial Hedging Ultimately, choosing between natural hedging and financial hedging depends on your company’s operations, cash flow, and tolerance for risk. For businesses looking for a long-term operational solution, natural hedging offers a straightforward approach to reducing currency exposure. However, if market conditions or transactions are more fluid, financial hedging provides the flexibility needed to navigate short-term fluctuations effectively. Both strategies have their place, and successful companies often use a combination of natural hedging and financial hedging to optimize their exposure. Whether you’re expanding into a new market or trying to manage ongoing FX risk, understanding both approaches—and leveraging tools like FXpert—can help you make informed decisions and protect your business from unexpected currency swings. The Value of GPS Capital Markets’ Expertise in Financial Hedging When you decide to go the financial hedging route, GPS Capital Markets’ team of experts becomes an invaluable resource. Our experienced advisors not only help you craft a tailored hedging strategy that aligns with your business goals, but they also provide real-time insights into market movements. With access to advanced tools like FXpert, we can help you identify opportunities, lock in favorable rates, and manage trades seamlessly across global markets. Whether you need ongoing support or quick adjustments in volatile situations, GPS offers the expertise, technology, and service that ensure you’re always one step ahead in managing your financial risk. Also Read Join our Treasury Community Treasury Masterminds is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click [HERE] or fill out the form below to get more information. Notice: JavaScript is required for this content.
Treasury for Non-Treasurers: Crossing the Chasm (Part I)
Introduction We left off last week talking about the ‘The Chasm’ and saying that many treasuries end up in it. We also noted that non-treasury stakeholders won’t get material value-add unless they deal with a treasury that has crossed the chasm. It’s, therefore, worth understanding what it is and how to get out of it. And how non-treasurers can help. This part of ‘Crossing the Chasm’ explains the chasm. We will review practical ways to cross it next week. Who is in the chasm? There is no specific revenue tell for companies in the chasm. A company with $ 250 m revenue with a treasury can be a control-oriented treasury not in the chasm or in a stakeholder-oriented one in the chasm. A multi-billion-dollar revenue company can have a treasury that is anything from control-oriented to value-adding and externally focused, so anything from operational to strategic, outside the chasm, or tactical. Many factors are at play, and we will talk about them here. What causes the chasm? In a few words, it’s amount, culture and context. Amount An organisation with a low turnover doesn’t generate enough cashflows in numbers of transactions and or values. It can’t cost-justify a bigger, more sophisticated treasury. Culture Treasury has a culture. It is within finance, which has a different culture. That’s within a company with yet another culture. Other functions with different cultures surround it, some more important than others, such as procurement in a company with large purchasing requirements or HR in one looking after talented and rare employees. Plus, any of these can have dominant individuals within them with their own background cultures and personalities. Geographical aspects of culture Consider the following: If a company is headquartered and senior management is in and from a risk-averse culture, are the board and C-suite likely to allow the treasury to cross the chasm and start taking financial risks? Even in a case where the CFO and Treasurer are from low-risk-aversion cultures? It’s not likely. Nor if it’s the other way round. A high-risk-aversion treasurer will not support crossing the chasm no matter if the CFO or board might be open to it. So, to bridge the chasm, what’s needed is a major culture change. And that’s something no treasurer I’ve met is trained to lead. However, that training, or support from people with that training, is exactly what’s needed if a company wants to cross the chasm and go from being operational and tactical to strategic. “What gets measured gets managed”, Peter Drucker. This is an excellent time to say that cultural factors, including risk aversion, have been quantified and can be compared to each other in a culture change program. See Image 1 below. Quantification allows culture change planners to be more exact in how to structure successful culture-change programs, so this information is invaluable: Organisational Culture Culture is not all about nationality. It’s about organisational culture as well. And let’s not reinvent the wheel here. We’ll use the ‘Iceberg Model of Culture’ created by Edward T Hall in 1976 and shown in Image 2: Again, these conscious and unconscious cultural aspects are different at organisation, finance function, treasury itself, and for all other material stakeholder functions. It’s complex. But, “What gets measured gets managed” again: Quantitative ways to measure corporate culture exist. The best known, now over 40 years old, is the ‘Competing Values Framework’ by Quinn and Rohrbaugh. In the interests of brevity, I won’t get into it here, but please get in touch if you want more details. Simplifying and Concentrating on the Key Elements of Culture Clearly, there’s too much to analyse to decide whether and how to change in a practical way. So, although we should remember the big picture for any individual company, we can simplify. I have found from my work that, in most instances, the following are most important: 1. The geographical culture of the company 2. The geographical culture of the essential stakeholder functions 3. The geographical culture of the key personalities, which, for treasury, always includes but is not exclusive to the CFO and Treasurer 4. How each external partner (you, the non-Treasurers) perceives time compared to treasurers (more on this in a moment) 5. How each external partner uses language (again, more on this in a moment) 6. The organisational structures in both treasury and the partner functions 7. The KPIs and bonus systems The first three are easy to understand from the paragraphs above. The following three, though, are thought-provoking: Time perception: The easiest way to describe this is by providing an example. Accounting, FP&A, and tax get, analyse and use information at month-, quarter-, and year-end. This is so normal that it’s taken for granted. It’s embedded in the core values of the finance functions. On the other hand, treasury works with financial markets, where rates move constantly. Their perception of time, embedded in their core values, is different. As a result of the differences in perceptions about time, accounting has problems understanding why waiting for information relating to cashflows to be added to systems at a convenient time within the month is a problem for treasury, who need it as soon as possible. The same is true with errors that will, in their minds, be corrected at month- or quarter-end or even after. It’s not a problem for the rest of finance, why is it for treasury? This time perception difference causes tension and prevents them working together to evolve from tactical to strategic. Other functions have their own embedded, unconscious perceptions of time. The more functions there are, the more difficult it is to achieve mutual understanding. But, it’s vital to understand there’s no malice between departments not being aligned or moving not fast enough or too fast. Each function must understand the time perception of the other and what’s important to each, to optimise how they work together. Language: The use of language is also a subconscious, deeply embedded part of cultures and subcultures. Using the…
Nicholas
Deciphering Bank Analysis Statements: The AFP Service Codes
Transparency is critical in any relationship. Unfortunately, there is a long-standing inherent barrier to transparency in every relationship between a bank and a client, the bank analysis statement. Understanding the majority, let alone all of the charges depicted on a bank analysis statement, is difficult at best. I have personal experience with the challenges of understanding bank analysis statements. It took me months and more than one in-person meeting with a group of employees with a bank partner to understand the charges on their monthly bank analysis statements. Deciphering bank analysis statements became a regular part of my routine. I spent hours each month reviewing bank analysis statements and I often found billing errors. I know that Treasury professionals still face these same challenges. The format and structure of a bank analysis statement are far from consistent across different banks, and the structure of fees and verbiage on the statements for most banks change over time. The good news is that there are resources and technology that can help companies understand and banks deliver transparency in bank analysis statements. AFP Service Codes and Global Service Codes The Association for Financial Professionals (AFP) created and manage the AFP Service Codes©, which have served as the industry standard codes assigned by all major banks to their cash management services billed to companies since 1986. The AFP Global Service Codes© were created in 2011. The global codes were designed specifically for the international community. Unfortunately, many banks still do not leverage the AFP Service Codes© and/or the AFP Global Service Codes© on their bank analysis statements. Even if a bank leverages both code sets and assigns them correctly, the volume of bank statements and services consumed still makes benchmarking and managing bank fees from even a single bank cumbersome. Proper assignment of the codes by banks on bank analysis statements would allow Treasury professionals to perform analytics, cross-bank comparisons, and manage bank fees effectively. Bridging the Gap in Code Utilisation Unfortunately, most Treasury professionals do not even know that both code sets exist, let alone how to leverage them to benchmark and manage bank fees. Companies should collaborate with banks in understanding each line in a bank fee analysis statement and look to them to help in assigning services to the right AFP Service Codes© and/or on AFP Global Service Codes©. Some banks offer AFP Service Codes© and/or on AFP Global Service Codes© on analysis statements for categories of fees, but these codes can still be assigned incorrectly. There have been recent updates to the AFP Service Codes and the AFP Global Service Codes. An update was done to the AFP Service Codes© in 2020 and left only 32% of the existing codes unchanged, and an update to the AFP Global Service Codes© in 2023 modified or added half of the codes in this release. Even before these comprehensive code updates, it was not uncommon for banks that attempt to use either set of service codes to assign more than 40% of them incorrectly. Therefore, the potential for the misassignment of codes by banks on analysis statements and the challenges of understanding and benchmarking bank fees has become greater for treasury professionals over the past few years. The Future of Bank Fee Management The good news is that there are bank fee analysis solutions that give users access to an unprecedented range of datasets to help them evaluate and benchmark the costs of their banking operations across the globe. This empowers companies to identify inefficiencies, eliminate redundancies, and benchmark and manage bank services while removing an inherent barrier to bank relationship management success, a lack of pricing transparency. Companies need to understand what they are being charged by a bank partner to determine the value of that bank partner. Deciphering bank analysis statements is crucial in this process. Also Read Join our Treasury Community Treasury Masterminds is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click [HERE] or fill out the form below. Notice: JavaScript is required for this content.
Ernie Humphrey
Data-driven Treasuries are the Future and Here’s Why
This article is written by Palm Unleashing the Power of Data in Treasury Management The skills required to be successful in treasury are changing, and more and more treasurers seek to hire candidates who are proficient in data management. As data becomes a critical asset of all businesses, this too is reshaping how treasurers and CFOs design their functions. This blog will explore how data-driven treasuries are not just a trend, but the future of corporate finance. We’ll discuss the evolving role of key financial players, and offer practical insights to help your treasury stay ahead of the curve. The Rising Importance of Data in Treasury Management Data is often referred to as the new oil—a resource that fuels decision-making and strategy in modern businesses. In treasury management, data’s role is no less significant. It enables treasurers to gain insights into cash flow, liquidity, and risk management. In an era where precision and speed are crucial, treasurers need access to accurate and timely data to make informed decisions. This reliance on data not only improves operational efficiency but also enhances strategic planning. Gone are the days when cash flow forecasts were collected in spreadsheets. Now, Treasurers are utilising data and statistical models in Palm to develop their cash forecasting solutions. The traditional treasury functions focused on only a few core tasks such as cash management and financial risk management are rare. Today treasurers are expected to do much more. They need to anticipate cash shortfalls, optimise working capital, and ensure compliance with evolving regulations. Data provides the necessary insights to meet these demands effectively. By harnessing the power of data, treasurers can create predictive models that forecast future trends and prepare for uncertainties. The integration of data into treasury management processes allows for real-time monitoring and analysis. Palm uses API technology to connect to your banks, ERP and TMS so all data is centralised in one place. Allowing your treasury to become proactive rather than reactive. The Evolving Role of Treasurers and CFOs with Data As the landscape of corporate finance evolves, so too does the role of treasurers and CFOs. These key players are increasingly becoming strategic partners within their organisations, using data to drive critical business decisions. The days when financial leaders only focused on balance sheets and income statements are long gone. Today, they are expected to be data-savvy leaders who understand the broader economic context and its impact on their organisations. Treasurers and CFOs are using Palm to leverage data to break down silos across departments, fostering a more collaborative environment. By sharing insights from treasury data, they can provide valuable input into sales forecasts, marketing budgets, and operational plans. This holistic approach ensures alignment between financial goals and overall business objectives. Data-driven decision-making empowers treasurers to optimise their organisations’ capital structures. They can assess various funding sources, analyse interest rate trends, and evaluate currency risks to make informed choices. By incorporating data analytics into capital allocation decisions, treasurers can enhance returns on investments and reduce borrowing costs. This strategic use of data ultimately strengthens the organisation’s financial position. AI and Data Management Palm utilises artificial intelligence (AI) and machine learning algorithms to offer powerful tools for data analysis. By analysing historical data and identifying patterns, AI can generate accurate forecasts and identify emerging trends unknown to a human brain. This capability empowers treasurers to make data-driven decisions with the support of emerging technology. Furthermore, AI-driven automation streamlines repetitive tasks, freeing up valuable time for treasury teams to focus on strategic initiatives. Practical Tips for Implementing a Data-driven Strategy Implementing a data-driven strategy in treasury management requires careful planning and execution. Here are some practical tips to help your organisation get started: Define Clear Objectives: Begin by identifying the key objectives you want to achieve with data-driven treasury management. Whether it’s optimising cash flow, improving risk management, or enhancing decision-making, having clear goals will guide your strategy. Invest in the Right Technology: Evaluate different technology solutions available in the market and choose those that align with your organisation’s needs. Look for platforms like Palm’s that offer robust data analytics capabilities, integration with existing systems, and scalability for future growth. Build a Data-driven Culture: Foster a culture of data-driven decision-making within your organisation. Encourage collaboration between departments and provide training programs to enhance data literacy among employees. By empowering your team with the skills to analyse and interpret data, you can unlock its full potential. Data-driven Treasuries are the Future Data-driven treasuries represent the future of corporate finance. Treasurers and CFOs who embrace this paradigm shift will gain a competitive edge, positioning their organisations for success in an increasingly complex business environment. By leveraging data, these financial leaders can optimise operations, improve risk management, and drive strategic decision-making. Remember, data is not just a tool—it’s a strategic asset that holds the key to accurate cash forecasts, better cash positioning, better decision making and ultimately business success. Also Read Join our Treasury Community Treasury Masterminds is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click [HERE] or fill out the form below.
Are Bigger Banks Better? A Corporate Treasurer’s Perspective
Introduction In the world of corporate treasury, choosing the right banking partner is a crucial decision that can impact cash management, liquidity, and risk mitigation. Recent industry moves, such as UniCredit’s potential takeover of Commerzbank and BBVA’s multibillion-dollar bid for Spain’s Sabadell, highlight a trend toward consolidation in the banking sector. As banks grow larger, many corporate treasurers may ask: Are bigger banks truly better for Treasury operations? This article will explore the benefits and potential drawbacks of larger banking institutions from a corporate treasury perspective. We’ll dive into how size affects service offerings, risk, and relationship management, and provide insight into whether treasurers should prioritize size in their banking decisions. 1. Bigger Banks: The Benefits Larger banks typically offer a broader geographic footprint, which can be invaluable for multinational corporations. Treasurers managing complex, multi-currency operations benefit from a bank with a global network, simplifying cross-border transactions, foreign exchange, and cash pooling. Big banks tend to provide a wider range of services, from sophisticated derivatives for hedging currency and interest rate risks to advanced cash management systems. This breadth of products can meet more complex treasury needs under one roof, offering scalability as a business grows. Large banks are often better capitalized, making them more stable and less vulnerable to financial shocks. This can reduce counterparty risk for corporate treasurers, especially during economic downturns or periods of financial market volatility. 2. The Drawbacks of Bigger Banks As banks grow larger, treasurers may experience more bureaucracy and less tailored customer service. Larger institutions may focus on their most profitable clients, leaving smaller corporations or mid-sized firms feeling overlooked. Due to their size, large banks can be slower in responding to customer needs, particularly when it comes to customizing solutions or making decisions on credit facilities. Treasurers who need agility in their banking relationships may find this frustrating. Large banks often have more overhead costs, which can be passed on to their customers in the form of higher fees for services, from transaction costs to liquidity management solutions. 3. What Do Corporate Treasurers Need Most Bigger banks often have the resources to invest in cutting-edge technology, such as artificial intelligence (AI) and blockchain, which can drive more efficient treasury operations. However, technology alone isn’t always the answer. Treasurers also need a banking partner that understands their business and offers a strategic partnership, regardless of size. For many treasurers, the stability of their banking partner is paramount. Larger banks, with their diversified portfolios, tend to offer more security. However, diversifying across smaller, specialized banks can also spread counterparty risk. Conclusion: Bigger Isn’t Always Better—But It Can Be As corporate treasurers evaluate their banking relationships, the size of the institution should not be the sole determining factor. While bigger banks bring advantages in terms of reach, product breadth, and stability, smaller or mid-sized banks can often offer more personalized service and flexibility. Ultimately, the key is to strike a balance between the treasury’s unique needs and what a bank, regardless of its size, can offer. Treasurers should focus on the quality of the relationship, the bank’s ability to support strategic initiatives, and its capability to deliver innovation and stability in a rapidly evolving financial landscape. This framework considers both sides of the debate, allowing corporate treasurers to reflect on their own needs and the value bigger banks might or might not provide. Would you like to add any specific insights or examples from your experience? Recommended Reading Join our Treasury Community Treasury Mastermind is a community of professionals working in treasury management or those interested in learning more about various topics related to treasury management, including cash management, foreign exchange management, and payments. To register and connect with Treasury professionals, click [HERE] or fill out the form below to get more information. Notice: JavaScript is required for this content.
Treasury for Non-Treasurers (Appendices)
Appendices for the article: “Crossing the Chasm, Part II” Appropriate Contexts and Cultures for Method 1: When: 1. The organisation’s culture is control-oriented. 2. Some senior stakeholders are external and profit or value-add-oriented. 3. One or several stakeholders have the budget to explore new sources of benefit. 4. The company is profitable and stable. Inappropriate Contexts and Cultures for Method 1: (The opposite of the above and) When: 1. The organisation has conflicting personalities or functions that can sabotage or unconsciously prevent culture change. 2. There are other major and potentially conflicting projects in progress. 3. The treasury team members do not support the change. Actions Needed for Method 1 1. The new function must be physically separated from other control-oriented ones until the external- and customer-focus orientation is embedded. 2. Fresh external resources must be brought in to create the new culture. 3. Internal resources must be brought in to learn the new culture. 4. The external resources must already have the relevant technical and soft skills. They must learn about the organisation from the internal resources. 5. The internal resources must learn the technical and soft skills from the externally hired resources. 6. Positive results must be achieved fast to justify the sponsors’ willingness to do something that defied conventional wisdom in the organisation. In order to realise these fast results, the overall project must be broken down into smaller parts that, ideally, can be implemented quickly but still be seen as impressive when successful. 7. Management must not only fund the above but also provide political cover at high levels so that inappropriate ways of thinking are not brought in. Recommended Project and Change Management Techniques for Method 1 Project, change and cultural change management techniques are not all the same. Some are more people-oriented, others are results-at-all-costs, and others are flexible. “Culture eats [change] strategy for breakfast]”. The techniques must match the initial culture of the company or the end culture wanted, depending on the circumstances. In situations where method 1 is culturally and contextually appropriate, techniques emphasising results, flexibility and speed are needed: Project management: Best: Agile or similar Possible but not optimal: Lean, Critical Path, or similar Inappropriate: Waterfall or similar Change management: Best: Deming Cycle (PDCA) or similar Possible but not optimal: ADKAR, Kotter’s Theory, or similar Inappropriate: Lewin’s Model or similar Appendix 2: General Framework for Method 2 Appropriate contexts and cultures for Method 2: When: 1. The organisation’s existing culture is control-oriented 2. There is or are senior stakeholders who are external and profit or value-add-oriented 3. The organisation is being restructured to be external- and results-orientated Inappropriate contexts and cultures for Method 2: (The opposite of the above and) When: 1. The company is already external-oriented. Key people leave. 2. The company’s restructuring strategy is poorly thought-out or detailed. Chaos happens. 3. The company is facing external pressures that distract management from effectively restructuring. Actions Needed for Method 2 1. Senior personnel with strategic treasury experience must replace the previous treasury leaders. 2. Other personnel who don’t embrace the new culture must be replaced 3. Budgets for systems and infrastructure change must be made available 4. The change must happen fast Recommended Project and Change Management Techniques for Method 2 In situations where method 1 is culturally and contextually appropriate, techniques emphasising results and speed are needed. Flexibility is an advantage but not a necessity: Project management: Best: Critical Path or similar Possible but not optimal: Agile or similar Inappropriate: Lean and waterfall and similar Change management: Best: Kotter’s Theory Possible but not optimal: Deming Cycle (PDCA) or similar Inappropriate: ADKAR, Lewin’s Model and similar Appendix 3: General Framework for Method 3 Appropriate contexts and cultures for Method 3: When: 1. The cultures empower staff to innovate and give them time to work on individual projects 2. The external environment is good, and the business itself is prosperous and stable 3. There are already skilled people in the treasury function, or the organisation is willing to buy in expert support when needed Inappropriate contexts and cultures for Method 3: (The opposite of the above and) When: 1. The company is not yet at the stakeholder-oriented level. Treasuries focused on control above anything else will not walk the talk on empowering personnel. 2. The staff does not feel like they are in a safe environment to propose ideas or be supported to overcome obstacles. 3. Unreasonable expectations and timelines in which to show success are set. 4. Management doesn’t plan for and communicate what will happen to the employee projects if organisational priorities change, making what should be a morale-enhancing effort morale-destroying instead. Actions Needed for Method 3 Taken from the analogous situations 1. Management determines how much time per week will be allocated to self-guided improvement projects. 2. Strongly recommended: Management creates charters of intent and holds pre-mortem meetings (“If the projects fail because of us, it will be because of … and the responsibility will be … ’s”). A ‘no-fault’ project-ending process must be in place for employee psychological safety. 3. Management regularly educates employees on strategic challenges at cascading levels relevant to the employee’s position. 4. Employees self-organise into groups, preferably cross-functionally, to brainstorm and find solutions to propose to management. 5. If a proposal is accepted, the employees work on it, bringing in new people or getting trained on what is necessary if a colleague is unavailable to join the group. 6. One person in the group takes on the role of project manager, or this role is rotated between the team members, ensuring the project progresses and appropriate stakeholders are updated on the progress. 7. After each strategic update meeting, the team members decide whether to continue with their existing project or change to another, which is currently more critical regarding the organisation. This meeting and the decision-making must be managed carefully to make sure time and resources are not spent uselessly. 8. The projects progress until success is achieved, or, if it isn’t, a…
Fraud detection models and machine learning: All you need to know
This article is written by Trustpair International laboratory Octapharma used to manually check each IBAN and bank details change request. After a potential fraud attempt, the company turned to Trustpair. By using the machine learning fraud detection solution, any future fraud attempts would be outlined. Also, the digital processes for checking bank details offer better collaboration with the purchasing department. What is machine learning? Machine learning is a type of artificial intelligence. It means that a system can learn and perform autonomously without clear instructions. It uses historical data sets to learn patterns. Machine learning methods can range from recommendations of products to buy or films to watch all the way to detecting invoice fraud in a business. There are four types of machine learning: How does machine learning work in fraud detection? There are several steps for how machine learning works in practice. Fraud detection software based on machine learning already does these for you. Let’s go into more detail… 1. Insert data By inputting data into the machine, it has a baseline to work from. When using supervised learning, the data has to be classed as ‘good’ (non-fraudulent customers) or ‘bad’ (fraudulent customers or those with chargeback claims) data. 2. Determine fraud signals Fraud red flags will be used as triggers to indicate when fraudulent activity may be occurring. Fraud signals and features can be split into categories and we have provided an example for each: 3. Prepare the algorithm The algorithm can learn from a business’s own dataset to make predictions. The training period is useful because the system is not using live customer data, it is historical. So, any false positives in training won’t impact the customers. 4. Deploy the model Following these steps, there is a model that is tailored to your business and ready to be put into practice. 5. Test and iterate As part of the testing process, give the algorithm some data that is new to the model but that the business knows the outcomes of (fraudulent activity). Therefore, in the test the algorithm will either pick up on the fraud or fail to do so, and then we know whether it’s working. It will also give an idea of the performance and accuracy of the model. 6. Set the right fraud risk score threshold Once the algorithm is in action and you have ensured its precision, fraud risk scores are created for every transaction. They are between 1 – 100 and the closer to 100, the higher the risk of fraud. If it’s a low-risk score, the transaction should be approved. However, if the risk score is high, then the purchase should be reviewed by the customer or the bank to ensure there is no fraud. It’s often on your business to set these risk scores accordingly to find the right balance. If it’s too low, there may be lots of false negatives (fraud that goes unnoticed). However, if it’s too high there can be lots of false positives (non-fraud transactions that are blocked) as this impacts customer satisfaction. It is worth adding that instead of a risk score, Trustpair’s process offers a risk status that can be positive, negative, or unconfirmed. Some software solutions don’t provide scores, as it can be difficult for companies to know what to do with them. Fraud detection models vs traditional fraud detection measures Traditional fraud detection measures were only able to detect fraud that it has been programmed to detect. For example, if a trigger is set to check over five digit vendor payments, if that transaction is made, the trigger will go off. However, the traditional measures cannot recognize fraud that it hasn’t been programmed to. Also, it cannot adapt to new methods of committing fraud. On the other hand, machine learning fraud detection models can learn from their experiences and therefore challenge new fraud methods. They are flexible and adaptable to new patterns of fraud. Machine learning systems are also more cost-effective because they are automated and often don’t need manual input or reviews from fraud analysts. Their time can be spent elsewhere. Examples of machine learning for fraud detection Machine learning based algorithms can outline credit card fraud attempts via fraud signals. Two of the fraud signals may be triggered if a fraudster makes several high-value financial transactions on a new account. Also, the customer and billing name may not line up. The machine learning algorithm can inspect invoices and pick up on duplicate invoices or a credit card bank account number of a supplier that has been involved in suspicious transactions and it can flag it up. Learn more about invoice fraud here! The models can recognize patterns internally within the accounts payable team. Say that an employee within your business is approving an unusually high number of invoices or approving invoices to a new, unverified supplier, that could be a method of internal fraud. That is because the unverified supplier could be a fake vendor with account information that aligns with the employee’s own account details. You may have logged in to your work email on a different computer or laptop in a different location to where you normally do and had to confirm your identity via a code sent to your mobile phone. It is machine learning algorithms that do this and helps in the case of an account takeover where someone does have your work email password and is trying to log in to your account from another country. It is important that your business is able to check to see that your suppliers are who they say they are, that they are legitimate, and that they are not fraudsters. A machine learning model can help identify this. A platform like Trustpair uses machine learning to detect any suspicious data or status change that raises fraud red flags. For example, Trustpair checks that the identity of the vendor corresponds to its bank account details thanks to its machine learning based algorithm. Recap A machine learning system can be incredibly useful in a business’s efforts to combat fraud. Now you know the steps to take to set up a machine learning model and how it can help with…