Bottomline’s Marcus Hughes shares with listeners his view on the intelligent use of data and analytics and how this drives improved financial performance for companies across their payables, treasury and receivable activities.

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Data Analytics in Treasury: The bedrock of better financial performance

Jacqueline Powell: Hello, and welcome to the Payments Podcast. I am Jacqueline Powell, and today I am delighted to host Marcus Hughes, he does strategic business development at Bottomline.

This episode will focus on the intelligent use of data and analytics, and how this drives improved financial performance for companies across their payables, treasury and receivable activities. Together, we will explore how aggregated data, including ERP, creates valuable insights, and helps finance and treasury teams to make better informed decisions.

Marcus has a wealth of knowledge in banking and payments, so I’d like to ask him to share his views on how data analytics makes it easier for companies to manage their finances more efficiently and grow their business.

Welcome, Marcus, and thank you for joining us.

Marcus Hughes: Hi, Jacqui, and thank you for inviting me. It’s good to be back, and I’m always happy to share a few thoughts on how best to use cloud-based technology to empower corporates to drive growth and profitability.

Jacqueline Powell: Excellent. So, kicking off then, can you tell me what is so important about data, and why it is gaining so much attention now. Haven't we always had data?

Marcus Hughes: Yes, exactly. Corporates have always had lots of data. But never before have we been able to access it in real time, and to convert it instantly into something truly meaningful. Now, data can be transformed into valuable information and analysis, with which we can drive greater insights into what has happened, what is happening, and most important of all, to predict what is likely to happen in the future. And with greater accuracy than before. And with this, we can therefore drive enhanced financial performance.

Jacqueline Powell: Ah, okay. So, it’s all about the insight. So, how does data analytics help finance teams then? Where is the value?

Marcus Hughes: The importance of data has risen really high on the agenda in recent times. To the point that we might even say that data is now the new green energy for corporates. Data can be used intelligently to power higher performance across areas like payables, treasury and receivables.

And these areas have historically worked in silos, despite being highly interdependent on each other. But with new technologies and better use of data, these units can now be truly interconnected, allowing a flow of data between these systems, as well as the ERP, of course.

So, data analytics and techniques like machine learning and predictive analytics, are becoming the essential tools for treasurers and other financial decision-makers. Whether they be in accounts payable, accounts receivable teams, or in central finance. Data can be obtained from multiple sources within a business, as well as from outside the business, such as from multiple bank accounts. And also, in real time.

Inside the business, there is a wealth of data in corporate systems, like the ERP, the treasury management systems, as well as accounts payable and accounts receivable, and the CRM system, or the customer relationship management system.

But the real value likes in combining this enterprise data with banking data, and then getting a single view. That is a summary of all this data by using dashboards, which show a business’s key performance indicators.

Financial decision-makers can greatly benefit from analytical tools which enable them not only to measure their KPIs, like day sales outstanding, days payable outstanding, cash conversion cycle, etc., but also to improve these metrics. This has a highly positive effect on an organization’s overall financial performance. And the analysis of this rich combination of data leads to great insights and better decision-making.

Advanced techniques, such as artificial intelligence and predictive analytics can be applied to historic performance and can therefore improve the accuracy of forecasts throughout the business cycle. This approach means an integrated system can generate actionable suggestions for improving financial performance.

Jacqueline Powell: Yes, I can certainly see how better data management can power better performance in treasury. Perhaps I can ask you to give us some practical examples?

Marcus Hughes: Yes, of course. Let’s look at cash flow forecasting. As we know, improving cash flow forecasting is often voted the number one priority for treasury teams. And many organizations are still over-reliant on spreadsheets for this complex and important task. There are a whole series of data elements, from the treasury management system, the ERP system and the bank accounts themselves, which need to be combined to create an accurate cash flow forecast.

For example, we need to bring together future inbound payments relating to outstanding invoices, maturing deposits, and investments, tax refunds, etc. And we need to include future outbound payments, relating to supply invoices, payroll, maturing loans, interest payments and tax obligations, that kind of thing.

But most important of all, we need a solid starting point, with accurate and fully up to date cash balances and uncleared items on multiple bank accounts in multiple currencies. These cash flow forecasts must be constantly reviewed against the actual cash flow, using tools like variants analytics.

By analyzing the variants of previous cashflow forecasts, predictive analytics can then be used to improve the accuracy of future forecasting. Some of the inbound and outbound flows are highly predictable, such as loan repayments on a fixed maturity date.

Whereas other items are less easy to predict, for example, when a customer will actually pay an invoice or not. If an item is not paid or received on the anticipated date, then it needs to be rolled forward in that cash flow forecast, to a suitable future date, and then to be checked, of course, as to whether it has then been received.

So, efficient liquidity management is a core requirement in any well-functioning treasury department, in order to ensure that a corporate has adequate liquidity to meet its financial obligations, as those obligations fall due.

But a treasurer must balance this requirement with the need to maximize returns on surplus cash, and also to minimize interest charges on loans and overdrafts. This can be achieved by ensuring surplus funds are not left sitting idly on current accounts. Instead, these available funds really should be put to work, to cover likely overdrafts on other accounts, or placed in deposit accounts or other investment instruments, in order to ensure a reasonable return.

So, working in conjunction with cashflow forecasting, an efficient treasury management system also allows treasury teams to set up automated sweeps and cash concentration pools. So, by associating an account hierarchy of parent and child accounts, with rules establishing minimum and maximum balance thresholds, an efficient sweeping system can calculate the optimum set of bank transfers to support a corporate’s efficient liquidity management.

The treasury management team can then accept or amend these recommendations, and the TMS will simply create the definitive payment instructions and place this in a cashflow queue, for approval and then submission to the bank.

Another important activity in any large corporate is efficient reconciliation or cash allocation. Many different pieces of data need to be reconciled on increasingly frequent basis, such as once a day or even in real time. And this is required to reduce operational risks and avoid errors.

It is also essential to constantly reconcile bank statements against the ERP ledger, to allocate cash correctly and therefore be able to take income to profits. To assemble all this data and analyze it in real time, and perform essential tasks like cash allocation, are easier in systems which span the full payments and cash life cycle. So, in particular, payables, treasury and receivables.

It is important to combine the data transformation in this capability with reconciliation, as data can often arrive in disparate formats, and can therefore be normalized before reconciliation can take place.

Jacqueline Powell: Those are very practical everyday examples. Thank you, Marcus. Now, we know many corporates have a large number of banking relationships and accounts in multiple countries, how can they use the aggregated data to keep on top of all of this activity, and manage these relationships effectively?

Marcus Hughes: Well, bank relationships for payments and cash management are driven by a number of factors. These include each bank’s geographical reach and their cash management capabilities in the countries where a corporate needs banking services, such as access to local payment and collection instruments.

Another very important factor in the background is the willingness of a bank to make credit facilities available. This is one of the underlying drivers for selecting banks, recognizing that they will sometimes make their credit facilities conditional on receiving a share of a corporate’s payments and foreign exchange business.

Finally, the quality of service and pricing are highly relevant factors in choosing a cash management bank. This needs to be assessed not just when selecting a new bank, typically as part of a request for proposal process, but also these factors need to be reviewed on an ongoing basis, at least once a year.

Bank data includes important information, such as the transaction fees and interest rates which a bank charges, or the remuneration which a bank pays on credit balances and deposits. It also includes the foreign exchange rates, which banks bid for spot and forward foreign exchange transactions.

So, a good treasury management system will enable a treasury team to aggregate all this data and perform an analysis of all these items, and assess whether a bank is actually competitive or perhaps failing to comply with the terms and conditions which were agreed with a customer.

Having this information at their fingertips is incredibly useful when a treasury team holds their regular review with their bankers. Clearly, having easy access to such precise insights is one of the best ways to negotiate improved terms and conditions. It also makes it easier to select which banks to retain and which bank relationships to exit, potentially, if rates and performance don’t improve.

Jacqueline Powell: Okay. I can see how this data puts treasury teams in a powerful position, to ensure decent pricing and full compliance with contracted conditions. If I may, Marcus, I’d like to move on to accounts receivable and accounts payable. Could you take a moment to explain to our listeners how data can drive better financial performance in these areas?

Marcus Hughes: Yes, of course, with pleasure. Continuing the important theme of managing costs, let’s look at spend management in procurement and accounts payable. It is increasingly important for a business to have control of its expenditure in sourcing and procurement. This ensures a corporate’s cash is being spent in the most efficient manner possible, and in accordance with an established plan or policy.

A business therefore needs to select and manage its suppliers carefully, in order to gain the best possible terms relating to price and quality. And then, of course, just like in treasury, it is important to track that these contracted terms are actually being fulfilled.

To achieve this improved spent management and analytics, data can be taken from various sources and checked. Invoices provide a wealth of information, such as what goods and services are being purchased, what taxes are due, and which taxes, like VAT, can be reclaimed.

Spend management systems make it easier for organizations to better manage their spend, by providing a series of analytical tools and insights to improve control and visibility of all aspects of sourcing. This would include the selection of suitable suppliers, the negotiation of terms and conditions, with proper documentation of course, as well as efficient resource management.

This end-to-end process enables an organization to track and ensure that a corporate entity, and of course its individual departments, are spending cash according to a plan and that they are achieving predetermined KPIs. Best in class systems should also be able to analyze supplier performance and contract fulfilment, while measuring captured savings that are achieved through the purchasing process.

A corporate also wants to be able to identify which of its suppliers are most important strategically, and which of them should therefore be prioritized in terms of making payments in a timely manner. While other less important suppliers might be made to wait a little longer for improved days payable outstanding performance.

Jacqueline Powell: Quiet, Marcus. Moving onto receivables more specifically, what can you tell us about using data to drive efficiency in this area?

Marcus Hughes: Okay, I think one of the best examples in receivables would be using data to ensure that funds are collected from customers in the most efficient and timely manner possible. This of course is extremely important in accelerating a corporate’s inbound cashflow, which is the lifeblood of any business, as we know.

Within a corporate, the collections and debtor management team need tools to assess the credit risk of customers, and they need to be able to track and chase the payment of sales invoices. A collections team benefits massively from a dashboard providing a clear picture of all outstanding invoices’ current status. In terms of when they're due and, of course, if they are past due.

From there, a user should be able to drill down to access full details of any invoice. A treasury management system is used to capture data from banks regarding inbound payments that are being received from customers. This is combined with data relating to sales invoices, which is in the ERP system. Aggregating this data enables the collections team to identify which invoices are paid and when, in terms of being paid early, on time or late or, worse still, even unpaid.

This data is used to analyze the payment history of customers and assess this on an ongoing basis. Customers’ past performance is used to create a credit score and, with the means of algorithms, to predict their propensity, or likelihood, to pay invoices in the future. Data helps the business to create a risk analysis and credit score on customers based on past payment performance, which is really important.

This ongoing analysis means that a collections team can quickly decide which customers are more likely to be late payers, and therefore on which customers they should focus, in order to chase payments on invoices, and therefore minimize the likelihood of late payments.

Aggregating all this data means the collections team can create an accurate cashflow forecast of inbound payments relating to sales invoices. This is driven by analytics of payment terms and individual customers’ past performance in setting their invoices.

A CRM system, a customer relationship management platform, provides valuable data on sales forecasts. These forecasts combine with analysis of customers’ propensity to pay, become a valuable sub-set of data, which feeds into a treasury team’s consolidated cashflow forecast.

In the background, an automated dunning process tool should allow easily-configurable, regular and personalized communication with customers, in order to track and guide those customers smoothly along the collections process. All this helps to accelerate and maximize inbound cashflow for businesses, which is hugely important for any business.

Jacqueline Powell: So, we have covered off the here and now, but looking forward, there are several new payment initiatives and regulations under way. I would like to take a moment just to ask you to explain to us how these new formats, like ISO20022, for example, can help improve data.

Marcus Hughes: You're right, Jacqui. There is an important change program going on in payment systems around the world. As many payment professionals will know, a new message schema, called ISO20022, is now globally accepted as the best way to standardize and modernize payments and financial messaging.

Global adoption of this network independent standard will make interoperability between payment systems so much easier. To deliver this objective, there is an ambitious global migration going on over the next four years, to adopt this new format in the world’s principal payment systems. And that includes SWIFT’s global financial messaging network.

This will affect not only treasury payments and real-time payments, but also bulk payments, which are going through the accounts payable team, like payroll and supplier payments. And it will also affect collections like direct debits, and new payments instruments as well, like the request to pay. So, this new format will have an important and highly positive impact in all types of payments.

Most important, from the point of view of data, is that this switch to ISO20022 will allow payments to carry a great deal more structured data, as well as standardizing payment formats, which were previously inconsistent and much less structured. And it’s important to know that this structure data is machine-readable, so it requires less human intervention.

A major reason why regulators are keen to see widespread adoption of this new format is that it is going to make it easier to automate compliance with anti-money laundering requirements. This will help enormously in the fight on fraud and financial crime.

That ISO20022 format has many structured fields which can be made mandatory for including important details, such as the names and addresses of the ultimate beneficiary, the originator of the transaction and the intermediary bank. This means payments which use this format can include all the information necessary in a machine-readable format, to comply with the FATF16 requirements and the EU wire transfer regulations, which are really important.

This comprehensive structured data will improve automation and reduce the number of false-positives when screening payments against sanction lists and watch lists, hence it is going to reduce many of those frustrating delays in cross-border payments.

Another important advantage is that this new format will significantly increase efficiency. It will result in lower costs and higher straight-through processing rates. The increase in structured information carrying a message will make it easier to track payments in real time across multiple banks and different payment systems. And the new format will also reduce the risk of errors, since users will be able to include additional payment details and references.

With this rich data, in a structured format, it will make it much easier for parties receiving payments to achieve higher levels of automated reconciliation and cash allocation. This in turn will enable a much richer level of analytics and insights about why payments are made and to whom.

Jacqueline Powell: It certainly sounds like it will increase efficiency. Talking of payments, we often hear about the increased level of fraud, something that financial institutions and companies across the globe are trying to combat. Can you share with us your view on how data analytics can help the fight against fraud?

Marcus Hughes: Absolutely. I definitely agree that cyber fraud and financial crime are a major worry for many organizations, as there are a growing number of banks and corporates who are falling victim to cyber-attacks. What is clear is that fraudsters are increasingly sophisticated. With the rise of cyber fraud, it is essential that organizations up their game and ensure they have multiple layers of defense.

Technology and data analytics have a big role to play here. But we should also remember the basics. It is, of course, essential to encrypt data, both at rest and in transit. Payment systems must obviously have an internal control framework with secure access, segregation of duties, four-eyes approval of workflow, a full audit trail and multi-factual authentication.

But on top of all these practical measures, one valuable technique, which is seeing growing adoption is to deploy a cloud-based system to monitor not only transactions but also user behavior. This helps to detect unusual activity. This strategy should really form a central part of any organization’s layered cyber defense.

Advanced analytics and intelligent profiling of user behavior and of payments enable a system to understand what are normal transaction patterns and therefore what is normal user behavior. This data is then used as a basis for detecting abnormal and potentially fraudulent transactions and in real time.

A powerful fraud analytics system combines rules-based detection with machine learning. This enhances the rules engine, to reduce false-positives, because machine learning updates the system continuously. A best in class payment fraud prevention system must have the ability to flag suspicious transactions and block these transactions, which are potentially fraudulent payments, all in real time.

It is vital that these suspicious transactions are stopped before they are released into the payment system. In that sense, unfortunately, the growth in real-time payments also means a rise in real-time fraud problems, meaning there is probably only a split second to react. So, payment fraud solutions must work in real time and across multiple payment channels.

Jacqueline Powell: Yes, without doubt, I think stopping fraud in real time and further upstream has become an absolute necessity. Following on from fraudulent payments, do you think data analytics can also help prevent invoice fraud? And if so, how?

Marcus Hughes: That is a good question, of course. And important advantage of accounts payable automation is that it can make a major contribution to preventing fraud. Invoice fraud is a growing issue across the globe, with scammers working on very sophisticated ways to prevent fraudulent invoices in the hope of getting paid.

When digital invoice processing and accounts payable automation are implemented properly, data verification of invoices can significantly mitigate the risk of invoice fraud.

I’ve got just a few examples of key data verification checks, which can cut the risk of fraudulent invoices in the accounts payable area. These processes should of course be automated.

First, checking your supplier and their lists against fraud databases helps to ensure your suppliers are legitimate. Business number validation is also important, by making checks against government and commercial register records, to ensure the business is who they say they are.

Validation of supplier details is important too, so you should always check whether supplier details on an invoice match your ERP supplier records. Duplicate checking is also helpful, for making sure you have not previously received this invoice and potentially paid this invoice already.

And purchase order matching identifies whether the invoice references a purchase order, and whether the supplier and purchase details reconcile with what is on that invoice.

Finally, bank account verification should be used, to validate that the bank account listed on the invoice matches the one in your supplier records.

Jacqueline Powell: Thanks, Marcus, those are very helpful tips. Looking ahead now, can you tell our listeners where you see the most significant growth in data? Or perhaps where companies can use data more efficiently?

Marcus Hughes: Well, a major growth area for the smarter use of data, especially consumer data, is open banking. That’s a big topic, probably for another day. But to give just a brief comment, Open Banking is making it easier for organizations to access bank accounts and transaction data, provided the end customer has given his approval for this data to be shared.

And one of the most successful use cases is that people and small businesses applying for finance can authorize a bank or online lender to access their data in real time and make quicker lending decisions, based on the analysis of the loan applicant’s balance and transaction activity across their various bank accounts. So, that is an important growth area.

But returning to the main theme today, of achieving more effective data analysis in payables, treasury and receivables, I would highlight that the e-invoicing market is growing rapidly, and that it involves the secure exchange of large quantities of data. The important thing about e-invoicing today is that there are a growing number of countries mandating the use of e-invoicing.

It is these new government mandating schemes which are driving much of the growth in the invoicing, at more than 20% a year. Some of the more obvious benefits of e-invoicing include greater processing speed, lower cost, improved visibility and control, as well as a reduced risk of fraud, as we have seen.

But this only explains in part why a growing number of countries have introduced mandatory e-invoicing, including a number of EU states.

Some of the early examples of e-invoicing success stories are in Latin America – Brazil, Chile and Mexico, and other countries in the reason, all mandated B2B, business-to-business, e-invoicing, a number of years ago. But it is important to note that, in these countries, the mandatory adoption of e-invoicing was driven primarily by the need to close the unpaid tax gap, by driving better VAT reporting.

In other words, those tax authorities in those countries wanted to capture more tax from businesses that was going unpaid. And it is the rich data in an invoice which provides the most complete information for tax authorities who are seeking to establish how much tax is actually due to be paid.

Anyone doubting how well the invoicing works in capturing more revenue for the tax authorities should only consider how Mexico has improved tax yields by more than a third, since implementing e-invoicing. This tax-related e-invoicing model is known as clearance, because all B2B invoices have to be submitted electronically via a government-approved platform.

This allows the tax authorities to perform real-time validation and to audit all invoices before they reach the end customer. This sharing of data enables the tax authorities to accurately capture and calculate the tax due on each invoice.

The successful implementation of clearance e-invoicing models has encouraged a wide number of countries to mandate e-invoicing for all business-to-business transactions, especially where significant tax revenues are going unpaid.

There was a report by the European Union’s Directorate General for Taxation and Customs Union, which found that a massive €137bn of expected VAT revenues went uncollected – so unpaid – across the region in 2017. Italy was by far the poorest performer, with €33bn of uncollected tax that year.

Italy therefore introduced mandatory clearance of e-invoices just a couple of years ago, and has already increased tax receipts by over €4bn, thanks to the new system.

In the last two years, nearly 30 new B2B invoicing mandates have been introduced by governments around the world, that includes Europe, but also Asia, for example India, Taiwan and Vietnam. France has also mandated B2B invoicing from 2023, with Spain, Portugal and Greece also making preparations. So, there is a clear shift towards adopting a clearance model of e-invoicing in many countries.

Jacqueline Powell: Marcus, I also understand that some governments are imposing e-invoicing on suppliers doing business with public sector organizations, to improve efficiency. Can you shed any light on these initiatives?

Marcus Hughes: Yes, that’s absolutely right. In some countries, sometimes as a preliminary step towards mandating full business-to-business e-invoicing, governments are introducing business-to-government, or B2G, e-invoicing mandates.

Many governments are working hard to create a streamlined public sector administration, which is paperless, data-driven and data-focused. In Europe, we have seen this strong trend in recent years. The shift was driven initially by a European Union directive, which set out build a pan-European standard for e-invoicing.

But it also required that the technology had to be in place across all EU member states by the end of 2018, and then to drive the steady adoption of business-to-government e-invoicing. More than 100,000 public administrations and agencies across Europe are affected by this directive.

It has also forced all companies trading with those government and public sector agencies to implement their own solutions, in order to meet these new regulations. And in the last couple of years, a large number of EU member states have introduced mandatory business-to-government e-invoicing. So, just for example, the Netherlands, Italy, France, Spain, Portugal, Belgium, Germany and Poland. So, that is quite a serious list of important countries.

For some years now, the European Union has promoted a protocol and a common standard, which is known as PEPPOL. This stands for Pan-European Public Procurement Online. But PEPPOL has actually already expanded far beyond Europe. Indeed, there are PEPPOL initiatives under way in Australia, New Zealand and Singapore, just to name a few.

As a significant step in this modernization program, the NHS in the UK is the first UK government entity to use PEPPOL for its procurement and invoice automation. I think other public sector entities in the UK will follow in their footsteps.

Jacqueline Powell: Yes, it certainly sounds like it’s a positive initiative, Marcus. So, far, we have looked at treasury, payables and receivables. But earlier, you mentioned that these three units could be increasingly integrated, thanks to the better sharing of data and enhanced analytics. So, as we draw this podcast to a close, could you explain to our audience how these three disciplines all come together?

Marcus Hughes: Certainly. Working capital is a key metric in improving a corporate’s financial performance. A corporate ERP provides data on when sales invoices were sent and when supplier invoices were received. These ERP data can be combined with bank statement data, to show when these invoices were paid, both inbound payments and outbound payments.

This combination of data enables a business to calculate its days sales outstanding, or DSO, and its days payable outstanding, or DPO. And these two metrics should be analyzed alongside how much inventory a business holds and for how long. In other words, its days inventory outstanding, or DIO. Measuring and improving these three metrics – DPO, DSO and DIO – enables a company to optimize its working capital.

In turn, improved management of working capital has a direct and positive impact on the business’s cash position. Also, on its operating costs and its profitability. Hopefully, this shows the high degree to which payables, treasury and receivables are interlinked and interdependent.

The intelligent use of data analytics can really transform how finance professionals work, by providing them with unprecedented real-time control and visibility of their payables, treasury and receivables, all through a single platform, which is securely connected to multiple banks.

I would say the consolidation, automation and digitization of these processes enables better decision-making and improved financial performance, while complying with a complex regulatory environment.

The objective here is to aggregate enterprise and banking data in real time and to provide a single view of all cash management activities and in multiple currencies. All this can be presented on a personalized and informative dashboard, which identifies trends and highlights risks, whether that relates to fraud and financial crime, or foreign exchange and interest rate movements.

Data analytics and machine learning drive better decision-making, improved working capital management, faster cash allocation, more accurate cashflow forecasting and more effective spend management. All of that, while optimizing bank charges and investment returns.

Jacqueline Powell: It certainly sounds beneficial. I’d like to just thank you for sharing your perspective today, Marcus, it has been fascinating to hear the role data analytics can play for treasury. That’s all we have time for today, but stay tuned to the Payments Podcast channel and we’ll be back soon, with more insights into the fast-changing world of business payments. We hope you found this episode useful.

It just remains for me to thank you, Marcus, for sharing your views with our listeners and me.

Marcus Hughes: It has been a pleasure. Thank you, Jacqui, and see you again soon.


Why it Matters

Corporate treasury hasn't always been able to access data in real-time, and convert it instantly into something truly meaningful. Now, data can be transformed into valuable information, driving greater insights into the past, the present and the future. And with enhanced accuracy.


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