Moving swiftly through the analysis and due diligence of a funding opportunity is key to maintaining deal momentum, and ultimately converting an opportunity into a live working capital program.

This process can be particularly challenging for portfolio-style receivables programs, where it’s important to understand the makeup of an entire debtor portfolio and not just focus on the top “x” or larger debtors.

Data plays an important role in this process, but there’s often a fine line between how much information you ask a seller to provide versus what the seller can provide relatively easily. We’ve probably all encountered situations where the seller can’t easily provide what we’re asking, becomes disinterested, and ultimately switches off.

Over the last 15 or so years, we’ve seen a significant change to corporate attitudes regarding data sharing, and until relatively recently, most mid-cap corporates were very reluctant to share their receivables data. I make the deliberate distinction between a mid-cap and an SME, as banks and insurers were often able to put greater pressure on an SME to share its data or else risk not getting their funding or insurance program.

Mid-cap and larger corporates increasingly understand the arbitrage between sharing their precious receivables data and achieving the working capital or insurance program they need. Technology is also helping this process, and the reliability of automated data connectors, coupled with their ease of implementation, can be a game-changer if positioned properly. Not only do these automate the process of collecting and transferring detailed receivables data, but in the eyes of the corporate, they also outsource the often onerous responsibility and compliance elements of accurate data provision.

Data connectors and our automated PASS reports give us the ability to reliably shorten the triage and due diligence processes, maintaining deal momentum, providing a competitive advantage, and hopefully improving conversion rates.

Ready to learn more?

Contact us and find out how our solutions are helping financial institutions to overcome barriers and offering new products and services.

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In this edition of ‘Receivable Only’ we’re focussing on receivables data manipulation and the hidden world of white-collar fraud.

Across all our receivables programs, we process in excess of 1 million invoices a night.  These range from invoices processed for trade credit insurance purposes to invoices considered for receivables-backed funding eligibility through to invoices analysed purely for portfolio analysis and credit monitoring reporting.  Regardless of why they’re being provided, every invoice generally has the same characteristics – debtor details, an issue date, a due date, a value and a close date if closed.

As a rule, we expect first to receive details of a new invoice overnight following the invoice issue, and then we’d expect to see updates to that invoice as payments or credits are allocated towards the invoice closure when we’d expect to also receive a close date. There are legitimate circumstances when we might see other forms of invoice update, such as correction of provided details being one, but this tends to happen early in the life of an invoice.  Due date extension within a maximum extension period is another, but this assumes the underlying insurance policy has an MEP provision. 

In a certain sense, Aronova is a bit like a credit card company in that we track each and every invoice during its lifetime, automatically look for trends or suspicious invoice behaviour, and, for years, provide our insurance, funding, and credit monitoring partners with ‘anomaly reporting’ — the identification of potentially suspicious invoice behaviour.

The scenario we see most is where a corporate has a trade credit insurance policy with a maximum credit period clause that restricts insurance to those invoices with, for example, a maximum tenor of 90 days.  We receive an invoice with a 90-day tenor, and assuming there’s capacity within the aggregate tests, we process this invoice as “insured”, and the policy beneficiary trades on the basis that the policy covers the invoice. 

A few days later, we get an update to the invoice that extends the due date by 15 days, which now breaches the 90-day maximum tenor restriction.  We can now invalidate the insurance on this invoice from a trade credit insurance perspective. However, what if the policy is being used to support a receivables finance program and the invoice has already been sold?  There’s no simple solution, mandatory repurchase is certainly an option, but things are starting to get messy.

This is just one of the many examples we see where suspicious data change is occurring, and in some programs, we’re not talking about the odd change here or there, but wide-scale, repeated changes.  There’s often a fine line between genuine data correction, approved due date extensions, and more sinister data manipulation.  We all rely on accurate and trustworthy data to make decisions, power AI, operate programs and to drive increasing levels of business automation, but with this comes perils and the often hidden world of white collar fraud.

Ready to learn more?

Contact us and find out how our solutions are helping financial institutions to overcome barriers and offering new products and services.

The post Data Manipulation – The hidden world of white-collar fraud appeared first on Aronova.

Economic outlook

As if Covid-19 was not bad enough, we now have the spectre of a no-deal Brexit looming closer by the day. Whether you believe that they’ll finally get a deal done or not, it inevitably leads to even greater levels of uncertainty.

Early in December, the OECD downgraded its outlook for the UK economy amid surging coronavirus cases and has warned of a hit from a no-deal Brexit:

“Brexit would entail physical and financial disruptions of different magnitudes across sectors, with exports falling by more than 30% in a few manufacturing sectors (notably the motor vehicle and transport, meat and textile sectors) and by almost 20% in the financial and insurance sector.”

Effects on behaviour

History tells us that not only do these uncertain times damage companies’ performance but they also lead to significantly increased risk of fraud, as stress in the economy changes people’s behaviour. This month, Global Banking and Finance Review wrote about the increased risk of fraud and described the ‘Fraud Triangle’. The Fraud Triangle is a framework explaining the factors that cause someone to commit fraud:

• The first factor is pressure. This is the risk that is most likely to cause Directors, CEOs, CFOs or mid-management employees to cross the line. An increase in pressure in any organisation contributes to a heightened fraud risk. Companies are facing liquidity challenges, leading to missed obligations such as rent or loan repayments, and many are having to consider alternative sources of finance. In addition, there are the less tangible pressures such as reduced morale and the challenges of keeping teams running from people’s homes.

• The next factor is opportunity. Working from home and having a reduced workforce in the traditional place of work presents a considerable opportunity for fraud. Many of the controls and mitigating processes are severely compromised, and therefore present individuals with an opportunity to commit fraudulent acts.

• The final factor in the fraud triangle is rationalisation. It is possible in the COVID-19 context, with large numbers of employees being made redundant or furloughed, that some individuals may rationalize committing fraud. They may believe they are in some way helping the business in the short term, or gaining a personal advantage, by looking for ways to benefit from a fraudulent act.

The need for improved controls

In these turbulent times, keeping control of a working capital finance programme is more critical than ever. As we learn more about the Brexit deal, or lack of one, the behaviour of decision makers will undoubtably change. The uncertainty in the market place and changes in payment patterns represents a huge risk to potential funders.

The application of technology to give funders and insurers up-to-the-minute visibility of the changes in risk and performance of funded portfolios can no longer be put off. In 2021 ability to quickly identify changes in portfolio’s performance will be vital. Those relying on periodic updates from a manual source and spreadsheets will find they are unable to react quickly enough to the issues that organisations will face. There may be huge changes in payment performance between one report and the next. This poses a material risk to the programmes as well as being very poor at spotting potential fraud.

Aronova

Our technology protects our partners in both settled and turbulent times. We provide the support and visibility to enable you to keep lending, to protect your portfolios and minimise the risk of fraud. For more information please contact us.

You can read more about fraud risk in our article The Invisible Fraud In Working Capital Finance.

You can learn more about how we help organisations increase portfolio performance in our article Increasing The Profitability Of Working Capital Programmes.

The post How a volatile economy and changes in buyer behaviours can increase risk and fraud appeared first on Aronova.

It’s an unfortunate fact of modern business that potential fraud is never far away, not least because the methods used by fraudsters have become increasingly sophisticated over the past few years. The digital age presents them with as many opportunities as it does the businesses they’re targeting. This creates a conundrum for those organisations that want to take advantage of the benefits of technology and data, but understand that doing so increases risk.

Nowhere is this felt more keenly than finance, where deception is more common than you’d like to think and often hidden within the detail and complexity of trade finance programmes. Fraud is not typically covered by trade finance insurance policies, so counter-parties to these transactions are highly exposed to the tricks of fraudulent sellers, and it’s funders who bear most of the burden of the ever-present risk.

Simply put: it’s extremely difficult to avoid well-planned fraud, so what can organisations who provide and manage trade finance programmes do to protect their investors and their investments?

Data is the answer here. When fraud lurks in the detail, understanding data helps to flush it out. By being able to easily identify the signs of potentially fraudulent behaviour, appropriate action can be taken to avoid potentially disastrous consequences.

The growing threat of hidden fraud

Most of the documented fraud in trade finance is based on common ruses that are well known, yet often very hard to stop. Fresh air invoicing is one obvious example: in which the seller sets up false client records and builds up a small trading history. Then, after lulling the funder and/or insurer into a false sense of security, issues larger and more frequent invoices before disappearing with the funds.

The organisations who run programmes are well aware of this type of fraud and are are using technology and obligor verification in solutions such as ours to take steps to eliminate it. But there is another type of fraud that is becoming increasingly more pervasive throughout trade finance, simply because traditional reporting methods are completely blind to it.

Undetectable minor tweaks

This type of fraud involves the subtle manipulation of individual data points to bypass funding eligibility criteria. All funding programmes control risk through setting criteria or eligibility rules: funders or insurers may, for instance, impose certain geographical or currency restrictions, concentration caps or minimum asset performance requirements as a condition for funding.

Once the programme has been set up with all the necessary criteria in place, funders and transaction counter-parties are generally unable to check every detail of every transaction against their original records. This is where the gaps that fraudsters exploit can open up.

In receivables finance for instance, minor details in the data record of invoices presented for funding are altered, ensuring that sellers receive funding for invoices, despite knowing that the invoice in question never met the agreed eligibility criteria.

In many cases, the perpetrators don’t even consider it fraud. In their eyes, since they intend it to be paid in the long run, no one ultimately loses. However, the practice is clearly fraudulent and introduces invisible layers of risk into the programme, unanticipated and uncovered by insurance in the case of invoice default, which is impossible to mitigate by traditional methods.

This is where data and behavioural analysis must be employed to help close gaps down.

Example fraud scenario
Let’s take a very simple example where a programme will fund invoices from US-based companies, in US dollars, with a maximum tenor of 90 days

• On day one, a seller presents an invoice that conforms to these criteria. It passes all the checks and funding is released
• Five days later, the seller changes a single data point on the invoice – they extend the tenor from 90 days to 120

This could be an honest mistake while inputting data details into an accounting system. Indeed, where a small number of sporadic instances occur, this is most likely what it is.

However, it could also be systematic manipulation of programme requirements:

• The seller’s buyer always pays on or around the due date, and the seller believes they will continue to do so
• The seller needs a bit more funding, so they change a minor data point on the record, knowing that this will never be flagged in the reporting they provide
• As the bank eventually gets its money, they are none the wiser and nobody is the victim – or so it seems

By manipulating the terms of funding in this way, the seller is passing risk on to their funders and committing fraud in doing so. The seller has obtained their funds illegally, and should the buyer default on payment (with no source of funds to settle the debt) it jeopardises the programme and it may fall to the funder to shoulder the loss.

In this instance, these behaviours often happen recurrently with identifiable patterns of data alterations over time.

Protecting programmes with insight

With more sophisticated sellers able to flaunt programme restrictions, the threat of this hidden fraud in trade financing is nearly impossible to identify with the traditional, periodic reporting that still supports the bulk of transactions today. The only way to effectively mitigate the risk of this fraud is a systematic approach to the monitoring of data, using technology to provide you with the right insight and the tools to take fast, decisive action.

Getting away with manipulating data relies on victims being blind to the fraud. Data analysis opens up visibility of your programme and raises red flags around suspicious data changes. The right analytical tools expose patterns of behaviour that indicate potential fraud. Historical data gathered during the evaluation phase of the programme and daily feeds of updated information can be analysed to build a picture of buyer and seller behaviours over time. All those ‘harmless’ little tweaks disguising frauds will be flagged as anomalies, allowing you to address them before they become real problems. Insight into behaviours both prior to funding and once the funding is in place helps to protect all parties to the transaction for the life of the programme.

How trade finance technology helps

• Identify sellers and buyers within a working capital finance transaction against a database of more than 330 million global businesses
• Gain visibility of (and manage limits on) geographical, sector and group concentrations
• Systematically apply and monitor eligibility criteria for every new invoice and obligor
• Monitor, and alert against, anomalous seller and obligor behaviours that may identify potentially fraudulent activity

The post The invisible fraud in working capital finance appeared first on Aronova.

Corporate fraud and invoicing

According to PwC’s 2020 Global Economic Crime and Fraud Survey, economic crime has reached its highest levels in the past 24 months, with 56% of UK businesses surveyed stating they were impacted by fraud, corruption or other economic crime.  Nearly half of these frauds being perpetrated internally.  

Throw into the mix the devastating impact Covid-19 has had on many company cashflows and we probably have the perfect storm.  Increasing desperation probably means an even greater propensity to commit fraud, with financial fraud being high on the hit list. 

As the likelihood and sophistication of corporate fraud increases, so must the tools used to identify and respond to these threats. 

What does fraud look like for corporates involved in receivables-backed finance? Well, examples include the invoice that’s sold, only for the issue or due date to change so the terms exceed the allowable maximum credit period, or the invoice whose value or advanced amount changes post sale.  

Sure, some of these are innocent data corrections, but when regular patterns start emerging, transaction parties must question just how innocent these changes really are. More importantly, all parties involved in a programme need a way of automatically dealing with these ‘innocent’ changes and a way to identify this potentially fraudulent activity. As part of our ongoing innovation, we have developed a new application called ‘Collateral Shield’ to help. 

A couple of months ago, our Head of Partnerships & Alliances, Ben Grant wrote an article called ‘The Invisible Fraud in Working Capital Finance’ on just this very subject. From the feedback we’ve had, we’re not the only ones to see or suspect that this is happening. Post-sale changes to receivables data are more common than many originally thought.

Aronova is ideally placed to help police these ‘innocent’ changes. We receive daily invoice data directly from the Corporate, we process the data to assess eligibility and we’re effectively the first line of defence in the receivables finance chain. We know which invoices are sold and we can identify where significant post-sale data changes occur. Of course, identification is just one part of the story. The actions taken next are what really count and it’s where our Collateral Shield technology we can make a real difference. By automatically detecting threats and then implementing a series of actions, we can protect the transaction parties from the effects of post-purchase data changes.

Collateral Shield

Collateral Shield is a really interesting piece of ‘always-on’ technology that sits discreetly behind a receivables-backed working capital programme. It works by monitoring significant data changes to sold receivables and executing a series of corrective actions when changes occur.

The significant changes we’re interested in are those that would potentially affect eligibility if an invoice were to be re-assessed. For example, changes to invoice terms, invoice value or advanced amounts. More dramatically, we’re also monitoring for changes to debtor identification as this could affect multiple invoices due to credit limit, activity sector or country aggregation tests.

Once we identify a significant change, and depending on a programme’s set-up, we can first auto-repurchase a sold receivable, then automatically re-assess it for eligibility (excluding any invoice ageing tests).  Finally, so long as the changed invoice is still eligible, we can automatically resell the invoice back into the funding programme.  But crucially, if a retested receivable fails eligibility, it won’t be resold.

How we help

Collateral Shield protects transaction parties with an auto-response mechanism to counteract the risk of invoice and white-collar fraud.  It can be switched on or off for each funding programme and different policing levels can be configured per client. In summary, it’s highly adaptable and can be built to the precise requirements of the programme and its constituent parts.  Its abilities seamlessly integrate with our standard Movements Reporting suite to ensure invoice level visibility, monitoring and programme reporting. After seeing the technology in action, the majority of our clients have either added this to their reporting suite or are in the process of upgrading. 

Source:
PwC’s Global Economic Crime and Fraud Survey 2020

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