Detecting fraud by numbers
Is your business inadvertently handing over the keys to its safe to unscrupulous employees or even total strangers? The Association of Certified Fraud Examiners (ACFE) estimates that 5 per cent of all revenue is lost to occupational fraud every year, while research by the Accounts Payable Network reports that 44 percent of organisations have experienced some level of fraud in the last three years.
A trinity of factors known as the “fraud triangle” can align to push a usually law-abiding citizen to do something unethical (in fact, it’s often a seemingly model employee in collusion with a supplier). All it takes is pressure, such as personal debt, opportunity, and the rationalisation that the fraudulent act is somehow justifiable or “no big deal” in the grand scheme of things.
Fraud isn’t 100 percent preventable – deception and opportunism are part of human nature. But there are steps you can take to deter and detect fraudulent attempts through continuous monitoring and surveillance. In fact, the ACFE found that companies could halve time to detection and reduce losses by two-thirds by adopting proactive fraud prevention measures rather than a reactive posture, such as an internal audit, accurate vendor master data or simply waiting for a tip-off.
Looking for clues
Fraudsters will always leave forensic clues behind, so P2P organisations are increasingly turning to data analysis to aid their detective work. For example, fraudsters often create fake invoices in rounded amounts (with no pennies or cents), companies can therefore rank vendors by those with a high percentage of rounded-value invoices. It’s also worth applying “fuzzy” matching to identify similar invoices as well as exact duplicates, such as those with values within a 5 percent range, those where one value is exactly double the other, or those with amounts that start with the same four digits.
Another tell-tale clue is invoice values that are just conveniently below management approval thresholds, so businesses can run searches to identify invoices that are <3 percent under the approval amount and flag them for investigation. Monitoring vendor invoice volumes can also alert companies to abnormal behaviour: a sharp uptick in invoices may be attributable to a legitimate increase in business, or an indication that a fraudster is getting more confident (or complacent) at stealing money.
Using fraud analytics to uncover suspicious activity
It can be labour-intensive to proactively carry out manual, spreadsheet-based analyses - that’s why organisations are adopting analytics solutions that use complex algorithms to do the heavy lifting of unearthing suspicious activity. For example, using a scoring system, it’s possible to identify abnormally large invoices for a given supplier by identifying the average and standard deviation of their values.
Another useful principle is Benford’s Law, also known as the ‘first-digit phenomenon’. This observes that certain numbers, such as 1 and 2, naturally occur more frequently as leading digits in data sets (about 30 percent and 17 percent of the time respectively) than those beginning with 8 and 9 (around 5 percent ). If you’re too young to remember logarithmic tables or skipped stats class, it basically means that the first digits in data sets like invoice values aren’t distributed uniformly, as you might imagine, but along a curve. So if the first digit of invoices is say, eight, 50 percent of the time rather than 5 percent , something may be amiss. While any anomalies aren’t conclusive proof of fraudulent activities – it is possible to produce a false positive – it can suggest that deeper digging is called for.
By using multiple variables as check points and more sophisticated analysis, it’s possible to score suppliers, either individually or on aggregate for risk indicators, in much the same way as the now-familiar practice of credit-scoring quantifies lending risk.
An ounce of prevention is worth a pound of cure
While all of this detective work after the fact can be highly effective, it’s worth remembering that automation can have a dramatic impact on internal and external fraud prevention. Invoice fraud thrives in an environment with poor visibility into the invoice process and weak payment controls. Adopting purchase-to-pay analytics can provide the visibility to help everyone in an organisation to manage spend, remove waste, cut costs and optimise use of working capital all whilst preventing fraud.
Matt Ingman is UKI Marketing Manager, Basware
Follow @SupplyChainD on Twitter.
NTT DATA Services, Remodelling Supply Chains for Resilience
Joey Dean, the man with the coolest name ever and Managing Director in the healthcare consulting practice for NTT DATA and is focused on delivering workplace transformation and enabling the future workforce for healthcare providers. Dean also leads client innovation programs to enhance service delivery and business outcomes for clients.
The pandemic has shifted priorities and created opportunities to do things differently, and companies are now looking to build more resilient supply chains, none needed more urgently than those within the healthcare system. Dean shares with us how he feels they can get there.
A Multi-Vendor Sourcing Approach
“Healthcare systems cannot afford delays in the supply chain when there are lives at stake. Healthcare procurement teams are looking at multi-vendor sourcing strategies, stockpiling more inventory, and ways to use data and AI to have a predictive view into the future and drive greater efficiency.
“The priority should be to shore up procurement channels and re-evaluate inventory management norms, i.e. stockpiling for assurance. Health systems should take the opportunity to renegotiate with their current vendors and broaden the supplier channel. Through those efforts, work with suppliers that have greater geographic diversity and transparency around manufacturing data, process, and continuity plans,” says Dean.
But here ensues the never-ending battle of domestic vs global supply chains. As I see it, domestic sourcing limits the high-risk exposure related to offshore sourcing— Canada’s issue with importing the vaccine is a good example of that. So, of course, I had to ask, for lifesaving products, is building domestic capabilities an option that is being considered?
“Domestic supply chains are sparse or have a high dependence on overseas centres for parts and raw materials. There are measures being discussed from a legislative perspective to drive more domestic sourcing, and there will need to be a concerted effort by Western countries through a mix of investments and financial incentives,” Dean explains.
Wielding Big Tech for Better Outcomes
So, that’s a long way off. In the meantime, leveraging technology is another way to mitigate the risks that lie within global supply chains while decreasing costs and improving quality. Dean expands on the potential of blockchain and AI in the industry.
“Blockchain is particularly interesting in creating more transparency and visibility across all supply chain activities. Organisations can create a decentralised record of all transactions to track assets from production to delivery or use by end-user. This increased supply chain transparency provides more visibility to both buyers and suppliers to resolve disputes and build more trusting relationships. Another benefit is that the validation of data is more efficient to prioritise time on the delivery of goods and services to reduce cost and improve quality.
“Artificial Intelligence and Machine Learning (AI/ML) is another area where there’s incredible value in processing massive amounts of data to aggregate and normalise the data to produce proactive recommendations on actions to improve the speed and cost-efficiency of the supply chain.”
Evolving Procurement Models
From asking more of suppliers to beefing up stocks, Dean believes procurement models should be remodelled to favour resilience, mitigate risk and ensure the needs of the customer are kept in view.
“The bottom line is that healthcare systems are expecting more from their suppliers. While transactional approaches focused solely on price and transactions have been the norm, collaborative relationships, where the buyer and supplier establish mutual objectives and outcomes, drives a trusting and transparent relationship. Healthcare systems are also looking to multi-vendor strategies to mitigate risk, so it is imperative for suppliers to stand out and embrace evolving procurement models.
“Healthcare systems are looking at partners that can establish domestic centres for supplies to mitigate the risks of having ‘all of their eggs’ in overseas locations. Suppliers should look to perform a strategic evaluation review that includes a distribution network analysis and distribution footprint review to understand cost, service, flexibility, and risks. Included in that strategy should be a “voice of the customer” assessment to understand current pain points and needs of customers.”
“Healthcare supply chain leaders are re-evaluating the Just In Time (JIT) model with supplies delivered on a regular basis. The approach does not require an investment in infrastructure but leaves organisations open to risk of disruption. Having domestic centres and warehousing from suppliers gives healthcare systems the ability to have inventory on hand without having to invest in their own infrastructure. Also, in the spirit of transparency, having predictive views into inventory levels can help enable better decision making from both sides.”
But, again, I had to ask, what about the risks and associated costs that come with higher inventory levels, such as expired product if there isn’t fast enough turnover, tying up cash flow, warehousing and inventory management costs?
“In the current supply chain environment, it is advisable for buyers to carry an in-house inventory on a just-in-time basis, while suppliers take a just-in-case approach, preserving capacity for surges, retaining safety stock, and building rapid replenishment channels for restock. But the risk of expired product is very real. This could be curbed with better data intelligence and improved technology that could forecast surges and predictively automate future supply needs. In this way, ordering would be more data-driven and rationalised to align with anticipated surges. Further adoption of data and intelligence and will be crucial for modernised buying in the new normal.
These are tough tasks, so I asked Dean to speak to some of the challenges. Luckily, he’s a patient guy with a lot to say.
On managing stakeholders and ensuring alignment on priorities and objectives, Dean says, “In order for managing stakeholders to stay aligned on priorities, they’ll need more transparency and collaborative win-win business relationships in which both healthcare systems and medical device manufacturers are equally committed to each other’s success. On the healthcare side, they need to understand where parts and products are manufactured to perform more predictive data and analytics for forecasting and planning efforts. And the manufacturers should offer more data transparency which will result in better planning and forecasting to navigate the ebbs and flows and enable better decision-making by healthcare systems.
Due to the sensitive nature of the information being requested, the effort to increase visibility is typically met with a lot of reluctance and push back. Dean essentially puts the onus back on suppliers to get with the times. “Traditionally, the relationships between buyers and suppliers are transactional, based only on the transaction between the two parties: what is the supplier providing, at what cost, and for what length of time. The relationship begins and ends there. The tide is shifting, and buyers expect more from their suppliers, especially given what the pandemic exposed around the fragility of the supply chain. The suppliers that get ahead of this will not only reap the benefits of improved relationships, but they will be able to take action on insights derived from greater visibility to manage risks more effectively.”
He offers a final tip. “A first step in enabling a supply chain data exchange is to make sure partners and buyers are aware of the conditions throughout the supply chain based on real-time data to enable predictive views into delays and disruptions. With well understand data sets, both parties can respond more effectively and work together when disruptions occur.”
As for where supply chain is heading, Dean says, “Moving forward, we’ll continue to see a shift toward Robotic Process Automation (RPA), Artificial Intelligence (AI), and advanced analytics to optimise the supply chain. The pandemic, as it has done in many other industries, will accelerate the move to digital, with the benefits of improving efficiency, visibility, and error rate. AI can consume enormous amounts of data to drive real-time pattern detection and mitigate risk from global disruptive events.”