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HARNESSING ANALYTICS IN THE FIGHT AGAINST FRAUD

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ANALYTICS

By Anna Lykourina, EMEA Fraud Analytics Expert at SAS

 

In the past, the fight against fraud has been a bit hit-and-miss. It has relied on auditors to identify patterns of behaviour that just didn’t quite fit. They often only detected problems months after the event. And then organisations had to claw back stolen funds through legal processes.

In a world where transactions happen in under a second, however, this is no longer acceptable. We need to be able to detect fraud immediately, if not before it happens. Customers want safe and protected data that is not vulnerable to identity theft through company systems. But they still want to be able to pay online and in seconds. The stakes are high, but fortunately new tools and techniques in fraud analytics are enabling companies to stay ahead of fraud.

 

Trusting machines to do the work

Machines are much better than humans at processing large data sets. They are able to examine large numbers of transactions and recognise thousands of fraud patterns instead of the few captured by creating rules. On the other hand, fraudsters have become adept at finding loopholes. Whatever rules you set, it is likely that they will be able to get ahead of them. But what if your system was able to think for itself, at least to a certain extent?

New approaches to fraud prevention combine rules-based systems with machine learning and artificial intelligence-based fraud detection systems. These hybrid systems are able to detect and recognise thousands of fraud patterns and learn from the data. Automated analytical-based fraud detection systems can reveal novel fraud patterns and identify organised crime more consistently, efficiently and quickly. This makes them a good investment for businesses across a wide range of sectors, including public sector, insurance, banking, and even healthcare or telecommunications.

How, though, can you harness analytics as a tool in your fight against fraud?

 

Identifying needs and solutions

The first step is to identify which options you need. Probably the best way to do this is through a series of company-wide workshops with the fraud analytics experts to determine what analytics you need, which data to include and techniques to use, and what results to report. They can also identify the ideal combination of rules-based and AI/ML approaches to detect fraud as early as possible.

Companies looking towards advanced analytics for fraud detection will need to make a number of decisions. They will need to optimise existing scenario threshold tuning, explore big data, develop and interpret machine learning models for fraud, discover relevant information in text data, and prioritise and auto-route alerts. There may be industry-specific decisions to make, too, such as automating damage analysis through image recognition in the insurance sector. By automating these areas, companies can both significantly reduce human effort – reducing costs – and improve their fraud detection and prevention.

 

Benefits of an analytical approach to fraud detection and prevention

Companies that are already using an analytical approach for fraud prevention have reported several important benefits. First, the quality of referrals for further investigation is better. Investigators also have a much clearer idea of why the referral has been made, which improves the efficiency of investigation. Analytics also improves investigation efficiency by reducing the number of both false positives (that is, alerts that turn out not to be fraud) and false negatives (failure to spot actual frauds). This improves customer experience and reduces risk to the company.

Analytics makes it possible to uncover complex or organised fraud that rules-based systems would miss. Companies can group together customers and accounts with similar behaviors, and then set risk-based thresholds appropriate for each scenario.

There are several sector-specific benefits too. For example, insurance firms can identify fraudulent claims faster to prevent improper payments from going out. Claims investigation is likely to be more consistent because claims are scored through technology, algorithms and analytics, rather than by people. Finally, it becomes possible to shorten the claims process through automated damage analysis. It is no wonder that organizations across a wide range of sectors are placing analytics at the heart of their anti-fraud strategy.

Business

THE EVOLVING TECHNOLOGY NEEDS OF THE FINANCE DEPARTMENT

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Jennifer Sims, Senior Consultant at Xledger

 

The world of finance software is evolving quickly, but with many new software contenders entering the market it can be a mindfield for organisations. Many finance teams are already using multiple accounting apps and software packages for bookkeeping, payroll and invoicing to service individual needs. Whilst it may work fine for now, this segregated approach isn’t sustainable for long-term growth. The world is swiftly moving to agile, automated ways of working. As a result, there is a growing need to choose suppliers that can fulfil multiple functionalities within the one platform.

Financial software is evolving at such a pace that it can be difficult to keep up. Changing up a finance solution is a big step and ease of migration can be a substantial factor in determining which solution provider to go with. But how do you choose a solution that will grow with your business and still offer something innovative in five or ten years down the line? The fear is always that non-techie organisations will end up falling behind, but in such a highly concentrated industry, how do you decide which solution would work best for you?

 

Cloud-first: the term that makes all the difference 

You could find a ‘cloud-based’ service with an application that comes with automated audit trails to make it easier to meet compliance and record-keeping obligations, for example. But for a solution to offer all of the many future benefits promised by the cloud, it needs to have been built specifically for a cloud environemt from the outset – ie. not an on-premise built system that has been later adapted. Cloud-first services (true cloud) were always intended to leverage economies of scale, cope with live updates, be accessible from anywhere with an internet connection, and to scale rapidly, to name just a few of the many benefits.

When we talk about innovation in financial technology, we’re not just talking about software that makes it easier for the financial controller to create reports. If eliminating reliance on Excel spreadsheets is the only tangible benefit you have to really shout about, you are missing out on the real deal. With ‘true’ cloud finance software the sky is the limit.

Finance and accounting technology needs to directly meet the needs of the finance function and support the wider business needs.  When looking at accounting software platforms you’d be hard pressed to find one that doesn’t now promise ‘cloud-based’ enterprise resource planning (ERP) capabilities. The cloud is nothing new, but it’s the way that a solution harnesses this environment that makes a real difference. And here is where there is a need to read between the lines.

 

Automate more with true cloud 

Historically, repetitive and manual tasks are typical of the finance role – from invoice postings to expense claims handling – these can overwhelm the finance team. Research by Xledger[1] has found that an enormous 91% of CFOs and finance decision makers are carrying out at least one of these repetitive tasks as part of their job. What’s more, senior finance leads are averaging a whopping 25 hours per week carrying out repetitive and manual tasks, compared with 15 hours for other finance decision makers.

A modern, true cloud finance system can enable your business to automate repetitive tasks and provide one source of truth so that teams can make informed business decisions that will help to scale a business. Bank reconciliation, dashboard creation and reporting are just some of the tasks that can be handled automatically.These capabilities are aiding overtasked finance teams and saving hundreds or thousands of hours a year.

Whilst different companies are at different stages in their digital transformation what is clear is keeping up with the latest technology is fundamental to the future success of an organisation.

Xledger is a true cloud finance solution. The basics include invoicing, robust general ledger accounting, detailed slice and dice reporting, purchase orders, billing, VAT reporting, and cash and bank payments. It also adds process and structure to the enterprise with procurement and inventory, budgeting and forecasting, and project accounting. Users are always on the latest version of the software and with regulation more stringent than ever today, Xledger is ISO 27001 accredited.

Choosing the right provider for your financial ERP solution comes down to whether it has the fundamentals right. When hosting all of your vital data in the providers’ own servers, it should evidence a highly tested security process that comes with backup services as standard.

As our demand for technology capabilities grows and as ERP models progress, innovation will become the structure for growth – and there is no end to the possibilities.

 

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HOW RETURNS ABUSE AFFECTS RETAILERS

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By Aaron Begner, EMEA GM at Forter

 

Accompanying the significant growth in ecommerce over the past 12 months, is the need for retailers to manage the impact of a growing array of fraud and abuse challenges. One type of fraud that can easily fly under the radar is the abuse of a merchant’s returns policies.

Returns abuse can be difficult to detect and prevent for retailers, as often it is a challenge to identify fraudulent behaviour vs. a ‘usually-good’ consumer trying to bend – but not break – return policies. Therefore, it’s often a challenge to identify how returns abuse actually affects retailers. Here are three of the biggest ways that returns abuse negatively impacts business.

 

Lost Revenue

The most obvious effect that returns abuse has on a business is lost revenue, which can be significant. Research indicates that returns abuse may be costing retailers up to $15 billion per year. When fraudsters purchase items with the intent of abusing returns policies, the retailer makes no profit. Furthermore, it stops legitimate customers from purchasing the items they want, as fraudsters who don’t want the items are moving them around.

Various types of returns abuse can profoundly damage retailers’ bottom lines. Some tactics, such as shoplisting, where fraudsters try to obtain a refund for a list of products listed on a perfectly valid receipt, yet that they never purchased to begin with, can significantly impact retailers’ bottom line.

 

Increased Operational Costs

Returns abuse doesn’t only affect revenue pertaining to the products themselves. There are also operational costs to consider. An increase in returns abuse will often lead to more consideration being put into checking every return, for signs of abuse taking place. This can range from missing tags to damage or wear on the product. This process can be time-consuming, meaning more resources might be necessary to continue operating in an efficient manner. Handling and warehousing costs can also begin to increase, with returned items becoming significantly less valuable.

 

A Poor Customer Experience

As returns abuse continues to increase, many retailers will feel pressure to tighten their return policies. This could range from reducing the allotted time for eligible returns, to only issuing store credit instead of cashback. In some cases, more extreme measures such as requiring a restocking fee for more expensive merchandise will be taken.

While these are all effective ways to help diminish the effect of returns abuse on retailers, they can also have an adverse effect on a retailer’s customer experience. If loyal customers have become accustomed to a more flexible and forgiving return policy, they could be taken by surprise when it’s more difficult for them to return their items.

Ultimately, it can be tricky to balance the two. Returns abuse negatively affects retailer revenue and the overall business, but so does a poor customer experience.

 

The Negative Impact of Returns Abuse Cannot Be Understated

Returns abuse is often overlooked. It can be difficult to detect, but significantly impacts revenue and operations. Because stricter return policies may restrict loyal customers, the reputation of a retailer’s business can be affected. Poor customer experiences can lead to bad reviews and a loss of current and potential customers. Because of this, returns abuse prevention should be a top priority for all retailers.

With this information in hand, retailers can get a better understanding of how returns abuse affects their business and why they need to put a prevention plan in place, as soon as possible.

 

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