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Differentiating Between Bad Debt and Hidden Fraud

Over the past decade, we’ve seen the process of digitalisation impact almost every area of daily life. From websites and mobile apps to social media and online shopping, the Internet has become an omnipresent part of how we communicate with each other, consume products and conduct our business.

The digital transformation that’s occurring has, unfortunately, made us more susceptible to various types of online fraud. Businesses need to adopt new digital strategies that can keep their online banking, financial data and business operations safe from opportunistic fraudsters.

Much of the online fraud that occurs today’s misidentified as bad debt or missed payments from clients or consumers. However, these often turn out to be cases of undetected fraud where the victim isn’t forthcoming or doesn’t know they are being defrauded. It might be a cloned credit card or a hacked smartphone, but cases of online fraud are rising in South Africa and across the globe.

Data analytics will play an important role in fraud management and protection for any modern business. Fraud prevention teams utilise various types of analysis to comb through financial data and identity potential fraud. Preventing fraud’s usually done by monitoring and analysing past financial transactions and events to help determine the likelihood of a future transactions being fraudulent.

Credit or debit card fraud and online banking fraud can be detected by identifying historical instances of digital fraud and using those features to distinguish between what’s likely to be bad debt and what’s likely to be fraud.

Despite the ever-increasing variety and quantity of online fraud, subscription fraud through telecommunications remains the number one type of fraud around the world, by far. This demonstrates that fraudsters value smartphones, mobile apps and other IoT devices as much as they value loans or credit cards.

The misclassification of hidden fraud for bad debt

The misclassification of banking, application, subscription and other types of online fraud for bad debt’s a very common occurrence. What may present as a doubtful account or defaulted payments, often turns out to be some kind of undetected or unreported fraud. This could be the result of several complications:

  • The victim doesn’t realise their identity has been stolen and used for fraudulent payments,
  • The fraudster is using their own identity (or variation of it) to commit fraud, or
  • The fraudster is using fake details where there is no human victim.

It’s estimated that up to a 20% of all bad debt’s actually some type of fraud and up to 50% of bad debt where zero payments have been made for goods or services. Businesses should always monitor and follow-up on defaulted payments to help identify cases of hidden fraud. This is more prevalent than most businesses would think is possible.

The reality’s that businesses have the tools to differentiate bad debt and hidden fraud. It’s about taking a closer look at historical cases of bad debt and acknowledging the extent of your fraud risk based on the type of business you run. Data analytics tools are a critical cybersecurity measure that deliver actionable insights and fraud prevention techniques to help business owners separate bad debt from undetected fraud.

What can data analytics do to help?

There are financial and digital characteristics that differentiate a person who’s a credit risk or someone with a doubtful account and fraudulent applications. The methods of analysis may vary, but digital systems allow fraud teams to easily search entire databases, categorise, normalise and compare historical data and automatically run diagnostic tests and analyses.

The information provided by these various techniques will help to improve your business’s predictive capabilities and prevent fraud before it happens. You can use analytic techniques to comb through the bad debt population of your business and identify which of those are hidden fraud and which are actually defaulted payments.

Businesses need to make use of the available fraud prevention tools to keep up with the growing cybersecurity risk posed by online fraudsters. The proliferation of online services, apps, payments and banking means that you and your customers are at more risk than ever before. The longer you run diagnostics and analytics on your financial data, the more easily, accurately and quickly your fraud detection tools will work.

Detecting hidden fraud in bad debt populations

Cybersecurity tools and services are becoming more common each and every day. From national fraud prevention agencies and online fraud databases to data analytics and financial management services, the tools we need to correctly identity fraud are available. Banking application fraud and telecommunications fraud are more prevalent than we realise and by misidentifying fraud as bad debt, businesses will always incur unnecessary losses that could’ve been avoided.

MarisIT are committed to protecting South Africans and their businesses from the growing threat of cyber fraud. Our range of products and services are designed to mitigate cybersecurity risks, while keeping your online presence secure. For more information, contact MarisIT today.

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