Online fraud presents a pervasive problem for
businesses of nearly every shape and size. According to a
PricewaterhouseCoopers (PwC) survey, 47 percent of the
5,000 companies quizzed experienced a fraud in the past
24 months, with a total fraud loss reported of $42 billion.¹
And, unfortunately, the problem is growing. A 2020
survey conducted by the Association of Certified Fraud
Examiners (ACFE) found that, at a worldwide level, 77
percent of respondents reported a significant increase
in cyberfraud risk, and 92 percent expected a significant
increase in the next 12 months.²
Industries like retail, delivery, media, travel and
hospitality, gaming, and financial services are the most
often targeted by fraudsters. But any organization that
conducts business online can fall victim to online fraud—
and must seriously consider the risks and impacts.
Companies typically use fraud detection applications that
often rely on business rules that don't keep up with the
changing behaviors of fraudsters. Rule-based systems
also require more human intervention and depend
on experts to update the detection logic. If the fraud
detection solution is not accurate enough, it will lead to
false negatives, which will result in higher fraud losses
and false positives, which will lead to lower revenue,
negative reviews, and customer churn.
Thankfully, advancements in technologies like machine
learning (ML) are enabling organizations to identify
potentially fraudulent online activities with greater ease.
Machine learning is well suited for the fight against fraud
because it:
• Addresses a problem that's rich in data and can
benefit from pattern identification within datasets
• Can achieve results that are nearly impossible to
accomplish through human input alone
• Produces results that are easily quantifiable in
financial terms, helping to foster executive buy-in for
larger machine learning investments
By leveraging machine learning to combat online
fraud, organizations can avoid revenue loss, mitigate
brand damage, and create frictionless online customer
experiences. The journey toward these benefits can
begin in several ways—so organizations should start by
considering the options and determining which path is
best for them.
Making inroads against online fraud
2 "Fraud in the Wake of Covid-19: Benchmarking Report." Association of Certified Fraud Examiners, September 2020.
1 "PwC's Global Economic Crime and Fraud Survey 2020." PricewaterhouseCoopers, 2020.
3
