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Technology to survive and thrive in a world of growing threats

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The outbreak of the Covid-19 pandemic has created a breeding ground for an increase in fraudulent activity, as the world shifted to working from home and reliance on digital technology was heightened in all aspects of daily life. This underscored the need for tighter procedures and processes around detection and protection within all sectors, but especially financial services.

The outbreak of the Covid-19 pandemic has created a breeding ground for an increase in fraudulent activity, as the world shifted to working from home and reliance on digital technology was heightened in all aspects of daily life. This underscored the need for tighter procedures and processes around detection and protection within all sectors, but especially financial services.

“Our collective reliance on phones has a number of implications for fraud, and in 2022 I predict that fraudsters will be so dialed in to our mobile lifestyles they will ply their trade in more ways and places than ever—including space,” writes TJ Horan, vice president of product management for FICO[1]. He goes on to outline how pre-pandemic appetite for spending in addition to post-pandemic levels of hurried, distracted phone use and unlimited access to satellite internet connectivity leads to new opportunities for fraudsters of celestial proportions. 

Specifically, phishing is becoming even more sophisticated, with Remote Access Trojans and automation being used to improve scale and reach of such scams. “Phishing has become a significant problem in the corporate arena too: CEO fraud, Business E-mail Compromise (BEC), and invoice redirection scams are rife. The latter is costing businesses upwards of GBP 92 million a year in the UK alone,” highlights Andreas Eliasson, commercial director, Callsign[2]. 

Account takeover fraud continues to be of significant concern while growing appetite for cryptocurrencies has left the space even more susceptible to bad actors. 

Eliasson warns how “many businesses are still relying on outdated and insecure authentication and online fraud prevention technologies. An over-reliance on static authentication such as passwords and SMS OTPs is endemic across every sector – not only are these simple to bypass, but it also means that organisations are authenticating in the very same channel where the phishers are casting their nets.” 

And as technology advances, these concerns are only bound to become more pressing. 

In its 2022 fraud outlook[3], KPMG found that fraud, compliance concerns and cyber attacks are common, have increased in severity, and are expected to become more frequent. 

“Increasingly, companies need to mitigate what KPMG calls the ‘threat loop’, which comprises the triple threat of fraud, compliance risk and a growing array of cyber security threats. Defending against this threat loop requires a collective, interconnected effort. Companies need to look at the impact created by these threats in conjunction, rather than just the risks they pose in isolation,” the consultancy outlines. 

AI elevates fraud detection 

Fraud detection is one of the ways companies can tighten their business to avoid attacks of a transactional nature. “Customer fraud, cyber-attacks and asset misappropriation can be detected using fraud detection technologies that leverage advanced analytics. Yet, according to PwC’s 2020 Global Economic Crime and Fraud Survey, only a quarter of respondents (25%) are using artificial intelligence (AI) — a technology that is ever more prevalent today. It is a staggering statistic when you consider the magnitude of the fraud threat every organisation faces,” the consultancy details. 

Mastercard is one of the leading companies employing AI systems to fight back against credit card fraud. 

“By using sophisticated technologies and massive amounts of data, the payment processing industry is fighting back against credit card fraud in innovative ways,” details a white paper published by Dell Technologies.[4] 

As a key example, Mastercard leverages machine-learning algorithms running on HPC systems to process large data sets at lightning-fast speeds in its efforts to identify and stop fraudulent transactions. The goal is to stop fraud in its tracks without disrupting or delaying legitimate transactions[5]. 

The incorporation of artificial intelligence (AI) and machine learning into fraud detection systems sees these new technologies both improving fraud detection while cutting the false decline rate in half. 

“The power of AI lies in its ability to self-learn, which brings flexibility and greater accuracy into traditional rule-based fraud detection systems. This allows for the personalization of fraud detection,” notes Karthik Ramanathan[6], Senior Vice President, Cyber & Intelligence Solutions, Asia Pacific, Mastercard, “AI systems mine historic and real-time data from a wider array of touchpoints and identify patterns so that fraud detection systems are able to create consumer profiles based on a segment of one. This means that AI-developed algorithms can more accurately assess changes in an individual’s spending patterns.” 

Mastercard has also created an anti-fraud solution called MATCH (Mastercard Alert to Control High-risk Merchants)[7]. The MATCH database maintains data on hundreds of millions of fraudulent businesses. Mastercard acquirers submit nearly one million inquiries to the database each month. They can search the database for each potential merchant or send Mastercard a bulk file of merchant names to perform a batch search on their behalf. 

The capabilities of this database were further enhanced through the adoption of Cloudera Enterprise and Cloudera Search. The data hub allowed Mastercard to add new tools to access, search, and secure more data than ever. 

Cloudera, in turn, also boosted its ability through a collaboration with NVIDIA computing. Joe Ansaldi, IRS/Research Applied Analytics & Statistics Division (RAAS)/Technical Branch Chief, Cloudera comments in a press release[8]: “The Cloudera and NVIDIA integration will empower us to use data-driven insights to power mission-critical use cases such as fraud detection. We are currently implementing this integration and are already seeing over three times speed improvements for our data engineering and data science workflows.” 

Protect yourself 

“The unprecedented pandemic shocked the global financial system and accelerated digital transformation, which brings stronger motives, more insidious forms, and more intelligent schemes of financial fraud activities,” write Xiaoqian Zhu, Xiang Ao, Zidi Qin, Yanpeng Chang, Yang Liu, Qing He and Jianping Li in a paper entitled Intelligent financial fraud detection practices in post-pandemic era[9]. 

“AI can help banking firms better detect and prevent payment fraud and improve processes for anti-money laundering (AML) and know-your-customer (KYC) systems. With NVIDIA GPU-accelerated machine learning and deep learning platforms, data scientists can deliver results in days, instead of the weeks more traditional methods require,” details Kevin Levitt who leads global industry business development for financial services at NVIDIA, in a technical blog. 

Further, in a report called Transforming the Business of Finance[10], Dell Technologies outlines practical ways in which firms can enhance their fraud detection and protection to survive and thrive in a world where new threats are continuously coming to the fore. 

Firms should unify their security programs with overall business risk and implement advanced security operations which adapt to the shifting threat landscape. Building a resilient, modern infrastructure to protect endpoints, networks, applications and data is also key. Finally, working with trusted, expert partners is a critical element which brings all these aspects together. “Rely on trusted advisory services to help you design and implement your security transformation program,” Dell advises.

This article is in partnership with Dell Technologies & NVIDIA.





[5] Interview with theCUBE conducted at Dell Technologies World 2017. 






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