SAS Regional Solution Director, Fraud & Security Gerard McDonnell says as digital technology becomes easier to use, fraud is also shifting drastically from counterfeit card capabilities towards harder-to-identify schemes.
By Gerard McDonnell
Digital fraud covers a wide range of illegal actions that are committed in cyberspace and has now become a serious cause of concern. As digital convergence continues to transform the marketplace, the new-age consumer is spending more time on “virtual platforms” and prefers digital conversations. These trends have accelerated in the past nine months as the pandemic has changed how consumers interact with financial services and commerce.
Amid coronavirus-driven lockdowns and social distancing, proliferating mobile apps and online channels have proven vital lifelines. Online shopping and contactless payments have propelled record e-commerce sales. This may have been a blessing during the crisis but there has also been an increased frequency of fraud attempts.
The coronavirus has not changed how fraud is committed, but it has shone a bright light on the risks of fraud in the digital age. It has also forced the massive un-banked population in ASEAN to use cashless payment methods and digital banking products more than ever before. This is a new experience for users and a new opportunity for the banks, but it brings with it new challenges. The new customer base has taken readily to a cashless and seamless experience, but is vulnerable and prone to phishing scams, identity theft, third party account takeovers and more.
Businesses have evolved digitally and must live up to consumer expectations, including digital payment capabilities. All businesses on digital platforms store consumer data – however, the question remains, how secure is this data? The answer is that it is typically not fully secured, and hackers are constantly finding innovative ways to access it.
As digital technology becomes easier to use, fraud is also shifting drastically from counterfeit card capabilities toward harder-to-identify schemes involving social engineering, cyber intrusions, and account takeovers.
Digital fraud has become strategic and innovative, changing the operating environment globally and threatening financial institutions with damage to their reputations as well as financial losses. Criminals are continually developing multiple strategies to identify and exploit systemic weaknesses and vulnerabilities, hacking into accounts by obtaining valuable customer information and login credentials.
If enterprises and financial institutions do not find a way to prevent fraud, there is a real risk of losing credibility and thus consumer trust and associated business. Such risks will also discourage companies from fully leveraging the amplified reach of digital platforms. On the other hand, investments in digital security will become a market differentiator, creating business value for companies that take a proactive stance.
Mitigating risk and protecting clients from exposure
The move from omnichannels to multichannel, combined with the sophisticated nature of tools that criminals have available to them, provides a road map for financial institutions to build their fraud mitigation strategy over the coming years. Without technological and operational improvements, the global rise of digital fraud will surpass the losses associated with counterfeiting magnetic stripe payment cards.
A new fraud report by Javelin Strategy & Research and SAS suggests this digital shift is also fueling a multi-billion-dollar fraud surge worldwide;
Digital payments present an escalating global risk.
Digital fraud is increasing in frequency and sophistication.
Financial services organisations need layered technology and analytic capabilities to identify overlapping threats in real time.
Data is critical in the fight to combat digital fraud.
Organisations need to manage risks during the movement from traditional payment methods to the new digital options. Data and advanced analytics can be highly beneficial in overcoming digital fraud and financial crime. The critical first steps are to start processing all data streams in real time and to combine identity management and transaction monitoring to not only identify fraud that has occurred, but to stop it even before it takes place.
The financial services industry as a whole needs to better utilise available artificial intelligence and machine learning technologies. Since the start of the pandemic, financial institutions have tirelessly innovated to meet customers’ need for flexibility and immediacy. Now, they must redefine how they protect themselves and their customers from the associated risks.
An end-to-end fraud detection and prevention solution that supports multiple channels and lines of business will enable enterprise-wide monitoring from a single platform. This will simplify data integration, enabling financial institutions to combine all internal, external and third-party data to create a better predictive model tuned to the organisation’s needs. Bringing together this data on a single technology platform gives the flexibility to scale up or out as the business changes, and respond faster to new threats as they arise.
Finding fraud faster reduces revenue loss by staying on top of shifting tactics and new fraud schemes. Embedded machine learning methods detect and adapt to changing behaviour patterns, resulting in more effective, robust models.
Businesses need more than just the standard analytics to handle fraud. Adaptive techniques such as machine learning are essential. Various practices can be implemented such as supervised or unsupervised machine learning, network analysis and text analysis. All of these form a powerful force for improving both the accuracy and efficiency of fraud detection. It only makes sense to bring fraud, Anti Money Laundering (AML) and cyber functions together.
What to do about it
Converge fraud and AML programmes. Centralise insights from multiple sources, including cyber event data, for more complete customer risk assessments in a broader context.
Establish consistent business processes. Intuitive workflow and case management support more efficient investigations, faster resolutions, fewer false positives and higher productivity.
Reduce false positives with advanced analytics and machine learning so investigative analysts can focus on the cases that pose the most risk to the organisation.
Intelligently prioritise alerts for triage, investigation and disposition. Quickly see areas of interest and where to focus first.
Conduct more efficient, targeted investigations through interactive visualisations. Import, search, filter and visualise the results in different ways to reveal patterns, people and events hidden in complex data.
Data without analytics is value not realised, which means businesses are unable to operate at their optimum capacity. Thus, it is imperative for organisations to understand the value and significance of data analytics to thrive in competitive markets.
(Ed. Featured image by Photographer Ryutaro Tsukata.)