Recent research highlights that more than 52% of fraud now happens over digital channels, surpassing conventional fraud for the first time, with South African businesses reporting a 49% increase in the 12 months preceding the survey. These fraudulent activities cost South African businesses nearly four times (3.64x) the lost amount to report, investigate, recover, and restore lost funds and damaged client relationships.
Overall, 69% of consumers reported being targeted with online, email, phone call or text messaging fraud during late 2023, with the rate of suspected digital fraud attempts being the highest in the South African telecommunications sector at 15.5% – a year-over-year increase of 78%. Captured tangibly, the South African Banking Risk Information Centre revealed in late 2023 that cyber criminals stole more than R740 million from unsuspecting users through digital banking fraud during the previous year.
With cybercriminals’ tactics constantly evolving, businesses need to continuously adapt their protections and responses to prevent loss and damage, with real time transaction monitoring, transaction fraud prevention, anti-money laundering protection (AML) and counter terrorism financing (CFT) being the most important barriers. Other cybercrime prevention tools include compliance monitoring and reporting, and customer behaviour modelling.
While many cybercrime prevention tools include elements such as user analysis (authentication and device identification), navigation analysis (such as IP addresses and user identification) and channel behaviour analysis, it’s only graph intelligence that can assess behaviour across channels and analyse relationships.
According to Locstat, a South African company included in the FINCRIMETECH50 list of the world’s most innovative tech companies fighting cyber and financial crime, graph intelligence analyses the information hidden in data relationships that identifies and provides insights into patterns and trends. These insights, identified by artificial intelligence, make it possible to assess those relationships, using this rich, contextualised data to make decisions and trigger the next best actions to safeguard the business.
“Adopting innovative, AI-supported digitalisation strategies can help organisations realise considerable gains and benefits in their cybercrime prevention and mitigation strategies,” says Waldick Herbst, chief commercial officer at Locstat. “Next-generation advanced analytics technologies can solve today’s complex operational challenges more cost-effectively than traditional solutions that are driven by relational databases.”
Herbst adds that the most effective fraud prevention and detection solutions are those that can be configured for each business’ unique context, including its geography, operational, systems and data environments, with graph technology able to identify the complex relationships and patterns between data points. This is either impossible or computationally expensive if employing legacy database technology, whereas graph data modelling enables the detection of suspicious activity that may not be visible to other solutions.
“Due to their diverse range of products, services and technology, each country on the African continent presents unique challenges in data protection and fraud prevention,” he says. “Businesses and financial services providers need to be able to adapt and respond to fraud attempts on platforms as diverse as USSD, mobile banking, traditional banking, digital banking, and wallet / vending based products, among many others. This platform diversity highlights that businesses that are serious about preventing cybercrime need solutions that are configurable and that enable constant innovation across multiple platforms, gathering, analysing and understanding data to identify and prevent costly fraud. Existing, off-the-shelf capabilities, sometimes referred to as ‘canned analytics’ may no longer have the agility to counter sophisticated fraud, AML or CFT activities.”
Technology research house Gartner opines that ‘graph analysis is possibly the single most effective competitive differentiator for organisations pursuing data-driven operations and decisions, after the design of data capture’.
As one of the world leaders in using graph technology to prevent cybercrime, Locstat’s solutions can help businesses prevent not only the most common types of transaction-related fraud but also complex fraud including account takeovers, card-not-present fraud, mobile money fraud, and trade-based money laundering. They can also identify agent-banking commission fraud and chargeback fraud.
“Financial services businesses and cybercrime prevention providers ask increasingly complex questions of available data, seeking deeply contextual answers that will make a meaningful difference, quickly,” Herbst says. “We can’t expect legacy technology to find the answers needed to respond to the challenges of the present and the future, and graph database technology, integrated with high-performance computation capability and complex event processing provides vastly more effective protection for financial services businesses.”
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