Meet Aidrian, a cloud-based fraud solution powered by adaptive machine learning (ML).
Unveiled by Experian South Africa during its annual flagship conference in Johannesburg last week, Aidrian is designed to prevent fraud without compromising the customer experience. Aidrian’s ML model continuously learns and adapts, with regular retraining using new data. This ongoing improvement enhances its ability to prevent fraud, while ensuring a seamless experience for genuine customers during checkout or onboarding.
“This powerful modular transactional fraud solution combines a state-of-the-art customised ML model with device fingerprinting to automatically classify transactions with 99.9% accuracy,” said Mark Wells, chief customer officer at Experian Africa. “Aidrian’s ability to differentiate between legitimate customers and fraudsters can significantly reduce false positives, helping to generate up to 15% more revenue for clients.
“With annual fraud losses sharply increasing, the use of ML is fast becoming essential to combat fraud. By adopting the latest technology, businesses can considerably reduce the volume of manual reviews, ease pressure on fraud teams and improve their customer experience.”
The Experian conference brought together industry experts and professionals to exchange insights and discuss trends shaping the business and consumer landscape. The summit took place against the backdrop of a challenging macro-economic environment, emphasising the significance of businesses enhancing their data insights, analytics, technology, and innovation to foster growth and resilience.
Wells highlighted the growing importance of data-driven customer insights.
“With the array of choice available for today’s consumer, organisations are investing more in data driven customer insights to create relevant products and services that can be better targeted at the right customers. For credit lenders, the affordability decisions made at acquisition are critical to delivering growth. With the advent of AI and ML, those decisions around who to extend credit to, can now become a lot smarter.”
AI and ML are not new wonders, but the application of advanced analytics is reaching new spaces and opening radical changes to processes that have remained largely unchanged for years. AI enables unprecedented analysis that will become essential to ensure precise decision making within risk management and fraud. Moreover, it enables greater operational efficiency through automation which ultimately improves the end customer experience.
Francois Grobler, chief of Decision Analytics, said: “We see that several winning organisations are using a wide variety of data sources and ML to improve the accuracy of their risk models. These two factors are key to creating resilience in the face of rapidly changing conditions.
“Machine learning can help businesses take advantage of the vast quantity of available data that grows exponentially each day. It allows businesses the flexibility to integrate new data sources quickly and understand the implications of this data in real-time. This in turn enables greater insight, agility, and adaptability in responding to rapidly changing macroeconomic conditions, market and customer risk and fraud threats.”
The ability to implement and deliver new models, rules and strategies at speed can be a competitive advantage with business improvements realised quicker. However, businesses are realising that cloud-based software is a key organisational enabler to accelerate their AI and ML programmes.
Additionally, with an increasingly competitive and cost sensitive market, businesses are under pressure to accelerate the customer onboarding process to drive revenue growth whilst reducing technology costs in support of a stronger profitability focus. At the same time, they need to carefully manage risk, ensure responsible lending, and provide customers with a personalised and affordable product.
“This isn’t possible without advanced software processing the data, making quick decisions, and coming back to the consumer with a decision in minutes. To do this, businesses need an automated way to understand each applicants’ risk profile and onboard the right customers quickly whilst using data and analytics to improve the accuracy of decisions, reduce manual effort and lower cost.”
The challenge of combating fraud in an increasingly digital world was acknowledged. Attacks are evolving and becoming more sophisticated, necessitating additional fraud prevention tools.
AI and ML were identified as crucial in managing data, credit risk models, and fraud risk decision-making. These technologies enable organisations to create, test, and deploy new models much faster than before, making them more effective in mitigating fraud threats.