Automation: The Key to Advanced Fraud Detection

The convergence of artificial intelligence and machine learning with automation will unlock unprecedented intelligence and help fight evolving fraud

Automation for advanced fraud protection

Innovations in the financial sector have provided customers with a number of payment channels—online banking, credit cards, e-wallets, and P2P transfers. This has led to an exponential increase in the number of digital transactions. While it has become convenient for customers to choose a suitable payment option, the risk to their identity and payment data has also increased. Cybercriminals are accessing this personally identifiable customer data to impersonate genuine customers and orchestrate various financial crimes. As a result, digital businesses are finding it challenging to distinguish between genuine customers and fraudsters, which is impacting their business growth and brand.

Traditional Approach Slows Down Business Growth

Many businesses still resort to reviewing transactions using legacy solutions. Rule-based linear models are not only time-consuming, but can also lead to high false positives in an over-zealous bid to prevent fraud. This traditional approach of authenticating customers makes the review process slow and can lead to customer impatience or in worst cases, customer churn. Financial institutions and digital businesses today do not have the luxury of time and must authenticate transactions in a matter of milliseconds. Therefore, time-sensitive decisions need real-time actionable insights.

Need for Real-time Fraud Prevention

Automating the review process with technologies such as artificial intelligence and machine learning can effectively resolve the challenges that digital businesses face today and can help in improving operational efficiency, preventing fraud in real time, and gain a competitive advantage.

Increase Operational Efficiency: Artificial intelligence and machine learning complete with an automated review process, can enable businesses to accurately distinguish genuine customers from fraudsters in real time and at scale. These technologies help aggregate and analyze data—structured and unstructured—from disparate sources to glean actionable insights and aid rapid decision-making, thereby enhancing overall operational efficiency. Large volumes of data make machine learning even more incisive as algorithms can iterate over large sets of data to unravel hidden patterns and accurately detect anomalous behaviors.

Fight Evolving Fraud: Since fraud is becoming more complex and sophisticated, fraud solutions must also evolve. Businesses can fortify their defenses against fraud only with technology-driven smart solutions that can learn and respond quickly. Given the results that AI and ML have achieved in fighting fraud, their automation will further revolutionize fraud prevention. Automated solutions powered by AI and ML provide businesses with intelligent and powerful tools that have enormous potential to prevent fraud.

Gain Competitive Advantage: At present, only a fraction of processes—mainly repetitive or process-driven tasks—are automated. But, going forward, automation will extend to a wider set of processes that will help unlock unprecedented intelligence. Automation will further enable machines to correlate trends across a larger spectrum of data streams—including raw data—and power advanced fraud prevention tools that can identify evolving fraud patterns and present real-time feedback, thus providing businesses with a competitive advantage.

Automated Decisioning, Powered by Simility

Simility, a PayPal service, uses the power of AI and ML in its cutting-edge automated decisioning solution, the Adaptive Decisioning Platform, to help businesses win the fight against fraud. The Simility solution is powered with advanced features to enable automation. These features empower the Adaptive Decisioning Platform to analyze historical performance of the existing rules and automatically suggest improvements according to evolving conditions so that the rules become smarter and more incisive. In addition, the platform automatically evaluates changes to a rule to generate performance metrics enabling businesses to take immediate corrective action and accurately detect fraud. With numerous automated features, Simility’s Adaptive Decisioning Platform can analyze enormous amounts of data from disparate sources to provide real-time insights. It can intelligently learn from the feedback and evolve with the changing threat landscape, making it truly future-ready.

To learn how to leverage the power of automated artificial intelligence and machine learning with Simility’s Adaptive Decisioning Platform, schedule a demo now.

Rahul Pangam

Rahul Pangam

Rahul is the Co-Founder and CEO of Simility. Being a fraud detection industry veteran, he believes in combining the power of algorithms to recognize similar and dissimilar signals with the ability for humans to create meaning and giving front-line fraud fighters tools that empower them to put their domain expertise and knowledge to use without needing to write code.
Rahul Pangam