Boosting Fraud Detection
Mastercard
Mastercard’s new generative AI model, Decision Intelligence Pro, can help financial institutions improve their fraud detection rates by as much as 300%. The proprietary model is trained on data from the roughly 125 billion transactions that pass through Mastercard’s network annually. Instead of focusing on textual inputs, Decision Intelligence Pro uses historical data to improve fraud detection rates by analyzing merchant relationships and predicting fraudulent transactions. The technology operates in real time and can potentially save financial institutions significant costs by eliminating much of the resources they’d typically devote to assessing illegitimate transactions.
Using AI to Keep Data Safe & Prevent Attacks
IBM
Cyberattacks in the U.S. were up 57 percent in 2022 and will cost the global economy an estimated $10.5 trillion by 2025. As the value of data increases, AI is keeping data safe and preventing attacks before they happen. IBM is using AI to produce incident summaries for high-fidelity alerts and automate incident responses, accelerating alert investigations and triage by an average of 55 percent. IBM’s AI technology also helps identify vulnerabilities and defend against cybercriminals and cyber crime.
Enhancing Cyber Threat Detection
IBM Watson
IBM’s AI platform Watson will soon be used to provide cybersecurity analysts a major edge in fighting cyberattacks by enhancing the human capability to parse vast amounts of security-related information quickly. Collecting and analyzing security data using traditional methods is expensive and time consuming. According to a recent IBM report, the average organization sees over 200,000 pieces of security event data every single day, leading to the wastage of over 20,000 hours per year due to the chase of false positives. With the proliferation of networked devices in the expanding IoT ecosystem, the volume of data will only continue to grow.
Watson is uniquely positioned to handle both the volume of information and discern the crucial context that determines what sort of threats exist. While a human security researcher might not have a firm command of all the tens of thousands of known software vulnerabilities, Watson can. Analysts will also be able to use Watson to help scour unstructured data and seek out anomalies and indicators that might correlate suspicious activity to other factors in the cyber domain.
Enhancing Fraud Prevention
NetApp
Rules-based expert systems currently used to catch financial fraud have become too easy to beat, resulting in billions of dollars in losses each year. In addition to trying to combat fraud, financial services institutions are also challenged to make the right credit decisions, improve risk management, enable fast, insightful trading, and develop personalized services — all while improving the customer experience.
NetApp has developed AI solutions that remove data silos and provide deep insights that financial institutions can use to improve their defenses and better serve their customers. NetApp uses AI and machine learning to provide real-time, market-ready analytics and risk mitigation to reduce threats, eliminate fraud, and protect customer endpoints. With AI, NetApp is providing financial institutions the performance they need to feed, train, and operate their applications so they can quickly and accurately detect illegal or suspicious financial activity across all areas of their organizations.