2 min
Detecting Fraud Using Emerging Technology: Innovating Beyond Traditional Controls
Fraud and financial crime are evolving at a pace that challenges even the most established detection systems. From cyber-enabled schemes and complex financial misappropriations to subtle internal manipulations, traditional audit and compliance methods are often too slow or too narrow to keep up. In a world where billions of data points can hide a single irregularity, the investigative advantage now lies in speed, intelligence, and technological adaptability. J.S. Held’s Ken Feinstein recently authored an article exploring how artificial intelligence, machine learning, and advanced data analytics tools are transforming how organizations uncover and prevent fraud. In his piece, “Detecting Fraud Using Emerging Technology: Don’t Be Afraid to Innovate,” Feinstein illustrates how the integration of digital investigation techniques — from automation to predictive analytics — is reshaping the fraud-detection landscape, helping companies not just react to wrongdoing but anticipate and deter it. Ken Feinstein specializes in investigative data analytics and has over 25 years of experience. He provides data analytics solutions spanning multiple sectors, including retail and consumer products, life sciences, technology, financial services, and industrial products. His clients include law firms and Fortune 500 legal and compliance teams for whom he delivers large-scale, complex investigations, regulatory response matters, proactive anti‐fraud efforts, and compliance programs. View his profile here Why This Matters As fraudsters exploit digital tools and globalized networks, detection efforts must evolve in kind. Regulators expect faster, data-driven investigations, and boards demand real-time risk visibility. Those who innovate with AI-enabled detection and forensic analytics are better positioned to protect assets, reputation, and shareholder trust. Looking to know more? Connect with Ken Feinstein today by clicking on his icon below.
