Sunil J Mathew

Title: Sunil J Mathew: Innovator in Machine Learning and Fraud Detection

Introduction

Sunil J Mathew is a notable inventor based in Brooklyn, NY, recognized for his contributions to machine learning and fraud detection technologies. With a total of two patents to his name, Mathew has made significant strides in developing systems that enhance the accuracy of fraud detection through innovative methodologies.

Latest Patents

Mathew's latest patents focus on below-the-line thresholds tuning using machine learning. The first patent describes systems and methods for ML-based automated below-the-line threshold tuning. This invention involves training a machine learning model to predict the probabilities of events being fraudulent based on historical data. The model helps in adjusting the threshold line that indicates suspicious events, thereby improving the alerting engine's accuracy. The second patent also revolves around below-the-line threshold tuning, detailing a method that includes selecting and labeling sampled events as suspicious or not. A machine learning model is built to calculate the probability of an event being suspicious, which is then used to generate a tuned threshold value that reduces classification errors in the alerting engine.

Career Highlights

Sunil J Mathew is currently employed at Oracle Financial Services Software Limited, where he applies his expertise in machine learning to develop advanced fraud detection systems. His work has been instrumental in enhancing the capabilities of financial services through innovative technology solutions.

Collaborations

Mathew collaborates with Jian Cai, a fellow innovator, to further advance their research and development efforts in the field of machine learning and fraud detection.

Conclusion

Sunil J Mathew's contributions to machine learning and fraud detection exemplify the impact of innovative thinking in technology. His patents reflect a commitment to improving the accuracy of fraud detection systems, making significant advancements in the financial services industry.