Khosrow M Hassibi

Title: Khosrow M Hassibi: Innovator in Risk Detection and Predictive Modeling

Introduction

Khosrow M Hassibi is a notable inventor based in San Diego, CA. He has made significant contributions to the field of risk detection and predictive modeling. With a total of 2 patents, his work focuses on transforming high categorical information into low categorical information to assess transaction risks effectively.

Latest Patents

Hassibi's latest patents include innovative methods for detecting and measuring risk using predictive models through content mining. These computer-implemented methods and systems process transactions to determine the risk associated with them. The technology converts high categorical information, such as text data, into low categorical information, like category or cluster IDs. This process involves analyzing merchant names, consumer data, and other relevant textual content. By employing content mining techniques, Hassibi's methods facilitate the conversion from high to low categorical information. The resulting low categorical information is then input into a statistical model, which outputs the level of risk in the transaction. His patents disclose various methods for converting high categorical information to low categorical clusters and utilizing such information effectively.

Career Highlights

Khosrow M Hassibi is currently associated with Fair Isaac Corporation, a leader in analytics and decision management technology. His work at the company emphasizes the importance of predictive modeling in financial transactions and risk assessment.

Collaborations

Hassibi has collaborated with notable colleagues, including Russell Anderson and Larry Peranich, contributing to advancements in their respective fields.

Conclusion

Khosrow M Hassibi's innovative work in risk detection and predictive modeling has made a significant impact on the industry. His patents reflect a deep understanding of content mining and its applications in transaction risk assessment.