Innovating Business Processes: Machine Learning at Oklahoma State University
On July 2, 2025, Oklahoma State University (OSU) unveiled an exciting collaboration aimed at revolutionizing business processes through cutting-edge machine learning and data analytics. Led by researchers from the College of Engineering, Architecture and Technology, particularly within the School of Industrial Engineering and Management, this initiative seeks to transform the way Jewelers Mutual operates by enhancing their business credit scoring methods.
The Collaborative Effort
This project is a partnership with the University of Wisconsin-Madison, focusing on ways to leverage machine learning to foster better results for Jewelers Mutual, a company renowned for its specialized insurance services in the jewelry industry. OSU’s primary role involves developing a custom business credit score model, a significant addition to Jewelers Mutual’s essential resources.
A Data-Driven Approach to Risk Management
At the heart of this collaboration is a commitment to loss prevention. The researchers are meticulously analyzing historical data related to crime-related losses, examining safety measures, and scrutinizing store locations to identify patterns and risk factors. This comprehensive analysis will enhance Jewelers Mutual’s underwriting process, allowing for more informed decisions that ensure better customer protection.
Meet Dr. Akash Deep
Central to this research endeavor is Dr. Akash Deep, an assistant professor in the Industrial Engineering and Management department. With five years invested in this collaboration, Dr. Deep has cultivated a deep understanding of the intersection between academia and industry. Having commenced this partnership during his Ph.D. studies, he embodies the essence of bridging theoretical insights with practical applications.
Dr. Akash Deep.
Project Goals and Methodology
The project focuses on three primary goals. First, researchers aim to identify opportunities for improvement in Jewelers Mutual’s current processes. Second, they will apply data science and machine learning techniques, which include analyzing relevant datasets and constructing predictive models. Lastly, the findings will be shared with Jewelers Mutual, empowering the company to adopt necessary innovations.
Dr. Deep emphasizes the collaborative nature of the initiative: “Typically, we can claim to be the experts in data science, but of course, the company is the expert on their business," he explains. This partnership is rooted in treating data responsibly to optimize operations effectively, utilizing descriptive analytics as a foundational step.
Predictive Modeling for Enhanced Decision-Making
The ultimate ambition of Dr. Deep and his team is to develop models that predict outcomes such as potential losses, a game-changer for Jewelers Mutual. They envision a future where their research not only contributes academic knowledge but directly influences business practices.
Dr. Deep expressed gratitude for the opportunity to collaborate with Jewelers Mutual: “I’m pretty lucky to be able to collaborate with Jewelers Mutual,” he states. The fusion of theoretical techniques with practical business needs highlights the real-world impact of their work.
A Synergistic Experience
Working closely with industry experts and talented students, Dr. Deep has found the collaboration to be a fulfilling endeavor. He reflects on the experience, noting, “It is a fantastic project to work on to really see how we can help.” The synergy between academia and industry has not only enriched the research but has also provided practical solutions that are beneficial to all parties involved.
Machine learning and data analytics hold the promise of redefining industries, and this initiative at Oklahoma State University is a testament to the transformative power of collaboration, innovation, and research in generating real-world solutions.