Unleashing Computational Speed: Enhancing Risk Models for Compliance in a Global Financial Powerhouse
The following steps were undertaken as part of the solution:
Updating the Risk Model: Quansight migrated the risk model from its existing framework to Python, taking advantage of Python’s extensive ecosystem and powerful libraries such as NumPy and Numba. This transition facilitated more efficient data manipulation, analysis, and numerical computations.
Leveraging Fast Numerical Libraries: Quansight incorporated NumPy and Numba, which are widely recognized for their optimized numerical operations and just-in-time compilation capabilities. These libraries enabled the risk models to execute computations at significantly higher speeds.
High-Performance Deployment: Quansight’s Open Source Architects deployed the updated risk model on computation clusters using PySpark. By leveraging the distributed computing capabilities of PySpark, the risk model achieved high-performance scalability, enabling faster processing and analysis of vast amounts of data.
Outcome
The implementation of Quansight’s solution led to remarkable improvements in the computational speed and efficiency of the risk models, resulting in the following outcomes:
Over 100X Improvement in Computational Speed: The updated risk models, powered by Python and optimized numerical libraries, reduced the computation time from one week to a fraction of the original time. This significant improvement allowed the financial institution to meet regulatory requirements within the specified deadlines.
Compliance Achievement: By accelerating the risk models, the client successfully met compliance obligations for current expected credit losses (CCEL) and comprehensive capital analysis and review (CCAR). The institution was now able to submit reports and assessments within the required timeframes, avoiding penalties and maintaining regulatory compliance.
Adoption of Tools and Techniques: The tools and techniques introduced by Quansight, including Python, NumPy, Numba, and PySpark, were widely embraced within the financial institution. The success of the project encouraged the institution to explore further opportunities for utilizing open source technologies and collaborating with OpenTeams partners.
Conclusion
Through the collaboration between Quansight, an OpenTeams Partner, and the top five financial institution, the challenges related to sluggish risk models were effectively resolved. The utilization of Python, along with optimized numerical libraries, and the deployment on computation clusters using PySpark, led to a remarkable improvement in computational speed. The successful outcome enabled the institution to meet regulatory compliance requirements and fostered the adoption of open source tools and techniques within the organization.
About OpenTeams
OpenTeams is a premier provider of open source solutions for businesses worldwide. Our goal is to help organizations optimize their open source technologies through tailored support solutions that meet their unique needs. With over 680+ open source technologies supported, we provide unparalleled expertise and resources to help businesses achieve their goals. Our flexible support plans allow organizations to pay for only what they need, and our team of experienced Open Source Architects is available 24/7/365 to provide top-notch support and guidance. We are committed to fostering a community of innovation and collaboration, and our partner program offers additional opportunities for growth and success.
About Quansight
Quansight is a renowned company that specializes in machine learning, data science, and open-source technologies. With their deep expertise in these domains, Quansight offers comprehensive solutions and services to organizations seeking to leverage the power of data and AI. They are known for their proficiency in developing customized machine learning models, optimizing algorithms, and implementing cutting-edge technologies to solve complex business challenges. Quansight’s team of experts possesses a deep understanding of open-source frameworks and tools, enabling them to deliver innovative solutions that are scalable, cost-effective, and aligned with the unique requirements of their clients. Their commitment to excellence and their ability to leverage open-source technologies make Quansight a trusted partner for organizations looking to unlock the full potential of their data.
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