Our technical papers
The evolution of forecasting techniques: Traditional versus machine learning methods
Machine learning methods have been proposed in academic literature as an alternative statistical means for forecasting operations. This technical paper examines the differences in their relative performance regarding accuracy, functionality, and computational requirements.
COVID-19: Impact and recommendations for credit risk management
In this piece, we outline the challenges that the banking and financial services industries are experiencing as a result of the COVID-19 pandemic. And we explore how data and analytics can help companies effectively identify, manage, and mitigate credit risk as we move forward.
Using artificial intelligence to sell mutual funds
Finance is in the midst of a technological revolution. To overcome inefficient prospect qualification, inconsistent sales processes, and forecasting challenges, data-driven decisions are a must. Discover how artificial intelligence (AI) is helping capital markets create more efficient and effective processes.
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Augmented intelligence in life sciences
Enterprises realize the greatest benefits of machine intelligence when it's used to amplify human intelligence. In the pharmaceutical and life sciences industry, data is an increasingly valuable resource - see how augmented intelligence is helping businesses make the most it.
Machine learning epidemiological models for COVID-19
Epidemiological models are often used to forecast the growth of infectious diseases, but they have some limitations. Our COVID-19 forecasting model can help hospitals manage resources more effectively, help businesses prepare for a new normal, and protect employees.