Francisco Hawas is a PhD candidate in Applied Mathematics and Statistics at Stony Brook University in New York. His research focuses on lifelong machine learning applications in finance. Further, he is a Senior Analyst in the Quantitative Modeling team at Kroll Bond Rating Agency. Prior to his current position, he worked as a Quantitative Analyst for Vision Advisors and ING in Chile. He holds a Master in Applied Mathematics and Statistics from Stony Brook University and a Master in Applied Economics and a Bachelor of Science in Engineering degree from the Universidad de Chile.
The authors introduce a simple numerical algorithm to study banking systems subject to credit risk. The algorithm is based on a model that is completely defined by only two parameters.