Application of Machine Learning Algorithms to Credit Scoring

Pedro Fonseca, CEO & Head of Data Science @ James by CrowdProcess participates in Risk Roundup to discuss “Application of Machine Learning Algorithms to Credit Scoring”.   Overview Is human intelligence still the most meaningful form of intelligence that can be effective in managing complex industry risks? As the digital global age grow in scale and complexity, there is an increasing concern that manual business practices, that are driven largely by human intelligence, are no longer sufficient to effectively perform complex industry tasks on its own, in a timely and cost-effective manner; nor are they effective in managing complex interconnected and interdependent industry risks. There are numerous reports emerging from across nations that machine learning has convincingly penetrated complex business processes across many industries. From credit lending to credit scoring, and robot control to remote sensing, thousands of machine learning applications have already been getting deeply embedded across complex business processes. These are just some examples and it is just the beginning. As we take a step forward in our digital global age journey, entities across nations: its government, industries, organizations and academia (NGIOA) will surely need to go beyond basic tasks and processes like computing data and collecting metrics to developing more intelligent algorithms to strengthen some of the most important interconnected and interdependent operational, tactical and strategic technologies, processes and initiatives. Independently and collectively, this will likely impact and change not only technology and processes; but also, business, management and governance models. Intelligent machines are here; and the question is whether, we the individuals and entities across NGIOA are prepared for what is to come… So, what does all this mean? It means that, if the decision makers across NGIOA are not thinking about Machine learning, Deep Learning and Intelligent Machines now, then they run the risk of their initiatives, products, services and businesses being undoubtedly disrupted in the coming years. Time is now to talk about Risks! For more please watch the Risk Roundup Webcast or hear Risk Roundup Podcast About the Guest Pedro Fonseca, is the CEO & Head of Data Science @ James by CrowdProcess. He is currently working on James, CrowdProcess’ flagship product in the Financial Industry, for the credit risk space. (http://www.james.finance/). CrowdProcess is a data science company, in the credit risk space. It has recently been considered the Best European Fintech at the prestigious Money2020 conference, for its risk product: James. The company’s flagship product, James, is a software for risk departments to build in-house scoring models using machine learning. James combines advanced scientific computing and machine learning algorithms with a business-friendly interface, specifically designed for the risk officers of mid-tier banks and credit institutions. It allows risk officers to build, test and validate credit scoring models, and comes equipped with the best Machine Learning algorithms, techniques and validation methods. About the Host of Risk Roundup Jayshree Pandya (née Bhatt) is a visionary leader, who is working passionately with imagination, insight and boldness to achieve “Global Peace through Risk Management”. It is her strong belief that collaboration between and across nations: its government, industries, organizations and academia (NGIOA) will be mutually beneficial to all—for not only in the identification and understanding of critical risks facing one nation, but also for managing the interconnected and interdependent risks facing all nations. She calls on nations to build a shared sense of...