AI will do many things better than humans currently do. But the universe of unsolved problems is so vast, and the cost of attacking them is dropping so fast, that the constraint will not be “what is there left to do?” It will be “who has the initiative to go do it?”
Reducing regulatory burden may feel like progress. But as we move toward lighter oversight, let’s not forget what those rules were designed to prevent.
Timing, resources, and budget are often the driving factors in deciding who will perform the validation of key risk models, yet the most important aspects are frequently overlooked.
XGBoost is a popular supervised machine learning algorithm and may be the new wave of modeling credit risk. Here are the basics of the mechanics behind the algorithm.
DCG’s primary objective for conference attendees is to walk away with “one key idea” for their institution. Sessions underscored a shared commitment to transforming unpredictability into opportunity through data-driven strategies. Here are the highlights from this year’s conference.