The banking industry has undergone significant changes that have fundamentally altered the competitive battlefield. With a focus on improving efficiencies, finding new revenue opportunities and improving the customer experience, five megatrends have arisen to impact banking in tectonic ways. They all are components of the digital banking transformation process – some being revolutionary while others are evolutions of trends already in process. In this webinar from MeridianLink, you'll learn how to deliver a world-class, omnichannel digital banking experience that's fast, responsive and frictionless. Read More about Is Your Credit Union Addressing the Digital Imperative?

Competition is a primary driver of player satisfaction and engagement in multiplayer online games. Traditional matchmaking systems aim at creating matches involving teams of similar aggregated individual skill levels, such as Elo score or TrueSkill. However, team dynamics cannot be solely captured using such linear predictors. Recently, it has been shown that nonlinear predictors that target to learn probability of winning as a function of player and team features significantly outperforms these linear skill-based methods. In this paper, we show that using final score difference provides yet a better prediction metric for competitive balance. We also show that a linear model trained on a carefully selected set of team and individual features achieves almost the performance of the more powerful neural network model while offering two orders of magnitude inference speed improvement. This shows significant promise for implementation in online matchmaking systems.

A model of sharing revenues among groups when group members are ranked several times is presented. The methodology is based on pairwise comparison matrices, allows for the use of any weighting method, and makes possible to tune the level of inequality. Our proposal is demonstrated on the example of Formula One prize money allocation among the constructors. We introduce an axiom called scale invariance, which requires the ranking of teams to be independent of the parameter controlling inequality. The eigenvector method is revealed to violate this condition in our dataset, while the row geometric mean method always satisfies it. The revenue allocation is not influenced by the arbitrary valuation given to the race prizes in the official points scoring system of Formula One.