We're finally on the cusp of the 2021 baseball season and we've all heard the phase “baseball is a game of inches.” A professional baseball bat, which on average is about 34 inches long and its 2-inch sweet spot makes up just a fraction of the barrel. The sweet spot offers the best chance for power and accuracy of the batted ball. A fielder reacting a fraction of a second to late could be the difference between an out or a run scored. Each of those inches add up. One run can be the reason for an additional win per month. A couple of extra wins could result in the playoffs and ultimately a chance to play in the World Series and be defined as the best. All this due to a game of inches.

FinTech is a game of milliseconds and efficiencies. A customer swipes, taps, or enters their card information when making a purchase and they’ve come to expects a response in seconds. Merchants, too, recognize that the slightest delay can result in a missed transaction. Do they realize the complexity of that payment? Do they realize the geographical miles traveled? How many systems and networks are touched to evaluate, secure, and approve the transaction? It's a game of milliseconds and trust.

The technological pipeline enabling the transaction is extraordinarily complex, but FIS makes it simple for merchants. We enable and monitor millions of transactions a day to give the impression to the end user that their transaction is the most important of all.

If you’ve seen the movie Moneyball, you’ll be familiar with the idea of ‘sabermetrics’ which took Major League Baseball by storm in 2002 when head coach Billy Beane used advanced analytics to help turn the Oakland Athletics into one of the best in the league. The idea was simple, use the data created from a baseball game (e.g., tracking hits, pitches, and home runs) to make better decisions in the future.

We take a similar approach with Fintech: the data flowing through the network becomes fuel for insights that help us make the system stronger. By collecting what may seem as unrelated, mundane, unstructured data and turning it into rich insights we identify healthy and unhealthy transaction patterns. A pattern of events that predict a known failure, gives us actions ahead of time to prevent unwanted outcomes. An unknown pattern of activity can be highlighted early on to uncover if an environment has changed allowing us to proactively research and act. Augmenting the skills to identify a potential problem, forecasting the transactions, capacity and ongoing health of the environment are what we’ve come to expect with an augmented operational environment. Patterns of the past will be recognized with speed and prescriptive antidotes giving us that extra step in defending against and eliminating known issues.