You might have watched the 2011 film Moneyball or maybe read the 2003 book of the same name which the film is based on.
For those who haven’t seen or read Moneyball, it tells the true story of the American Major League Baseball team the Oakland A’s who were able to compete with teams boasting more than triple their payroll by adopting a statistical approach to player recruitment.
Statistics are nothing new in sports, but what the A’s did was explore a more effective way to evaluate a player’s ability by looking at less-discussed statistics which were often overlooked. While the approach was widely criticised by some of the A’s staff for going against the conventional wisdom used across the league for over a century, it ultimately brought in impressive results.
In the season this tactic was introduced, the A’s went 20 games unbeaten, one of the longest winning streaks in Major League Baseball history, with a team of relative unknowns.
Since then most Major League Baseball teams have now incorporated some level of statistical analysis to their player selection, signalling a shift from archaic methods based on outdated signifiers of talent to a new ballpark where data holds the key to getting the desired results.
That same disruption is already happening in the finance sector where data and technology are sparking innovation and transformation. The digitisation being experienced has handed businesses unprecedented amounts of data and opportunities to gather it. Being able to use that data to gain an advantage is now imperative to achieving targets in an increasingly competitive space.
New research from IDC has revealed that in 2015, the financial services industry spent $114 billion worldwide on mobility, cloud, and big data & analytics (BDA) technologies out of a total worldwide financial services IT spend of $455 billion. That’s more than 25% of IT budgets going towards three transformative technologies, and by 2019 that margin is tipped to reach almost 30%.
Organisations in the financial services industry are taking data analytics seriously to stay ahead of the pack – whether it be through accelerating innovation, driving optimisation, improving compliance or engaging customers by using data-driven decision making.
Seasoned business professional Martin McInnis has written a great blog for IBM’s Big Data & Analytics Hub about how the proper use of big data is arming financial services providers with capabilities that are driving increased productivity and profitability, read it here.
Download our Financial Services Use Case ebook to explore how our solutions are giving Banks, Credit Unions and Super Funds the tools to harness the power of big data and greatly improve how they do business.