5 ways credit unions can apply machine learning today
Fueled by the large volumes of data available in today's digital world, machine learning has the power to completely transform the experience financial institutions deliver. Until recently, it was a tool available only to tech giants and international companies on the Fortune 500 list. But it is increasingly within the reach of financial institutions of all sizes, including community banks and credit unions. Brace yourself... you're about to see machine learning and artificial intelligence applications take the banking industry by storm.
Machine learning is an area of computer science that uses large-scale data analytics to create predictive and dynamic models. In essence, you feed the right data to computers with the right algorithms and they have the ability to learn — automatically, on their own. These algorithms iteratively improve over time. That’s the “learning” part of machine learning that allows computers to find hidden insights without being explicitly programmed where to look for them.
The exceptionally large data sets used in machine learning make it possible for computers to recognize both anomalies and patterns lurking within the information, yielding faster and more accurate data-driven decisions.
The process of crunching numbers is made more efficient, reliable and cost effective thanks to major advancements in machine learning. This up and coming technology is driving innovation in every sector — but particularly in banking — and it will only continue to grow in popularity.
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