Few industries depend as heavily on data as financial services. Insurance companies, retail and investment banks aggregate, price and distribute capital with the aim of increasing their return on assets with an acceptable level of risk.
To do that, financial decision-makers need data. Apache Hadoop helps them store new data sources, then process the larger combined dataset for batch, interactive and real-time analysis. More data and better analysis improves bottom-line results.
Read this Hortonworks white paper on seven common financial services use cases that are generating enthusiasm in the industry.
David Gleason, managing director and head of data strategy at BNY Mellon, recently shared his enthusiasm for Hadoop in The Wall Street Journal saying, “It’s the most exciting technology I’ve seen in my career since the advent of relational database management systems.”
Here are three examples of financial services use cases covered in the white paper:
While participating in the 2014 Hadoop Summit keynote panel discussion “Hadoop in the Enterprise”, Gleason from BNY Mellon articulated how his bank came to understand the opportunity presented by Hadoop:
“As we brought [Hadoop] in, we started to realize that there was so much more we could be doing, and that it really was more than just big data and decision science. It was a platform for really changing the way we manage data around the organization.”