There’s a lot to say on this topic and we’ll continue to explore it in future. At some point, you may be unable to create even a simple reports, because your spreadsheet contains too many different rows and variables.īoth examples of Big Data usage in fintech and reasonable methods of data mining/processing in banking you can find in this blog post. The more data you have – the more difficult it becomes to process it. Unfortunately, using Big Data in financial services comes with a price. Two-thirds of enterprises have even appointed a chief data officer for those purposes.
By now, about 80% of all companies from this sector are exploring Big Data and predictive analytics. analysts site that those spending will increase by 26% annually. What’s more, fintech is one of the most active users of this data.īack in 2015 firms from fintech spent around $6.4 billion on data-related programs. Financial industry generates a big chunk of this data.
We create 2.5 exabytes of data every day.
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