Brian's Blog


Big Data analytics is transforming the financial services landscape. Over many years, the focus of big data analytics has been in the client acquisition and marketing side of the financial services industry. But over the past few years much progress has been made in utilizing big data analytics techniques, such as natural language processing, or NLP

As I have described in earlier blog posts, traditionally unstructured data was too complex for common statistical programming languages to analyze. Therefore, in order to gain meaningful interpretations from unstructured data, people had to manually sort through various and voluminous sources of data to draw conclusions. With limited resources and an overwhelming quantity of data, this method has become inefficient and costly. As a result, a series of tools and methods have emerged over the years that enables analysts to process and analyze both structured and unstructured data to gain valuable insights and help guide business decisions.

NLP refers to techniques that allow text to be analyzed and identify trends, patterns, and statistically relevant findings through mining thousands of data sources. Using NLP techniques, analysts can discover unexpected correlations or anomalies for businesses to investigate and can analyze at a higher level than previous technologies would allow. Businesses are increasingly using NLP to react faster to changes in data and make better business decisions. Organizations can benefit from the use of NLP in various industries such as banking, insurance, healthcare, and law enforcement.

In an article published this month in CFO magazine by David Katz, “Big Data, Smaller Risk” he explores the role of big data through a series of use cases impacting financial services. In particular, David gives me the opportunity to describe in detail a use case that I have implemented in the financial services industry with regard to monitoring borrower support using NLP.


This article represents the views of the author only, and the information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation.

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