Optimizing commercial Lending through Big Data Analytics

Banking CIO Outlook | Friday, November 30, 2018

Although the big data leap has come to create huge opportunities to businesses in making defining decisions and bolstering profitability, it also accompanies raging concerns of how to draw valuable insights and its implications to businesses when used incorrectly. The same stands perfectly true to commercial lending.  An optimum application of big data solutions can help businesses get valuable information about the terms on which other businesses avail financial funding. On the hand, it can also help lending institutions avoid uncalled for risks by having access to the most relevant information, thus contributing in creating a commercial lending process based on justice, equity and productivity.

The coming of cloud storage solutions although has come to make data storage a trivial issue, the biggest pain point towards the application of big data solutions to commercial lending is that of data swamp, leaving data ungoverned, de-contextual, unorganized and hard to find, thus, making the use of big data by commercial lenders detrimental to the businesses . The resolution to such a pernicious challenge certainly requires a technological solution that could filter the obsolete data and provide analysis that engenders valuable insights for decision making.

One of foremost software spearheading these solutions is Apache’s Hadoop; a java powered programming software that provides storage and processing of exponential amounts of disparate big data in a highly advanced environment of computing distribution. Hadoop, which is at the heart of Big data analytics has come to revolutionize commercial lending by providing risk management, sentimental analysis and preventing institutions from unduly engaging in fraudulent or criminal activities. Hadoop provides risk management by enabling lenders to access exacerbating ocean of data, used for credit, counter and geo-political risks. In addition it performs swift analysis of this data to help lenders make intelligent and apt decisions. Hadoop offers sentimental analysis through enabling its machine learning capabilities that draw pith from the large bulk of sentimental data. Lastly, Hadoop is equipped with the capabilities to identify relationships across different entities, aggregate data from remote sources and integrate with other external entities which together have come to make it a powerful platform to prevent all forms of fraudulent activities. 

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