Impact of Big Data on Finance Industries

Banks have been storing enormous amounts of data since ages and this valuable data has helped understand customer behavior and helped prevent thefts. Banks in the United States have already been using this enormous amount of data in various spheres such as sentiment analysis, risk management, product cross selling etc. Big Data can be applied to banking firms in areas of such as analysing the spending patterns of the users, the possible loans a user wold take in the future, fraud analysis, customer segmentation, product cross selling, customer segmentation, sentiment analysis etc.

The major areas of work in a Banking firm where Big Data can have a drastic impact are:
1. Customer Centric
2. Risk Management
3. Transactions
Customer Centric: Big Data can be applied to measure the client feedback, strategy planning, decide the next best offer , sentiment analysis, analyse the customer life events, measuring the quality of leads etc.

Risk Management: The ways in which data analysis is being used to find out and evaluate financial crime management (FCM) solution rules, by early detection of the correlation between financial crime and attributes of the transaction, or series of transactions are MIS reporting, real time keyboard conversations etc.

Transaction Analysis: Transactions tend to reveal a lot about the nature of trade, log analysis etc. The ways in which this can be done are log analytics, B2B merchant insights etc.

With the help of Big Data analytics banks can perform better Risk Management, Transactional Analysis and also get Customer Centric data faster.