Big data analytics helps JPMorgan identify the best set of products they can deliver to their customers
JPMorgan started off with open source Hadoop framework using a small Hadoop cluster but now it relies on the tiny elephant for making decisions about mission critical investment projects.
“Hadoop's ability to store vast volumes of unstructured data allows the company to collect and store web logs, transaction data and social media data. Hadoop allows us to store data that we never stored before. The data is aggregated into a common platform for use in a range of customer-focused data mining and data analytics tools”- said Larry Feinsmith, Managing Director of IT at JPMorgan Chase.
"JPMorgan started off with open source Hadoop framework using a small Hadoop cluster but now it relies on the tiny elephant for making decisions about mission critical investment projects.
JP Morgan still depends on relational database systems, it is extensively using the open source storage and data analysis framework Hadoop for risk management in IT and detecting frauds.
The use of big data at JP Morgan Chase helps in optimizing the sales of foreclosed properties helps develop new marketing initiatives, managing risks and helps in credit assessment. The big data analytics technology at JPMorgan crunches massive amounts of customer data to discern hard to detect patterns in the financial market or in customer behaviour that can help the bank identify any risks in the market or possible opportunities to make money. The analytics systems at JPMorgan analyse internal bank records and relate them with other sources of information so that the financial institution can draw better insights from the data to get a clear perspective of their customers-by predicting which customers are credit-worthy and prospective buyers of novel financial products or services."