Saturday, July 13, 2013

Bigdata in Banking Domain

As financial industries growing with evolving business landscapes and increased information and business demands, finding efficient ways to store, organize and analyze the continuously increasing hell of data and integration and analysis is really crucial job. How effectively they can make better business decisions based on the this huge amount of data in short Bigdata they processes on a daily or weakly basis will be hurdle for the industry going forward. Nowadays banking system introduced very innovative and productive banking ideas like mobile banking, SMS banking, as we are able to carry banks in our pocket and every transactions are on our fingers. As it is increasing and having many more ideas equal proportionally the risk of banking also increasing like fraud, fake transactions, fake user accounts, miss-use of banking products by thefts and hackers.

Banking industries are using structural data from many years ago and finding a ways to tackle with such situations but they are not that much effective and accurate, So banks also should focus on not using more data but should use more diverse and variety of data from different data sources available on network, this includes not only the banks internal transactions and profile based data but the external information such as social networking data, application logs. Previously such data considered as none of any use but banks should use this data for customer analysis and getting more business insights out of it. Simply Banks should not only use internal structured data(traditional data) but also the external unstructured data to grow with more accurate results and effective predictions.

Bigdata plays a very important role to protect and secure end users and he’s banking activities. There are 1000’s of ways to protect our customer from theft and fraud if you have amount of data. As we can do analysis of customer transactions and monitoring its regular activities like customer salary, beneficiary transactions frequency and amount of every transaction helps banking industry to analysis of customers, customer location and transaction location analysis.

Today social networking is being very important part of every business network, we can found lots of ways customer analysis and sentimental analysis against products, as product reviews are easily available on such networking sites. There are 100s of solutions based on Hadoop available to replace banking traditional crucial analytics to new real time and less time consuming solutions to developing true relationship based analytics and finding out the true business values as per customers views.

Think again in growing business perspective take a look what data (internal plus external) we have, how we use it more effectively and where should we focus more to get more accuracy to fight in competitive market for survive and grow.