How Big Data Analytics Influences Banking IT

Milind Rajhans, AGM-IT, A.P.Mahesh Cooperative Urban Bank Ltd

Milind Rajhans, AGM-IT, A.P.Mahesh Cooperative Urban Bank Ltd

It was thought that implementation of Core  Banking Solution (CBS) in Banks will be a panacea for all manual illnesses for Banking  Processes and will satisfy growth objective spanning a decade or two. However, with the multi-fold increase in customer demands and business, Core Banking functionality, Scalability and Performance came to the fore.

“Banks are adopting BigData technologies to capture the business preferences and predict trends from the social media presence”   

 The important factor is there is no native  tool available in CBS to analyse the massive data  (Big Data!) that it is being generated on daily  basis. Further, no one is sure about what to do with this Data, how it has to be slice and dice  for generating the meaningful information which  is necessary to re-design the products as per the  customer demand.

Now the era of  providing affordable excellent products has emerged and will continue for  years to come. Competition will increase day by day and there will be strong need to focus on customer centricity for business growth than any  other thing.

Banking is the industry with largest consumers  with variety of service offering which requires  High Performance Computing (HPC). As such,  there is no surprise that Big Data and its related technologies affect Banking Industry as like other  industries.   

Banks understood that the Data Analytics is  required to predict the financial health. Big Data  Implementations provide the opportunity to  manage huge volumes of disparate data, at the  right speed, within the time frame, facilitating  Banks to have real time analysis of their customer  data.

Banks are adopting Big Data technologies  to capture the business preferences and predict trends from the social media presence. Social  Media has emerged as a medium for banks to  make out the customer insights, consumer habits  and behaviour, helping Banks to design the  products and services.

The recent trend of analysis of consumer  purchase behavioural Data and sharing the  same to the retailers is facilitating the retailers to  provide special/discount offers on the products and services. The analysis also helps the sellers  to showcase their offerings to the consumer  whenever they are browsing the similar category  product.

Today numerous mobile and sensor sources  of data are emerged, so there will be too much  requirements for rapid ingestion of huge amounts  of diverse data types. In order to process these  requirements, related tools and Technologies are   to be in place, wired or wireless networks should   not struggle to provide the capacity needed to feed   some of the planned big data implementations. In  order to achieve desired results in time, the data is  to be analysed strategically as it is ingested so that  both the processes running concurrently should  not Conflict/disturbed. This specifically requires   technology to be in place which can handle small   jobs separately and big jobs separately otherwise   in high throughput frequency the smaller jobs will    get lost. Here the challenge will be in ensuring   to allocate the resources for the smaller jobs. The  technology shall provide the solution where the  nodes are being dedicated automatically to these  smaller jobs without disrupting the larger jobs requiring individual scheduling.

The more data Banks can collect, the more  they can analyse to better predict the stocks. The  better their capabilities to analyse the data, the more precise they will be about their business predictions. In short, unless better analysis and visualization tool, financial institutions will be unable  to comprehend the relationship or pattern that exists within the data, defeating the point of using it at all.

Banking IT certainly will have challenges to mitigate the above  scenarios strategically within their  budget to get the competitive advantage of the technology without losing the opportunity of the Business  requirements & its related pressure there of. 

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