After a short break back home in Bangalore, it was time to get back to the world of technology and this time in a new country and city! While I was tempted to pen my thought on the SAP HANA Cloud Strategy the last few weeks saw me present my ideas to my new colleagues Max Richard, Toon D’Hollander, and my bosses – Rocky Woestenborghs, Jean-Pierre Nelissen and Thomas De Wulf on the topic that is Big Data 😉
Of course, my discussions on the content and context was rather specific to ING which I will leave out for obvious reasons but I thought of taking a broader outlook of the impact Big Data specific to the banking and the financial services world ! I read this article on What Makes big Data Projects Succeed and it got me thinking what is the mode of functioning in the bank for Big Data?
Data analytics have completely reshaped the enterprise data management and even more so in the financial world. So I thought among all banking institutions and their structures, these are some possibilities of “How to use Big Data in banks“:
Use predictive analytics to generate the Next Best Personalized Offer especially in real time either over the internet or over the brick-&-mortar interaction at the counter!
Use more sophisticated data models and stochastic paths to capture Fraud and Compliance activities. Basically it is the case of correlating data from the trading activity to newer data sources such as social media and emails, to detect different patterns. Hadoop can significantly lower computing costs as well.
Use Big Data via departments in Marketing and Corporate Communications as a leverage. The company perception and public feedback on new policies and products can be analyzed in real time. Differentiate ’noise’ from information or create a buzz around the service/product/policy is possible with Big Data.
Big Data is not just about analyzing Twitter feeds or websites. It can be used to integrate data and then in different sets break them into smaller sets of data to study purely financial transactions. Financial transactions are highly complex computations and data-intensive. So a good idea to just get product analytics and next best personalized offerings would be to integrate data, run analytics, new data models and use in-memory databases. The important part is not about simply using Hadoop mindlessly and also have a nice mix of traditional storage on tapes, cloud…………….
Banks are no more the only ones to have customer information. In fact banks are lagging in understanding customers. New peer-to-peer services and the PayPal’s, Amazon’s, Google’s and Walmart’s are the new competitors to banks. What you don’t want is information in silos in the bank or search for information across infrastructure. But how can legacy and what you would call a future bank coexist ? That we discuss on some other post, some other time! One thing is sure, banks need to realize that Internet is therefore at the heart of their distribution architecture!
The world of Big Data shows how much information exists in the world and we just need to tap into this information to get wisdom. It’s been such a nice a wonderful journey to personally serve people or from a distance watch how lives get transformed 🙂 This time around my focus is on ethics in business and since it happens in my new hometown of Brussels – time to work hard 🙂