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Big Data Changer for Banking

Will Big Data be a Game Changer for the Banking and Finance Sector?

Big Data analytics is becoming a significant game-changer lately, especially within the last 5 years. One of the most competitive disruptive technology there is today, Big Data is often used as an analogous term for real-time analytics and customer analytics. Or, is at times used to denote a combination of technologies and contemporary methodologies used to organize, collect, analyze and process a diverse range of data (both structured and unstructured) on the chain.

This, added advantage of Big Data–Business insights into data, has an outstanding potential to assist banking and financial sector at large in the coming years. Here’s how-

The Impact on the Financial Sector

It’s understood that the financial sector is the most data-intensive sector in the world. Banks have a huge flood of customer data flowing through their systems every second, but unfortunately, this data is underutilized. Adding to this, with the changing dynamics of the fintech sector, banks and other financial institutions are lacking in meeting customer’s changing expectations. Moreover, an increase in frauds are also adding to the risk factor faced by the traditional technological setup in the banking and financial sector.

Solutions Big Data offers to the above set of issues along with a few additional challenges today-

Customer Service– Understanding customer behaviour is the most important key to launching a great advertising strategy, and the financial industry lacks this to a certain extent. With Big Data analytics into play, companies involved in the financial sector can easily have a greater understanding of evolving customer expectations. And from these customer insights, they can retarget them with a better-advertizing strategy and enhance the customer experience.

Risk Management and Fraud Detection- One of the biggest advantages of Big Data analytics is contemplating risk factor and identifying potential frauds. Through a data-driven setup, financial companies can easily predict, detect, and prevent frauds. And all this can be done in real-time within a cost-effective budget therefore eliminating any further losses.

Customized Solutions– There are only a few financial companies in the world, that actually use targeted marketing. With cost-effective Big Data Analytics, companies can eventually customize their solution offerings to the customer, in short, they can do target marketing or campaigns through these insights.

Enhancing employee engagement- Although this impact of Big Data analytics is inhouse, data-driven analytics can empower employee engagement and enhance work performance as well. The technology can help HR managers classify best work performances and use the analytics to improvise the overall success ratio of all employees. This will impact both overall revenue and operational workflow, set within the organisation.

Final Words

AeoLogic is at present working with both public and private sector companies and is assisting them in identifying their technological scope, in order to maximize growth and revenue both. At present, the company is handling major technology projects with Spicejet, and Government of India.