Sustainability in Banking Sector through Data Analytics
bankingciooutlook

Sustainability in Banking Sector through Data Analytics

By Banking CIO Outlook | Wednesday, October 31, 2018

A recent survey conducted by the Chartered Institute of Bankers Nigeria (CIBN) on the financial sector shows that data analytics plays a critical role on the future banking sector by creating values with respect to work efficiency. The president and chairman of CIBN, Uche Olowu, believes that still there is a requirement of efficient integration model amongst bank and Fintech to evaluate the technological gap amongst them in a cost-effective manner and provide more efficient services. During financial analysis, banks should leverage the process of data analytics to extract efficient insights, but the process seems to be complex since fintechs are disrupting the space.

At present, there are several data analytics tools and techniques to analyze the huge amount of data collected. Selection of better technology along with customer service channel and business model helps in getting better insights about the customers and increase efficiency through the service agreement with customers. The better strategy that can be deployed in banks is to develop a strategic alliance amongst the fintechs and the banks so that the services delivered can be easily modified with respect to the changing environment, especially in the retail sector.

Furthermore, it is seen that numerous innovative banking opportunities face the challenges of structural cost along with benefits collected over an extended time frame. This can be overwhelmed by developing an innovative adoption framework. The idea or source for the model is captured from the influencers who can be the targeted customers, vendors, advisors, or regulators. The obtained data is given as input to the model and is processed through several stages such as initial review, feasibility review, and capability review enabled through data analytics algorithms to ascertain better coordination with procurement process or vendor risk management activities.

There are numerous opportunities that banks are missing due to their inability to process the captured data completely. Ascertaining proper communication amongst the customers within the bank also fails to extract the complete advantages of data analytics. Harnessing effective data through data mining algorithms help in retaining the loyal customers as well as gaining more profits. Furthermore, with the deployment of automation and artificial intelligence in banking sector helps to target growth in the selective market and deploy technological investment to gain better customer experience with user-friendly operations.

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