Intelligent Banking

By Manoj K Mishra, Vice President - Technology, Magma Fincorp Ltd

2016 has seen a decent push towards knowledge integration in Banking and Financial services sector. Robots are no longer a fancy concept but have already invaded enterprises. Robotics is essentially backed by Artificial Intelligence (AI), which is powered by Machine Learning. For example, Axis Bank has deployed AI powered chat bots to resolves customers issues (ET Tech, Nov 15, 2016), while HDFC has deployed chat bots for conversational banking (Times of India, Dec 28, 2016). AI is thus all set to make the working of Banks intelligent.

Machine Learning, Artificial Intelligence and Robotics, have potential to reduce costs, lend extended arm to business, improve upon customer experience and portfolio quality and also offer engineered products to customers. Banks and Financial Institutions have traditionally invested in Data Warehousing and reporting solutions. Banks are now in the pursuit of unlocking the potential much more with a broader scope and deeper impact. Technological advances are timely. On-demand computing, in-memory processing of large data sets, faster data processing with Hadoop kind of technology, hyper-converged infrastructure, advances in securing mobile transactions etc. are all timely that can support knowledge integration through the value chain. It is for the enterprises now to unlock the untapped potential.

Customer servicing is no longer just about 360 degree view of customer, but an intelligent handling of them. Customers can be offered engineered products to suit their needs and also safeguard Banks’s risk. Handling of NPAs, one of the most daunting task of any Banking and Financial institutions, is just getting better by the ability to predict the probability to default at customer level. Banks are able to utilize their field workforce intelligently by integrating these insights with mobile applications. While Mobility has disrupted the brick-and-mortar business model, Intelligent Banking is poised to take the whole sector to next level by creating an impactful customer and internal touch points. Routine jobs can be handled by Robots. This can have impact on traditional departments like strategic performance management, which need not carry an army of people to crunch data. Allocation of manpower can thus be on the basis of predicted business pattern to gain on productivity. It can also lead to better channel effectiveness. Customer experience can take significant improvement by adding intelligence to customer touch points. However, all of these require a robust back-end data processing. This is possible today with other timely advances like on-demand computing, fast in-memory processing of data, smart data aggregators, Data Mining engines, tools to handle big data etc.

"Intelligent Banking powered by Machine Learning, Artificial Intelligence and Robotics, is an evolutionary step forward"

ICICI Bank is reported to use Analytics to improve debt recovery. As per an article in Computer Weekly (Nov 2011), ICICI has been able to reduce credit loss by 50%, reduce manpower in interventions by 80% and reduce the turn-around-time (TAT) from days to few hours. Other banking players in India are not far behind. Axis Bank is reported to increase the productivity of its sales force by 5 times by using Analytics, as per an article published in CIO & LEADER. As per an article in Computer Weekly (April 2011), Kotak Mahindra Bank is reported to use Machine Learning for fraud detection and also credit scoring. As per ET (Jan 29, 2015), SBI, the largest Bank in India, has strengthened its team by hiring 16 statisticians and economists on board for advanced analytics focus. SBI has taken leap forward and added social media for customer sentiment analysis.

However, there are challenges to this journey. As advances in automation in enterprises, people on the ground fear their jobs. This fear needs timely attention and preventive measures like training their workforce in other required skill areas, effective change management and communication etc. There can also be the challenge in adoption of such sophistications by the workforce. This can be addressed by making it an easy to use solution and also adequate on the ground support for the line staff. Information security can pose a real threat, if not deployed sufficiently. Worst can happen if a hacker can manage to get into the intelligent ecosystem and misguide business. Much harm can be done even before it is realized. Hence enterprises must focus heavily on adequate processes, procedures and technology to secure information perimeter through curative as well as preventive actions. Interestingly Machine Learning is also being used for security solutions.

Intelligent Banking powered by Machine Learning, Artificial Intelligence and Robotics, is an evolutionary step forward. It is now time for the enterprises to embrace the advances in right context and prepare for the changes and disruptions.

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