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Friday, October 29, 2021

How AI Powers Bank Transformation

Over decades, banks have adapted technologies to understand how customers interact with them. In the 1960s, they introduced ATMs, and by the 1970s banks hopped to card-based payment and later by the 2000s the shift was more on 24/7 online banking services and in 2010, mobile-based banking became a popular trend. Did it stop there? No! Artificial Intelligence (AI) technologies have become an integral part of the world that we live in. The ripples of its powerful impact are felt across the financial industry.

The digital age powered by AI-powered technologies gave banks a big leap as its capabilities were seen to support reducing data storage and process costs and increase access and connectivity for value creation. As customer value, market share, and revenue play the bottom-line goal of the banking sector, banks optimize AI to the core to gain a competitive edge while stepping into big markets and expanding globally.

A distinguishing feature of deploying AI capability into banking systems is that it is more dynamic to meet the evolving business needs, unlike relying on static rule-based approaches for solving business challenges. However, let's try and find out how AI matters to the Banks.

Broaden Customer Base

Customers are a lifeline to banking systems. So to track sentiments, needs, and preferences, banks optimize new technologies like AI. One of the advantages of using AI is to identify the journey of customers, mostly the potential platforms like mobiles, messages, bank kiosks, ATMs,s or bank websites to access information and meet financial needs. By closely following the customer trends, banks will be able to customize support and services on the launch page to gain customer attraction to the offerings. AI applications help to reduce tons of messages, focus on prospective customers based on their responsive levels and engagement through strategic communication. According to a recent Harvard Business Review report, around 20-25% of customers adapted mobile or online banking channels and it is predicted that about over 45% of customers will cut their branch visits once the pandemic subsides.

Credit Lending 

One of the primary functions of banks is credit lending. Let us imagine a customer is on his toe to get a loan from the bank, but if the process is tardy, he might lose interest. To bridge the service gap, many banks have built lending schemes using AI that has the ability to make smart and real-time decisions of customer data and other verification processes. Some leading banks use AI to quickly check on the lending limits, the income, and repayment capacity of their customers through leveraging Optical Character Recognition (OCR).

Pricing Strategy and Investments 

A primary source of revenue for banks is interest on loans, and it employs competitive relationship managers and sales executives to adjust interest rates within certain limits. But due to stiff-neck competition to provide interest at a lower rate might look a bit more complex, but banks capitalize on AI to devise effective pricing strategies through computational technologies and data engineering.

Detecting Frauds and Risks

Machines are superior in crunching vast amounts of numbers and data than humans. Unless AI tools are badly programmed, there is hardly any chance that they commit errors in calculating numbers through various algorithms. With the world growing more tech-driven, the security risks are considerable, hence integrating AI-ML can act as a prizefighter for banks in sensing threats and flagging them. AI has the potential to enhance user authentication through sound analysis of varied factors.

What’s Next

Since the use of AI is episodic and focused on specific use cases, the majority of the banking leaders are moving for a comprehensive approach to deploying AI from the front- to the back-office operations. Moreover, AI is not going to take over banking overnight, rather provide a glimpse into the future of the retail banking system.



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