Artificial Intelligence in Banks
Naman Jain ?
Global Head - Sales and BD @ JMR Infotech | Business Analysis, Consulting, Project Management
Use of Artificial Intelligence to Enhance the Banking Experience for Customers
According to recent research by Gartner,?89%?of businesses will compete mostly on customer experience in the coming years. The research also indicates that?85%?of the customer’s relationships with an organization will be managed without human interaction in the next 5 years.
In short, the Gartner report indicates that seamless customer experience will be the yardstick on which the efficiency of a financial institution’s customer services will be measured. The battle lines to hold the competitive edge in customer experience are being redrawn on the digital landscape with the use of AI and ML.?
The banking industry today is staring at an inflection point with the acceleration of the digitalization process. Digitalization itself has evolved into multiple dimensions, ranging from the basic mobile and internet banking services to a more complex, biometric-enabled, secure transactional services.
Financial institutions that are quick to adopt technological advancements will continue to maintain a competitive edge. Artificial Intelligence (AI) and Machine Learning (ML) provide unprecedented opportunities to take the digital transformation to the next level. The fact that according to the Gartner report, there has been a?270%?increase in the use of AI by enterprises over the past 4 years, indicates that the process is already rolling with full steam. Joint research conducted by the National Business Research Institute and Narrative Science affirms that about 32% of financial service providers are already using AI technologies like Predictive Analytics and Voice Recognition.
AI and ML-enabled cognitive systems can help financial institutions to radically transform their customer experience in the following ways:?
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Automation of Customer Service
Customer service is one area where AI has made significant inroads in the banking industry. Today, if we were to chat with a ‘customer service representative’ on a banking portal, it almost always will be an intelligent chatbot, although you can’t be too sure if it indeed was a chatbot!??
Customer queries, for the most part, are predictable and repetitive, with preformulated resolutions already in place. The combination of AI and ML which enables cognitive systems to continuously learn from each customer interaction and improve its response to queries.??
It also eliminates the scenario of a customer being put ‘on-hold’ till an agent is available to solve a simple query, ensuring that ready resolution is available on customer’s demand.?
Moreover, customer support through AI can be made available 24x7 without any disruption and can be relied on to be error-free and efficient in the resolution of customer queries, while freeing up human resources for more complex tasks.?
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AI-Driven Data Analytics and Customer Insights
AI can help financial institutions build actionable customer insights through micro-segmentation of the customer data with the use of advanced Machine Learning. AI algorithms use billions of data points to systematically develop customer personas. Such integration of AI and data analytics enable financial institutions to effectively use its structured and unstructured data to not just transform its customer experience but also enhance the effectiveness of its marketing programs.?
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Enabling Personalization to Marketing Programs
There are hundreds of mass emails that offer a host of products and services, cluttering customers’ inboxes on a daily basis. Personalized communication therefore would help ensure our communication stands out from the clutter and captures the mindshare of the target customer.?
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Customer segmentation and customer personas created through data analytics by AI can help financial institutions to offer only relevant products and services that would be of interest to the different customer personas. When such smart targeting is combined with personalized communication and curated content, it would be more effective in engaging customers and lead to better sales numbers.?
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Ensuring Regulatory Compliance
Financial institutions across the globe are required to abide by stringent regulatory compliance norms. Today’s customers have a wide variety of payment and investment options available at their fingertips vis-à-vis crypto-currencies, shared economy, and marketplace lending, which in turn has led to more sophisticated money-laundering operations.?
Conventional compliance methodology which involves AML experts screening suspicious transactions would take hours with the possibility of human error letting some fraudulent transaction slip through. AI, on the other hand, can harness the power of advanced data analytics to sift through piles of transactional data to identify fraudulent transactions and improve compliance.?
AI algorithms can complete the anti-money laundering scan within a few seconds, which otherwise would take hours with human effort. Ensuring regulatory compliance leads to better branding of the financial institution which in turn yields improved revenue, reduced costs, and better profit margins.
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Improving Operational Efficiencies
AI can help financial institutions to reduce their operating costs by adopting more efficient operating models while ensuring tighter control of the operational processes.??
Identifying and replacing manual, repetitive, labor-intensive processes like teller transactions or ATM transactions for cheque deposits with a more efficient mobile cheque deposit results in significant cost savings by eliminating the need for a bank teller.?
AI enables the processing of the image of the cheque to complete the transaction. The whole process is designed to ensure efficiency, improve the speed of processing the transaction while ensuring transactions are error-free.?
Likewise, AI-powered chatbots can automatically resolve straightforward queries checking account balances or resetting the password, providing a seamless customer experience, while helping to reduce the call volumes, leading to a leaner and more cost-efficient call center.??
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