The Banking industry is experiencing significant transformation, particularly with the propagation of customer-centricity. We live in a world where most of us are digitally empowered. The scope of digital transactions has increased through different mediums.

Banks have already started implementing Artificial Intelligence (AI)-based solutions to uplift their processes to offer a smooth customer experience. AI-powered processes assess customer credit histories more accurately to minimize future payment default. Using AI in processes like these helps banks make faster and more precise predictions to analyze the risks associated with issuing loans, insolvency, and the threat of fraud. Banks and Credit Unions worldwide are also applying software robotics in their business processes across diverse functions.

AI does not limit itself to just making processes smarter. Machine learning (ML) and Artificial Intelligence can be implemented to make processes far more intelligent and study consumer behavior, purchase patterns, and human sentiments to make better decisions. AI analyzes user data to improve customer service and deliver it much faster than traditional systems. AI is providing Banks and Credit Unions across the US the opportunity to further enhance both business and customer value.

We have listed some common AI use cases that Banks and Credit Unions can leverage to improve efficiency, lower operational costs, reduce human error, and personalize customer service.

AI Chatbots – AI Chatbots (also known as bots) are modernizing Banking services offered to customers. AI bots can provide customers with 24*7 *365 service and help with everyday queries. AI-powered chatbots can provide a more personalized experience to users with an accurate and faster response rate. According to a survey by Juniper Research, banking-related chatbot interactions will grow by 3,150% (between 2019-2023), and Banks will save around 826 million hours through chatbot interactions by 2023. The AI chatbots for Banking and Finance operations are already influencing customer retention positively and optimizing their quality of service.

Security – AI can help Banks and Credit Unions identify and mitigate cyber risks. It takes longer for the human IT force to detect and stop these threats, resulting in increased demand for AI in cybersecurity. For example, JP Morgan Chase built an AI algorithm to detect cyber threats (trojans, malware, phishing, etc.) in advance. Banks can now counter potential cyber-attacks with continuous AI monitoring before the threats affect the internal and external (customer-facing) systems.

Robo-Advisors – Low-cost alternatives to traditional advisors can provide financial counseling to many more people. By using Robo-advisors, customers can directly make their own informed financial decisions (retirement, mortgage, financial planning, etc.).

Customer Experience – From everyday transactions to solving customer queries, AI has made breakthroughs across industries. Conversational AI influences customer experience with technologies like Natural Language Processing (NLP) and Predictive Modeling. Bank loans take just 2 days (with AI) for approvals (instead of 10-15 days), significantly improving customer satisfaction. A McKinsey survey of US Retail Banking customers reported that deposits grew 84% at Banks with the highest level of customer satisfaction (all thanks to AI) compared to Banks with low satisfaction ratings.

Underwriting – Artificial Intelligence is proving to be an important asset for Banks and lenders to make accurate underwriting decisions. AI-based underwriting solutions power insurers to optimize financial risks. It also amplifies the scope of data sources that underwriters can use for continuous evaluation. BFSI organizations can use AI to mine large amounts of data which improves underwriting productivity and reduces operational costs.

Collection & Recovery – According to debt.org, 191 million people in the US were using credit cards with Credit exceeding 14.9 trillion dollars in 2020. Leaving the collection process to traditional methods would have created significant issues for the lenders. The lenders had to use a smarter way to collect the debts on time and manage their cash.

Compliance – AI helps mission-critical compliance functions such as Know Your Customer (KYC) during onboarding, customer lifecycle management, risk management, fraud prevention, reporting, etc. The regulatory adoption of AI has been increasing over the years, and with increased coordination between RPA and Machine Learning, the AI-based platforms will aid with complicated compliance functions.

AI is expected to become a key driver for growth for banks in 2022. With increasing AI solutions, there will be an increase in acceptance by more Banks and Credit Unions in the future. It will continue to evolve and help the Banking sector enhance quality, empower customers, enrich employees while benefiting all the stakeholders involved. AI in Banks and Credit Unions can help generate new revenue streams and streamline processes to onboard clients, manage security threats, and deliver better customer service.