If you haven’t heard it already, let us be the first to tell you… AI can be a game changer for the banking industry. With AI-guided technology, financial institutions can process and scrutinize huge amounts of data, automate processes, and deliver highly personalized services. The key is integrating AI with the core and other front-end platforms using application programming interfaces.

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Although AI has been gaining momentum for nearly two decades, it has recently taken on massive popularity. In just the last year, ChatGPT attracted 1 million users within the first five days of the chatbot’s release; OpenAI launched DALL-E 2, a deep-learning model that can produce images from text instructions; and Google and Meta generated a way to produce videos from text.

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According to the Forbes Advisor survey, 73% of businesses use or plan to use AI-powered chatbots for instant messaging; and 61% of companies use AI to optimize emails, while 55% deploy AI for personalized services. The Forbes survey also found businesses onboard for AI to improve production processes (53%) and search engine optimization tasks (52%).

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According to a Deloitte report, AI can help improve efficiency, enable a growth agenda, boost differentiation, manage risk and regulatory needs, and positively influence the client experience. 86% of financial services AI adopters said AI will be very or critically important to their business’s success in the next two years.
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If your head isn’t already spinning with ideas of how you can use this for your financial institution, let us help get those creative juices flowing.
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AI in Banking‍

Where can financial institutions implement AI solutions?

  • Client experience. Enable frictionless, 24/7 interactions by leveraging conversational and natural language processing (NLP). Banks and credit unions can provide quick responses to client queries and needs. For example, clients can request information on account balances, make payments, or transfer funds using voice commands.
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  • ID and verification. Some financial institutions leverage algorithms on the front end to facilitate client identification and authentication, imitate live employees through chatbots and voice assistants, deepen client relationships, and offer personalized insights and suggestions.
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  • Improved compliance and regulatory oversight. Using AI, banks and credit unions can ensure compliance with regulatory requirements, such as anti-money laundering (AML) and know your client (KYC) regulations. AI can also help identify potential compliance issues before they become major problems.
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  • Automating the underwriting process. Analyze vast amounts of data, including credit scores, income, and employment history, to make lending decisions. By automating the underwriting process, you can reduce the time it takes to approve loans, improve the accuracy of lending decisions, and reduce the risk of defaults.
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  • Straight-through processing (STP) and exceptions. This enables banks to automate the total transaction lifecycle, from beginning to settlement, without human involvement. AI-powered predictive analytics can help banks to predict STP exceptions and other work drivers upstream, allowing them to take proactive measures to prevent downstream errors.

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An AI-Enabled Future

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The growing adoption of AI promises to have a lasting impact on the banking industry. However, financial institutions banks must still overcome operational and organizational challenges. The successful strategies employed by financial institutions undertaking an AI-enabled transformation highlight the need for an all-inclusive AI plan that encompasses all business lines, operational data, and alliances with third-party fintechs.

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Financial institutions must first solve some vulnerabilities inherent in legacy systems before deploying AI technologies. That begins with identifying systems that lack the capacity and flexibility required to support the computing requirements, data-processing needs, and real-time analysis of AI applications. In addition, banking data is fragmented and spread across multiple silos. For many analytics and advanced-AI systems to scale, organizations also need vigorous tools and processes to build, test, deploy, and monitor models.

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To overcome the challenges that limit organization-wide deployment of AI technologies, financial institutions must take a holistic approach. APIs connect and enable controlled access to services, products, and data. Within the financial institutions, APIs diminish the necessity for silos, grow the capabilities of technology assets, and improve flexibility in the technology ecosphere.

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The key to AI-based fintech partnerships and API usage lies with proper assimilation. Our OmniConnect Platform, for example, uses cutting-edge cloud technology to securely connect fintech solutions to financial institutions, ensuring a safe and reliable integration, and providing an open banking marketplace for all API needs.

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“Never stop innovating.” – Kinective

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