Generative AI is a category of AI that can create new text, images, video, audio, or code. Generative AI is powered by foundation models (large AI models) that can multitask and perform out-of-the-box tasks, including summarization, Q&A, classification, and more. Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content. It then uses the learned patterns to generate new content. Learn about additional use cases in banking.

While AI’s potential to improve the banking sector for both banks and their customers is significant, it should be developed and applied in a responsible manner. It’s especially important in the context of generative AI. That’s because some concerns about generative AI’s accuracy and security are particularly acute when talking about its use in regulated industries, such as the larger banking system. We identified four critical building blocks for generative AI in banking: explainability, regulation, privacy, and security. 

Convert speech to text to improve your service with insights from customer interactions, such as contact center calls, and drive better customer service experiences.

Analyze sentiment in a given text with prevailing emotional opinion using Natural Language AI, such as investment research, chat data sentiment, and more.

Detect anomalies, such as fraudulent transactions, financial crime, and cyber threats.

Find suspicious, potential money laundering activity faster and more precisely with AI in retail and commercial banking. 

Deliver highly personalized recommendations for financial products and services, such as banking offers, based on customer journeys, peer interactions, risk preferences, and financial goals.

Make your content, such as financial news and apps multilingual with fast, dynamic machine translation at scale to enhance customer interactions and reach more audiences wherever they are.

Extract structured and unstructured data from documents and analyze, search, and store this data for document-extensive processes, such as loan servicing and investment opportunity discovery.

Derive insights from images and videos to expedite customer onboarding with identity document verification.

Delight your customers with human-like AI-powered contact center experiences, such as a banking concierge or customer center, to lower costs and free up your agents' time. Transform personal finance and give customers more ways to manage their money by bringing smart, intuitive experiences to your apps, websites, digital platforms, and virtual tools.

Use data customer, risk, transaction, trading, or other data insights to predict specific future outcomes with a high degree of precision. These capabilities can be helpful in fraud detection, risk reduction, and customer future needs’ prediction.

Access a complete suite of data management, analytics, and machine learning tools to generate insights and unlock value from data for business intelligence and decision-making.

Use data customer, risk, transaction, trading, or other data insights to predict specific future outcomes with a high degree of precision. These capabilities can be helpful in fraud detection, risk reduction, and customer future needs’ prediction. 

Automate aspects of cybersecurity by continuously monitoring and analyzing network traffic to detect, prevent, and respond to cyberattacks and threats.

Build new AI-powered search and conversational experiences by creating, recommending, synthesizing, analyzing, and engaging in a natural and responsible way. Watch this video to see how banks can transform the resolution of customer credit card concerns with generative AI. 

AI is set to accelerate growth across the banking sector. Digital platforms are enabling banks to adopt new sales strategies, improve efficiency, focus on data utilization, and offer personalized, relationship-based customer interactions on a large scale. AI is crucial in facilitating customized customer responses, providing safer and more reliable product and service recommendations, and gaining trust through expanded concierge services accessible to customers at crucial moments.

Furthermore, banks must develop distinct, permission-based digital customer profiles. The challenge is that the necessary data often exists in isolated silos. By dismantling these silos, integrating AI, and combining it with human interaction seamlessly, banks can shape experiences that meet their customers’ individual needs while efficiently scaling to growth.