Natural language processing can transform banking — here are 4 use cases

Generative artificial intelligence (gen AI) is not just a trend—it is arguably a revolution in creativity and communication. On one side, we marvel at its ability to create relatively new, though somewhat unoriginal content. But let’s not forget the other side of this coin, the equally remarkable ability to generate complex content from everyday language. This is a potential gamechanger for banks and credit unions of all sizes.

This transformation demonstrates an ability to equalize technological access, a key pillar of the so-called open finance movement. Whether banks and credit unions use gen AI to create innovative concepts or to simplify complex ideas, natural language processing (NLP) bridges the gap between communication barriers and technological prowess, making the extraordinary accessible to all.

Nowhere is the transformative power of NLP more apparent than within community financial institutions. Today, community banks and credit unions are not just competing with one another and national counterparts, they increasingly must keep with traditional tech competitors that bring payments options to the table. Since NLP bridges gaps in communication and technology, it levels the playing field in at least some banking offerings.

For community financial institutions, this means it enhances customer interactions, streamlines operations, and empowers strategic decision-making. NLP is far from second-rate technology that comes as an addendum to gen AI; it is a powerful tool that can boost productivity and maximize ROI. Many people exclusively associate NLP in financial services with chatbots and virtual assistants, but these applications only scratch the surface of its potential.

Here are four use cases where banks and credit unions might find potential value in NLP technology.

Information Retrieval Systems

It is not an exaggeration to say that financial institutions deal with vast amounts of data daily. Whether retrieving client information, transaction history, or compliance documents, these systems streamline data access and reduce the time employees spend searching for information. By streamlining routine processes, this approach frees up valuable time for employees, allowing them to channel their expertise into more impactful and rewarding work. Not only does it boost overall productivity, but it also empowers staff to tackle complex challenges, develop innovative solutions, and provide the type of personalized service that truly makes a difference for customers.

Automated Translation

In a globalized economy, financial institutions serve a diverse clientele who speak multiple languages. NLP-driven automated translation services facilitate seamless communication with non-English speaking customers. This not only broadens a financial institution’s customer base but also ensures compliance with regulatory requirements in different regions. Automated translations can be deployed within chatbots and virtual assistants and be used to market to diverse customer bases. The more people a financial institution can reach, the more likely they can grow their deposits and remain solvent.

Text Summarization

Financial institutions generate extensive reports, from market analysis to financial statements. NLP-based text summarization tools help in condensing lengthy documents into concise summaries, highlighting key information and insights. This makes it easier for stakeholders to digest complex information quickly and make informed decisions without getting bogged down by details.

Sentiment Analysis in Social Media Monitoring

Understanding customer sentiment is crucial for financial institutions to maintain a positive reputation and improve their services. NLP-based sentiment analysis tools monitor social media platforms to gauge public opinion about an institution’s products, services, and overall brand. By analyzing customer feedback in real-time, banks can quickly address issues, adapt strategies, and enhance customer relations.

In a world where technology and human interaction are constantly evolving, and buzzworthy innovations dominate conversations, NLP makes much of the user interface we rely on possible. NLP is not merely an extension of gen AI; it is a formidable force that democratizes access to technology and information. Community financial institutions, facing the immense pressure of competing with Big Tech, find in NLP a powerful ally. This technology not only amplifies FIs’ ability to enhance customer experiences, but it sharpens their competitive edge by streamlining operations and enabling strategic decisions.

As we look to the future, the true value of NLP lies in its ability to break down communication barriers and drive innovation across the financial landscape. Whether through NLP-powered information retrieval systems, automated translation services, sentiment analysis, or text summarization tools, the potential applications are vast and varied. Each innovation brings us closer to a more inclusive, efficient, and effective financial ecosystem. The extraordinary becomes accessible to all, ensuring that every player, big or small, has the tools needed to thrive in the digital age. With NLP at the forefront, the future of finance is not just about keeping up with change; it is about leading the charge into a new era of possibility.

Alex Borsuk is Head of Data and Software Engineering at Finastra.