3 ways AI is revolutionizing banking and financial services

Over the past couple of years, AI has enabled new levels of independence, transparency, quality and accuracy in business, which is now motivating companies to further integrate intelligence into their operations.

The banking and financial services sector is a prime candidate for AI. In fact, 80% of this sector has already recognized the benefits of implementing AI – says a Business Insider study. It also estimates that banks which adopt AI in their digital solutions will save $447 billion by the end of 2023. It’s no surprise that investments in AI by this sector are set to increase in value by $1.2 trillion by 2035.

Here’s a look at 3 ways AI technologies are helping banks and financial services providers to gain a competitive advantage in customer service, compliance, risk mitigation and overall digital operations.

Decision-makers no longer need convincing that artificial intelligence technologies have the potential to enhance processes in banking and finance. There are already a diverse range of intelligent capabilities available to improve banking and finance processes, for example:

• Machine-learning based ID and document recognition (e.g. automated reading, classification and extraction of ID documents to, e.g., open a bank account) 
• Sentiment analysis (e.g. discerning a customer’s mood or intention in communications sent via digital and even non-digital channels, like a customer portal, a scanned letter or email, to route communications and address issues faster)
• The extraction of valuable structured content from interactions or documents (data that can be turned into insights regarding, e.g., customer actions, preferences and choices)
• Process ‘mining’ (analyzing, e.g., loan approval processes for insights into issues or scope for improvement)

Such AI-driven services can help employees to make faster and better decisions and improve the customer experience. Artificial intelligence is perfect for gaining direct and high-quality insights into customers, making it significantly easier to develop personalized services, customize product recommendations, and anticipate the customers’ future behavior. Eight out of ten banks that currently use AI in customer processes report an improvement in customer and employee satisfaction; a majority have seen an increase in AI-enabled customer interactions through, for example, chatbots. This poses an important USP in a competitive market that is laser-focused on providing a top customer experience.

In highly regulated sectors like banking and finance, customizable AI is playing an increasingly important role. While external data can be a good source of training sets for more general purposes, like image recognition, for compliance and risk use cases, it can lead to less reliable results or a lack of traceability. Banks and financial service providers might want the option instead to base their machine learning sets not on external training data, but on their own high-quality data, customized to their business. Furthermore, AutoML technology enables users to quickly train & deploy new AI models without the need for in-depth machine learning know-how. This combination of customizable AI and AutoML gives banks and financial service providers a powerful means of independently speeding up and improving fraud and risk detection as well as regulatory compliance.

Case in point
When authorities enforce new and tougher regulations regarding the retention and management of data, this has the potential to tie up personnel for months. A customer from the international banking sector recently approached us to help them find a way to analyze loan agreements and store a set of metadata for each one – as stipulated by new regulations. Without the use of content analytics and extraction, this would have been a very costly endeavor and, frankly, impossible for the team to complete within the given timeframe. Because this customer already has a content services platform in place, they are able to base the content extraction on its own data sets – ensuring higher quality results and no external influence.

In banking and financial services, where troves of information come from loan applications, risk analyses and ratings, property value assessments, stock settlements, etc., employees have to handle immense volumes of documents every day. Not only is there a high risk that they waste time searching for documents, but information (if it’s found!) is sometimes outdated or simply unrelated to the context at hand. Artificial intelligence can help to make document-intensive work faster, smarter and easier for employees, for example, by:

• Automatically ingesting, analyzing, verifying and processing information to ensure it’s constantly available, immediately accessible, up-to-date and error-free
• Recognizing and validating early on that all required information was included, e.g., in loan applications
• Automatically forwarding an inquiry to the right employee using named entity recognition (NER)
• Automating routine and repetitive tasks to free up an employee’s time to work on more value-added tasks
• Suggesting values for searching for and filing documents, based on an algorithm for word associations. This could, for example, improve a user’s search through the inclusion of semantically similar terms
• Identifying topical similarities in documents. This could help an employee to find all documents with a similar main topic

Talking with our customers over the past years, we have observed repeatedly that, because they already use a digital solution that unites document, process and collaboration services, it was easy to adapt to hybrid work scenarios. One bank executive, a customer, explains why they are able facilitate secure, remote work for their hundreds of users at a moment’s notice: “From our point of view, mobile working is no longer conceivable without a good document management system... A pure collaboration solution no longer suffices.”

In fact, having a document and process management solution in place has created the foundation for Raiffeisen Bank International (RBI) to start exploring ways AI can enhance their processes. Wolfgang Rachbauer of RBI, explains: “The next important step [of our project] is to evaluate the use of artificial intelligence in the framework of loan agreement management. This means not only producing loan agreements efficiently and securely, but also locating the content of contracts quickly – separately from OCR searches. The goal is to benefit from natural language processing in document layout and management, i.e. nothing less than ‘reading a loan agreement like a human being.’"

Are you interested in exploring how AI could enhance your banking and financial services processes? Would you like to experience firsthand how Doxis Intelligent Content Automation can make your operations smarter, faster and more customer-focused? Then contact us at any time. Our experts are happy to speak with you.