Business insights

NLP to drive process revolution in banking

NLP to drive process revolution in banking

Unstructured textual data is an important resource but simply having access to it is not enough: banks need to monitor the quality of their data and to implement the right technology and solutions to analyze and process it efficiently opening up new business and operational scenarios.

read time

Natural Language Processing (NLP) applied to the financial and banking sector: driving efficiency, providing insights, offering better, tailored services and improving customer satisfaction.

Leveraging high quality data to thrive in the banking sector

Complexity in the financial services sector keeps increasing, fueled by the introduction of more and more regulations, by changing demand for new financial products, but also by the higher level of digitalization expected, if not demanded, by clients and advisors alike. It’s time for financial services companies to embrace this shift, and to start employing Artificial Intelligence technologies at every stage of the process to lead the sector into the future.

To this end, Natural Language Processing (NLP) in particular is the right solution for banks (and insurance companies), to tap into their textual data’s full potential to improve compliance, customer satisfaction, efficiency and productivity, while saving time and resources. 

To achieve these goals,, a leading company in AI-based natural language software, with more than 20 years of experience in Natural Language Understanding, has developed the first Hybrid AI Platform to empower processes by combining symbolic human-like comprehension with Machine Learning.
In fact, the platform leverages powerful technology to address even the most complex unstructured information management use cases with high accuracy and limited training, when compared to a traditional ML approach.

Fincons and improving businesses together

In the changing, complex financial and banking landscape, more and more institutions are considering introducing NLP technologies to automate processes, increasing productivity and reducing the risk of human errors. 

Leveraging their expertise in the field, and Fincons Group combined forces to offer a full range of on-premise, private and public cloud solutions, augmenting business operations, accelerating and scaling data science capabilities and simplifying AI adoption in the different scenarios described below.

NLP and data quality management 

The foundation of any application is the data upon which it is based, making data collection and data quality management critical to its success. 

Good quality data collection starts with onboarding, where NLP methods can be applied not only to the collection of new client data but also to help detect any omissions, inconsistencies or suspicious data that slips through, thus improving overall data quality. 

To further optimize and speed up the lengthy onboarding process, as well as loan origination and front and back-office processes, NLP empowers Intelligent Robotic Process Automation, that expands the scope by providing bots with additional data from complex documents that NLP can extract automatically.

Step into the future of customer care: NLP and Digital Customer Interaction

Customer experience is becoming increasingly digitalized across all industries, even in the banking sector, where customers have high expectations of their service providers. With the launch of AI-based new technologies such as ChatGPT, taking headlines by storm, is it clear that the financial services sector should immediately explore how AI can leverage its potential.

Natural Language Processing can help bring banks’ customer care to the next level, optimising self-service systems, chatbots and even email management, providing digital tailored solutions for customer satisfaction. In addition, NLP enables data analysis, identifying discrepancies or possible mistakes from data or documents provided by the customers before it’s too late, improving overall customer experience and compliance, ensuring a high-quality service at a sustainable operational cost.

NLP & anti-money laundering procedures: a perfect match

The financial services sector is one of the most regulated in the world, and anti-money laundering (AML) regulations are one of the biggest compliance challenges for banks.
Natural Language Processing can be applied to augment human-run tasks to better review legal documents, ensure compliance and evaluate the impact of new regulations on bank contracts and policies, consequently improving efficiency and productivity. 

NLP supporting compliance and legal departments

One important source of unstructured textual data are contracts. Legal and Compliance departments typically trawl through these manually to extract relevant information or flag potential issues. A small omission due to human error can end up costing the business huge amounts in both financial and reputational terms, if it landslides into a regulatory compliance error and a hefty fine.

NLP technology can help ease the burden on these departments by automatically identifying inconsistencies, missing information or errors in legal documents, contract and policy agreements. Problems are thus flagged early-on when it is possible to go back and rectify the issue.

Are you interested in evaluating how Natural Language Processing can help your company to increase productivity and reach your business goals?

Giuliano Altamura - Fincons Group Giuliano Altamura

Fincons Group

Global FSI BU General Manager and UK Country Manager

Andrea Ricotti - Author of the Fincons Blog Andrea Ricotti

VP Director EMEA – Channel Development