Finance institutions are using Natural Language Processing (NLP) to analyse performance drivers and predict market trends, which is revolutionising the financial sector.

When it comes to market research, content evaluation, and risk management, NLP is quickening the speed of change in the financial sector. Demand for BERT (Bidirectional Encoder Representations from Transformers) NLP is rising among financial institutions. BERT is an open-source NLP machine learning framework. The purpose of BERT is to provide context to assist computers understand confusing terms in text. This reflects the growing popularity of NLP in the financial services industry.

In today’s financial world, data and information are becoming more important than ever before. With the help of NLP, financial firms around the world can gain a significant advantage by analysing vast amounts of text and words. This presents a great opportunity for growth and success in the industry.  

Overview of Natural Language Processing

The Bank of America is embracing natural language processing technology to stay competitive in the market! The use of natural language processing by other banks, such as HSBC, to improve processes and gather market data is becoming more widespread.

COIN, a piece of machine learning software developed by JPMorgan Chase, would supposedly aid the bank’s legal departments in their assessment of thousands of legal papers via natural language processing.

So, What’s the big deal about NLP in the finance industry? The Answer is Simple because the recovery of data from the kinds of unstructured sources that financial organisations often struggle to mine is now easy. 

Benefits of Using Natural Language Processing in Financial Services

Finance and insurance firms utilise NLP to lessen the amount of routine, error-prone tasks that employees must do every day. It has a significant effect on both the efficiency with which applications are processed and the friendliness with which customers are treated. So, what other applications make NLP in the finance industry more beneficial?

• NLP helps to undertake investment analysis, which entails compiling summaries of market knowledge to get a better understanding of the market. 
• ESG evaluations are another way in which financial organisations might utilise NLP to evaluate the competitive landscape. Investors often use ESG ratings as a guide when deciding which businesses to put their money into.
• NLP may also be employed to guarantee compliance with regulations. Companies may analyse business data and identify particular key terms using text categorization and NER (Named Entity Recognition) to see whether its traders are in compliance with applicable laws and regulations.
• NLP can identify illicit transactions and scams, which are costly for financial organisations. The company may then employ text mining and NER to flag terms related to fraudulent conduct after using OCR to put the raw information into an acceptable form. 
• NLP tools help manage risk throughout a financial institution by highlighting potential trouble spots. This lessens the potential for financial harm even more.

What NLP Means for the Future of Finance?

Financial institutions in the Post-COVID era rely on data produced by NLP systems for market analysis and risk assessment. Bank executives are using NLP systems to assess the impact of the epidemic on their businesses and make informed decisions.

By 2023, financial institutions are expected to save a total of 862 million hours owing to the use of AI-powered chatbots, making the investment and adoption of AI-related fintech apps an easy decision. The more at ease customers are with utilising conversational technology, the more time, money, and effort may be saved for everyone concerned.

The worldwide NLP market has been worth $9.2 billion and a survey by Quince Market Insights projects that this number will increase by 18.4 percent between 2020 and 2028. Therefore, the coming decade will see tremendous advances in the practical applications of natural language processing, and financial services are expected to be a major contributor to this expansion.