by Apoorva Bellapu
February 5, 2022
If there’s one technology that has transformed our lives for the better and holds immense potential in the years to come, then it has to be Natural Language Processing (NLP). The extent to which organizations have benefitted as a result of NLP cannot be put into words. Out of the many industries that NLP caters to, the financial sector seems to be impacted like no other. On that note, have a look at 10 ways NLP is impacting the financial sector in 2022.
Better lending decisions
NLP has played a pivotal role in allowing organizations to make better lending decisions. NLP analyses bank statements, pay stubs, tax documents, mortgage forms, invoices, etc. to determine credit lending eligibility.
Compliance
Natural Language Processing can be used to support compliance processes of the banks and other financial institutions. NLP facilitates searching across thousands of digital documents, thereby allowing compliance officers to swiftly determine whether regulations have been followed.
Underwriting intelligence
NLP stands the potential to connect unstructured and structured data, followed by smartly transforming the data, learning from each interaction, and thereby offering contextual underwriting intelligence.
Tracking relationships
The finance industry is associated with analyzing earnings calls to establish the main theme, or to compare against previous, similar calls to identify trends. This is where NLP comes into the picture. It can be used to link entities and build a graph of relationships. This further helps in detecting money laundering and/or fraud.
Risk management
Natural language processing has served to be a blessing when it comes to creating more exacting, nimble models for the protection of businesses. These models can pinpoint trends, identify risks, conserve manpower and ensure better information for future planning.
Answers to complex financial questions
NLP has made it to the headlines for its ability to answer complex financial questions. It does this with the help of cloud computing. This NLP application is widely used – so much so that global institutions like J.P. Morgan, Bank of America, Morgan Stanley, and S&P Global rely on it.
Accounting and auditing
Today, we have reached a stage where companies across the globe have realized how crucial NLP is when it comes to gaining a significant advantage in the audit process. With NLP in place, finance professionals can directly identify, focus, and visualize anomalies in day-to-day transactions.
Predicting stock behaviour
Considering how irregular and fluctuating stock prices are, it is quite obvious that the long-term and seasonal variations can cause large errors in the analysis. However, a combination of NLP and deep learning outmatches previous methodologies working with financial time series to a great extent.
Sentiment analysis
The financial industry has a lot to do with reviewing unstructured content about a particular company to look for inconsistencies and anomalies. NLP is no less than a savior here as it can identify potential signals of equity performance from thousands of research reports and company transcripts.
Identifying trends in the financial markets
NLP stands the potential to analyse keyword searches within filings, transcripts, research, and news to discover changes and trends in financial markets. Well, can anything get better than this?
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