Natural Language Processing (NLP) and Finance

Natural Language Processing (NLP) and Finance

Text & NLP

Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves

Finance

Nowadays, data is driving finance and the most weighty piece of data can be found in written form in documents, texts, websites, forums, and so on. Finance professionals spend a considerable amount of time reading the analyst reports, financial press, etc. The automatic textual data processing can significantly decrease the amount of manual routine work and accelerate the trades.

NLP techniques and algorithms help to translate the raw textual data into meaningful insights across several areas in finance. Traders, portfolio managers, analysts, banks and other financial organizations strive to improve their financial analysis, and NLP and ML have become the technologies of choice. NLP is used across the financial industry, from retail banking to hedge fund investing. Such NLP techniques as sentiment analysis, question-answering (chatbots), document classification and topic clustering are used to work with unstructured financial data.

NLP and ML techniques can be used to design a financial infrastructure that can make informed decisions on a real-time basis. NLP can help with designing such systems that can enrich financial flows by tracking a company’s changing nature. For example, NLP can improve the operation of a bank as follows:

- Better personalized experience to customers
- Better equipped to deal with fraud and money laundering activities
- Improved operational efficiency
- Better compliance with policy norms
- New analytical insights
- Innovative product offerings

Eden AI

This use case can be handled with different engines offered by different providers on the market. To help companies discover and test these different engines, we have developed Eden AI, which provides a single, simple access to all these engines:

Screenshot - Eden AI Portal.png