Fintech and NLP: Revolutionizing the Finance Sector
Artificial Intelligence (AI) and natural language processing (NLP) are becoming widespread in almost every industry from healthcare to legal and everywhere in between. NLP has made tremendous advances, and its use has expanded extensively inside the financial industry. In Fintech, NLP can be used for text examination and human responsiveness.
What is NLP?
NLP is an offshoot of AI that assists computers in understanding 'natural language' or human language. Every language has specific nuances that humans are used to catching, but aren't automatically assumed for computers/machines. Computers use programming language and need to be trained to understand nuances and grammatical etiquettes. Enter NLP.
NLP uses tools to understand the basic techniques of word definition, phrases, sentences, texts, and syntactic (knowledge of word meanings and vocabulary), and semantic processing (understanding the combination of terms). It also develops applications such as machine translation (MT), question-answering (QA), data retrieval, discussion, document production, and recommendation programming to name a few.
NLP and Fintech
People have developed high expectations of their banks, insurance companies, and credit unions. This is especially so since COVID-19, as more and more elements of the customer experience because digitized and people could expect more from the programs that helped them. People now expect easy tracking of real-time transactions, supervised management of their assets, and the opportunity to settle any issue online with genuine care. To make that a reality, financial services must be equipped with innovative technologies that demonstrate speed, intelligence, and autonomy.
AI gives machines human-like intelligence by enabling them to perform tasks akin to a superpowered human. This is achieved mainly by ML and NLP.
NLP in Fintech: Use Cases
NLP has two main use cases in Fintech: understanding the way humans speak and extract the meaning. In practice, this means recognizing intent and coming up with an appropriate action that corresponds to requests for help, claims, and so on. NLP helps turn unstructured data in databases and documents into structured data and extracting relevant insights through pattern recognition (text mining).
Here are a few use cases where AI and NLP are influencing the FinTech world:
- Evolving chatbots into virtual assistants and counselors.
- Enriching chatbots with advanced Big Data analytics.
- Making communication seamless and precise like a human communicator.
- Detecting fraud.
- Segregating customers into groups & improving relevant product offers.
- Minimizing administrative work and automating separate tasks and whole domains.
Customer Service
"Conversational banking" is a new concept, and it represents a drastic shift from simple chatbots to well-equipped digital assistants. To set yourself apart from the competition, invest in virtual assistants with advanced capabilities. They should be able to process context, analyze text sentiment, and perform predictive analysis. NLP helps chatbots with functionality, essentially helping them translate user queries into information that automated systems can use for appropriate responses. This can help with:
-Counseling consumers on bank account management.
-Sending an alert when approaching the spending limit.
-Flagging payments for anomaly detection.
InsurTech
Advanced specialists and NLP-based client support are the upcoming players in the worldwide protection market. Insurtech means to use technology innovations designed to bring out savings and efficiency from the current insurance industry model. Insurtech is a combination of the words "insurance" and "technology," influenced by the term fintech. Artificial intelligence is a big reason why Insurtech has become successful. Machine learning-powered applications can process the colossal amounts of data required to create improvements in efficiency and effectiveness. There are multiple applications for Insurtech within this sector: This includes personalized policies, more possibilities for small business policies, and customer-facing applications.
RegTech
RegTech technology is a tool used by financial institutions and FinTech firms to remove regulatory risk and minimize the costs of compliance issues. This is still in the making and has a very narrow spectrum, so it cannot be utilized commercially. This up and coming age of artificial intelligence instruments with NLP will include:
- Agreement survey. Performing a full-scale records audit takes a few seconds, which previously required 360,000 hours of routine work.
- Administrative examinations. It helps in detecting tax evasion, potential anti-money laundering (AML), and combating the financing of terrorism.
NLP and Fintech are constantly coming up with innovative solutions that help the financial sector create better policies and protect assets. Combined with machine learning, many financial processes can be fast-tracked, leaving humans to focus on more intricate matters. If you'd like to find out more about how NLP and data labeling can help your financial institution, contact us to set up a custom demo.
Want to learn more about how NLP is used in industry?
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