4 Ways NLP Machine Learning Transforming Fintech Industry

The FinTech industry is disrupting the traditional financial institutions and the finance sector at a record pace. People no longer have to ...

The FinTech industry is disrupting the traditional financial institutions and the finance sector at a record pace. People no longer have to rely on physical checks and bonds for transactions. They can have their money right on the phone and send it across the world in an instant. With NLP Machine Learning, the FinTech Industry is transforming itself.

4 Ways NLP Machine Learning Transforming Fintech Industry

Machine Learning (ML) is the technology enabling machines to learn by continuously analyzing large quantities of data without requiring every function's programming. It is the primary mechanism behind Artificial Intelligence (AI) development. When applied to Natural Language Processing (NLP), it enables incredible innovations like voice-activated virtual assistants.

NLP-based machine learning has been growing over the years, and its potential is practically unlimited. It's estimated to grow to $35.1 Billion by 2026, from a market size of $11.6 Billion in 2020. 

1. A Natural Ally

Due to its technology-based evolution, FinTech benefits from any development that happens in the tech space. The features offered by NLP machine learning blend very well with FinTech's needs. Better user experience, security, ease of access, faster processing, etc., all result from the merging of these two technologies. It also offers rewards like:

2. Legal Document Management

Working in the finance world means dealing with plenty of legal aspects. Every FinTech company is bound to contain databases chock full of legal documents. Managing them in traditional ways is a time-consuming and tedious process that's prone to errors.

Machine learning-based AI can search and process documents efficiently. NLP brings in the ability to attach metadata to them. The search can go beyond keywords to incorporate broader search parameters. Digitized handwritten documents too can be analyzed and sorted.

3. Customer Service

NLP-based chatbots are replacing customer service agents in droves. These chatbots rely on machine learning to constantly analyze interactions and adapt to better understand and respond to a query. The NLP aspect of it also helps enquirers interact with them like they were speaking with a person.

Finance involves a lot of complexity and complaints that customer service agents have to deal with regularly. Add to those irate customers who demand to know why their transaction failed and what happens to their money. NLP-based chatbots can handle these with ease on a global, 24/7 basis, including in the language of customer's choice. 

It saves all of the company's resources, as human agents can be limited to dealing with only escalated cases that the bot can't handle. 

4. Insurance Underwriting Automation

Processing claims and selecting the most suitable policy for customers are painstaking tasks that insurance companies deal with all the time. Without automation, these tasks are resource-intensive, thereby, reducing productivity.

NLP-based solutions can clear the files in no time. It takes less than a minute for a chatbot to approve claims or ask some more pertinent questions to a client to select the best policy for them.

Complemented by machine learning, these solutions can work on more complex tasks like creditworthiness assessment of clients. They can scour the internet and find relevant information, including in places like their social media profiles.

FinTech is growing every day, and so are its challenges. NLP machine learning solutions are the best bet to meet those challenges and grow the industry altogether.