Today, Fintech appears to be one of the world’s leading industries thanks to the increasing number of internet users. Users find it much easier and faster to make their financial transaction through mobiles than traditional means of transactions.
Fintech owes its success to multiple technologies that pave for the industry to become successful, scalable, fast, and secure. One of these remarkable technologies is Artificial Intelligence (AI)
Artificial Intelligence refers to the human simulation in machines specifically programmed to think and act like humans. However, the question is how these machines are helping the fintech industry?
This article will help you learn about how artificial intelligence is helping fintech grow and bring a difference. Let’s discuss in detail how AI is an ally for your fintech idea.
Your Digital Financial Advisor
One of the most famous applications of AI is transactional bots. They have become your digital financial coaches and advisors and are guiding users regarding their savings, spending. And other financial plans. By setting up a digital assistant for customers in finance, you can help enhance the overall engagement and experience for your customers. For that purpose, Natural Language Processing (NLP) and Machine Learning (ML) and other subdivisions of artificial intelligence help a lot.
Detection and Prevention of Fraud
With the integration of in-app transactions in applications like WhatsApp, the chances of unauthorized transactions and frauds have increased. Therefore, the incorporation of artificial intelligence in the fintech market has developed.
Robotic Process Automation and Machine Learning technologies have gained higher traction in the industry to detect patterns informing about frauds. For instance, the insurance industry can depend on AI to identify claims that are fraudulent as these algorithms and analyzers keep an eye out for details that humans can easily miss.
Algorithmic Trading
A pre-programmed set of instructions is used to analyze the data and make well-informed decisions, and the process is much faster than humans. For that purpose, Machine Learning appears to be the most flexible AI technology.
Machine Learning models carry huge data for training models. It can be historical or current market data. The more the amount of data is present, the better and easier it would be to make decisions. The most notable use cases of artificial intelligence in this industry are detecting data patterns using these algorithms that are much faster than any human can do.
Claim Processing
Consumerization refers to the impact cast by consumer-oriented technologies on businesses. By leveraging the advantages of consumerization, it has become easier for businesses to invest in consumer-centric platforms to target their customers and engage with them at platforms where the users spend most of their time. One of the most common examples of this is an artificial intelligence-powered chatbot.
Claim processing is the most tedious and difficult task to be done by insurance companies. It uses the standard procedure to determine the problems of customers, such as accidents, sickness, etc., analyzes genuineness of cases, and activates the claiming process. This cycle is not only time consuming but complicated as well.
Risk Profiling
For businesses belonging to the finance sector, such as investment companies and banks, the most critical operation is client profiling based on their risk score. In order to categorize clients on the basis of risk associating with their profiles, they need AI. Using technologies like Artificial Neural Network (ANN), training of classification models is easier using pre-labelled or historical data for rating the client profile lower to higher.
