How Artificial Intelligence is Contributing to the Fintech Industry

How is AI resulting in the development of the Fintech Industry?

Fintech Industry

Fintech Industry

Fintech is one of the fastest-growing industries, getting stronger because of the rising number of internet users. There is a standard shift to mobile devices for performing financial transactions and related actions. Fintech is among the sectors that are getting stronger even with the heavy hit of economic disruptions caused by Covid-19. The financial sector is transforming with the world’s new reality through the use of Artificial Intelligence.

The Advancement of AI has redefined the operations performed by the financial sectors. Most of the financial activities are now performed via apps that can be operated through mobile phones as well. This is opening up great opportunities for the customers.


Here is the list of developments brought by AI in the Fintech industry.

Financial Advisor & Customer’s Credit Analysis 

AI helps the fintech industries in examining and analyzing credit accounts, cash accounts, and investments accounts to regulate and govern the client’s financial health. AI is used to create customized advice based on incoming data of new customers. Unlike traditional banking, today’s banking institutions can process a huge amount of information about their customers. 

In the fintech industry, transactional bots, one of the most popular applications of AI, provide financial coaching services. It can be considered as a digital assistant who helps in guiding the customers about their spending and savings and overall financial plan.


Process Control and Optimization

One of the most significant driving forces of AI in financial organizations is process automation. AI systems can perform complex automation processes. This technology allows scanning of documents, which not only intensifies accuracy but also lowers down the time taken to check regulations and rules in trade finance.

Process optimization is applied in a broad range of departments which include sales, call-centers, accounting, and training and development. Most of these processes are automated, which increases the institution’s overall productivity.


Fraud Detection and Prevention

In the financial sector, fraud has always been a constant problem. But with the evolution and development of AI, fintech industries are deploying predictive analytics into their fraud detection process. Machine Learning and Robotic Process Automation technologies are gaining importance in the fintech industry for identifying patterns that inform fraud-related cases.


Customer Support

Bots are one of the most famous tools of AI. The fintech industry implemented potent chatbots for the purpose of carrying out interactions with customers. Due to Covid-19 and lockdowns, financial institutions are taking advantage of AI chatbots to solve customer issues remotely.


Decision making

With the advancement of AI, customers can now make use of fintech applications that have data visualization tools. These tools can crack complex data into a simple form that can be understood even by ordinary citizens. This improves their financial decision-making. Without focusing on the recommendations given by human experts, managers are basing their decisions on machine-generated information. These machines can analyze data and provide the most feasible and practical recommendations.


Customer Risk Profiling 

For banks and insurance companies and all other fintech companies, categorizing customers based on their risk score is very complex and critical. Using AI technologies like Artificial Neural Network (ANN), the classification models can be trained with historical or pre-labeled data to rate the client profile from low to high.

Artificial intelligence (AI) technology is already developing the fintech industry to a large extent. According to a survey of 80 fintech by Tribe Payments, AI will deliver more impact on fintech development over the next five years, with the use of five emerging technologies: Application Programming Interfaces (APIs), blockchain, low code, and edge computing.