Narrowing the gap between Fintech companies and the traditional company frameworks is a work in progress. Fintech startup firms are engaged in "disintermediation via innovation" through Artificial intelligence, Machine Learning, Big Data, blockchain technology, Robo-advisors, and the Internet of Everything. Traditional financial organizations have the upper hand in providing services tailored to the needs of their customers, as a standard approach would not fit the objectives sought by every customer due to the extensive relationship formed over the years.

To further explain, Navaretti, Calzolari, & Pozzolo argue that since large institutions collect data from their consumers on a broad scale over time, some connections develop and certain risks are eliminated, allowing financial institutions to remain flexible to their customers' demands, hence creating certain bundles.

Financial service organizations, such as banks, insurance and reinsurance companies, aim to provide services promptly with the help of technology. Companies engaged in this sector, in particular, deal with savings, lending, investing, financing, financial markets, and different forms of insurance. Noticing any changes in the financial services business due to technology can be done by observing how banking was formerly conducted "offline" when all activities took place in person before everything moved online. One example would be how businesses used to provide physical handwritten checks but now electronically transfer their personnel paychecks.

According to the Bill and Melinda Gates Foundation, virtual application users will reach 2 billion in the banking industry alone by 2030. According to Klaus Schwab (2016), founder and executive chairman of the World Forum, the Fourth Industrial Revolution was developed on top of the Third Industrial Revolution, in which the digital process blurs the boundaries between physical, digital, and biological realms of technology.

An analysis

A paper published on the role of AI in the FinTech sector analyzed previous research to decipher the role and influence of artificial intelligence and machine learning in the financial services industry, and it contributes to a collection of related papers on the specialized topic of artificial intelligence in the financial industry.

The information was gathered through a background section and two structured tables highlighting the issues addressed by financial institutions using AI and ML and the top ten ranked institutions worldwide by their specialized business category, such as banking, insurance, and reinsurance, that are leveraging AI and ML to improve their service delivery and internal operations. Much of the data reviewed and acquired originated from research established in recent years as AI and ML became a more prominent subject of debate.

Result of Analysis

Due to the increase in suppliers, the Financial sector has shown great potential in implementing technology, particularly AI and ML. The nature of the data handled by financial service companies requires tools that handle big data. The business models of these financial institutions are soon to be completely digitized due to the pressure rising from Fintech companies and customer demands.

Unlike traditional financial services, Fintech companies can offer innovation and flexibility strengths to their clients through efficient and responsive processes. The nature of the data handled by financial service companies requires tools that handle big data. The business models of these financial institutions are soon to be completely digitized due to the pressure rising from Fintech companies and customer demands.

Unlike traditional financial services, Fintech companies can offer innovation and flexibility strengths to their clients through efficient and responsive processes.