AI Became the Front-Runner of Fintech – What Should People Expect?

AI became the front-runner of Fintech 3

The financial industry is among the few ones that adopted technology advancements immediately after they emerged on the market. Finance companies are the ones that took advantage of the capabilities of a computer first, and they eagerly waited for the next changes that were about to make their jobs easier and error-free. In time, finance companies that made use of technology for most of their activities earned the name Fintech. People all over the world know this sector as one that is highly technologized and solves human problems the fastest, showing a maximum level of efficiency.

Since inorganic intelligence became one of the hot topics of the century, there’s no wonder why Fintech companies started focusing on it and the benefits it may bring to this industry. Artificial Intelligence is now a reality and is stronger than ever. It combines the best aspects of human, organic intelligence with the positive aspects of technology. The obtained result goes beyond human abilities and has the capacity to revolutionize not only Fintech but also other industries that require automation. Fintech is now making great use of AI, Machine Learning, Neural Networks and complex programming algorithms that take years and years to make.

Before technology influenced the Fintech sector so much, bank employees had to have tremendous knowledge in this field in order to properly assist clients with their financial decisions. The digital world changed how things were handled, offering finance employees the chance to use AI and Machine Learning to handle the huge amounts of data that went through their hands. Of course, this led to a visible increase in the customer satisfaction level, as well as a reduction of human errors. As for trends in Fintech and how AI changes it, keep reading.

Making better decisions

Fintech companies rely on analyzing data and using it so that they make wiser financial decisions. This change led to modifying the way financial institutions manage everything. Fintech companies and banks don’t have the best connection because of the discrepancies that separate them. Banks made a few steps forward in terms of technology by adopting some features which make the life of their users easier. Internet banking is a mainstream service today while using AI to make better decisions is still questioned by many people.

Luckily, the trend that is most likely to dominate the coming years has to do with relying on data-driven management to make financial decisions and save money in the long run. Today’s machines can become better than banking agents at asking questions and personalizing the financial services that a person receives. Human experts will soon become unimportant in the Fintech industry, which is both an advantage and a downside.

Frauds can be detected easier

Banking still has to face the risk of fraud, while Fintech seems to be a happier case due to AI and machine learning. Artificial Intelligence tools are directed towards finding patterns that look abnormal and give Fintech companies signs if these patterns might trigger a fraud attempt. Using AI to improve security measures is a trend that is still under development, but people should expect to notice advancements in how techniques are applied in future years.

Both leveraging AI and using large amounts of data can help with finding and stopping fraudulent attempts that are directed towards Fintech companies. Because Fintech relies more and more on the use of technology, people started to worry about the possibility of cyber attacks. Considering the lack of trust that some people manifest towards the Fintech sector and how they handle data and money, Fintech companies make bigger investments in protecting their systems from frauds, most of them containing AI or Machine Learning technology.

Predictive analysis saves the day

To analyze data, human employees spend hours or even days to put readable reports together. With the emerge of AI technology, as well as Machine Learning algorithms, that is no longer required. Programs such as Timesheet Portal became the norm in handling data and generating automated reports or invoices. Most companies learned or are currently learning more about how to handle their data efficiently and reduce the time resources involved in organizing it. Fintech companies sorted this problem out a few years ago when they entirely placed their trust in the use of technology and the impressive benefits it comes with.

Predictive analysis proved to be essential for Fintech businesses and not only. It helps with generating considerable revenues, optimizing resources better, nurturing sales and the list doesn’t stop there. The benefits of predictive analysis are present on both sides – one has to do with Fintech companies and the other is represented by customers who are unhappy with bank services and the security they provide. Revealing what will happen next based on data that was gathered in the past is an opportunity that Fintech companies should take full advantage of. Improving predictive analysis represents another trend that won’t disappear any sooner.

Some processes become a breeze

AI systems can also help with automating the underwriting process in Fintech companies. Using unpolished information is a lengthy process that would take a human employee’s hours and hours. Virtual assistants that use AI to function, on the other hand, can automate the process which can be reduced to just a few minutes. Virtual financial assistants can also deal with repetitive tasks that require attention such as monitoring stock and bond price trends or user data. AI assistants can personalize their services according to the needs and financial history of a customer, a capability that couldn’t be achieved by human employees.

Financial robo-advisors are popular among Fintech giants and startups seem to be adopting them as well to make the process more rapid and error-free. The rise of synthetic identity in Fintech has more benefits than disadvantages, and its use doesn’t seem to stop here. Most industry experts stated that they are planning to adapt AI and Machine Learning in one way or another before the year 2020.

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