Financial services were one of the first industries to see the potential of the Big Data revolution and the wave of new technology that has accompanied it – including AI. AI is a powerful technology that is already being used extensively in the financial services industry. It has a lot of potentials to make a big difference if firms use it with enough caution, wisdom, and care.

Artificial intelligence (AI) is on its way to becoming mainstream in the financial services industry shortly. FinTech firms are more likely to utilize AI to develop new goods and services, whereas incumbents are more likely to improve current ones. An increasing number of FinTechs are approaching AI deployment from a product standpoint, offering AI-enabled services as a service.

Artificial Intelligence saves lives, and this is not a metaphor. Doctors use AI to give the most excellent care to their patients, from robotic operations to virtual nursing assistants and patient monitoring. Image analysis and different administrative duties such as filing and charting assist in lowering the expense of expensive human labor, allowing medical professionals to spend more time with patients. Even in historically conservative industries, the development of AI in financial services demonstrates how fast technology is altering the corporate environment. Here are a few of the most well-known AI in finance instances.

Credit Decisions

Credit reigns supreme. According to recent research, 77 percent of customers prefer to pay using a debit or credit card, while only 12 percent choose cash. Consumers value credit availability for various reasons, not the least of which is better payment choices.

Having strong credit may help you get better financing, obtain a job, and rent an apartment, to mention a few things. With so many life essentials reliant on credit history, the loan and card approval procedure is more vital than ever.

Artificial intelligence solutions assist banks and credit lenders in making better underwriting choices by including a range of criteria that more properly analyze historically disadvantaged customers, such as millennials, in the credit decision-making process.

Managing Risk

In the world of finance, time is money, but if the risk is not managed correctly, it may be fatal. Accurate forecasting projections are critical to many organizations’ speed and security.

Machine learning, a type of artificial intelligence, is increasingly used in financial markets to build more precise, agile models. These forecasts aid financial specialists in identifying trends, identifying dangers, conserving personnel, and ensuring better data for future planning.

Quantitative Trading

Quantitative trading is the practice of identifying patterns in massive data sets to make strategic bets. In this sort of trade, AI is very beneficial.

AI-powered machines can process large, complex data sets quicker and more efficiently than humans. The algorithmic trading procedures result in automate deals and save time.

Personalized Banking

With today’s digitally aware consumers, traditional banking isn’t cutting it. AI assistants, like chatbots, utilize natural language processing to provide tailored financial advice and deliver immediate, self-help consumer support.

Cybersecurity & Fraud Detection

Users shift money, pay bills, deposit checks, trade stocks, and more via online accounts and smartphone applications every day, resulting in massive amounts of digital transactions.

Any bank or financial institution must now increase its cybersecurity and fraud detection efforts, and AI is playing a significant role in strengthening online banking security.

Process Automation

Forward-thinking When it comes to cutting operational expenses and increasing production, industry leaders turn to robotic process automation.

Intelligent character recognition allows for automating several boring, time-consuming operations that formerly required thousands of hours of labor and inflated payrolls. Software using artificial intelligence checks data and creates reports based on the criteria set, examines documents, and pulls information from forms (applications, agreements, etc.).

Robotic process automation for high-frequency repetitive activities minimizes the possibility of human mistakes, allowing AI in financial services to refocus staff resources on procedures that require human interaction.

Conclusion

As we can see, the advantages of AI in financial services are many and difficult to overlook. As per Forbes, 65 percent of senior financial executives believe AI will positively influence the financial services business.

However, as of late 2018, just a third of businesses had begun integrating AI into their operations. Many people still err on the side of caution, fearful of the time and money it would take to deploy AI in financial services, and there will be obstacles. However, one cannot avoid technological development indefinitely, and avoiding it now may be more expensive.

So, if you are looking to automate your financial services using AI, Contact the ONPASSIVE team to know more.