There is a revolution undergoing in the financial sector. This sleeping giant pinned down by compliance regulations,and old practices are about to be awakened by artificial intelligence (AI). FinTech start-ups are getting more financing and delivering high-quality services to a millennial public who embraces the digital way of dealing with money.
The introduction of AI in this sector has been limited so far to high-frequency trading algorithms. Now, the technology is moving from SF to the main stream, bringing new applications such as personal finance management, risk management, fraud detection, and more.
1. Personal finance advice
The private financial consultant is no longer reserved for the rich, now there is an app for that. Called bionic advisory, these systems retrieve information from the client’s bank accounts, credit cards,and other relevant sources to create a spending profile. Once in place, the robot advisor gives the user hint and pertinent recommendations about managing their budget to hit some pre-set goals like paying in full the student loans or a credit card.
Another application of AI for advice is chatbots for financial institutions. The aim is to create deep learning algorithms that are so performant that they can replace call center workers. As most younger clients prefer to text and ask for help using a chat instead of calling and waiting, there are a consistent market and growth opportunities for such web apps.
2. Detecting and preventing fraud
The top concern in financial institutions is safety. The increase of online transactions, available platforms,andvendors, is a risk factor since not all of these players have proper encryption and transaction safety methods in place. This is where AI can become very helpful by learning about the clients’ patterns.
People are creatures of habit. We usually access our accounts from the same terminal, in the same geolocation and most of the times even around the same hours, operating with amounts in a specific range. If the algorithm sees that someone in a different country is accessing your account from a different device, aiming to move a significant value, that might be the indication of fraud.
3. Financial management
Companies have been using data to get ahead of competitors long before AI was available. Now it is just a matter of transferring a part of the process from the team of analysts to the software. The only risk is that most AI algorithms work as black boxes and the quality of the output is dictated by the availability of excellent input data.
The good news is that such tools are now available even to small companies at a reasonable price. The results these can offer are related to the client’s behaviors, spending patterns, the churn rate, and more.
4. Risk assessment & management
AI has the power to transform the current loan system. Not only it can create a more realistic valuation of the risk associated with each borrower, but it can take into consideration a much broader set of variables. What if you could add up to the FICO score other dimensions like your studies, your rent payment record? Maybe you would stand a better chance of getting a loan.
In fact, some companies already take this approach and have created millennial-friendly loan products. Yet, until this becomes the norm, there is always the option to fix your current score by asking the experts: https://creditrepaircompanies.com/.
5. Automation of processes
More generally, financial companies can look at AI as a way to free some time for their workers, both regarding repetitive tasks.
For example, scoring loan applications can be automated in a vast proportion, leaving underwriters to deal with those cases that require special attention, but only constitute 3-5% of the total. Such a process relies on the machine learning algorithm going through thousands of previously approved applications and learning the success criteria.
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