Managing finances in this well-connected and materialistic world can be a challenging task for so many of us. As we look further into the future we can see Artificial Intelligence helping us to manage our finances. AI has already proven its capabilities in different sectors and has already been used in Fintech for high frequency trading since the late 80s, however new applications are emerging. These include personalised financial advice, fraud detection mechanisms, investment decisions and blockchain.
The Capabilities of Artificial Intelligence
Artificial Intelligence seems like the perfect tool for the financial market as it can be used to forecast vital trading decisions. Financial success depends heavily on predicting where the market is heading. AI is predictive by nature and it can analyse mass data sets with incredible speed and accuracy. Therefore it is not difficult to see why businesses in the sector have been quick to adopt AI and machine learning.
In the last couple of years, financial trade has seen the rise of administrative AI, from AI customer services to now AI-powered hedge, funds aiming to provide alternative investment while generating the highest returns regardless of market fluctuations. Even with AI, this can still be risky but it’s clear why AI is so valuable when it comes to maximising potential gain, especially when it can gather so much information about the financial climate and simulate risk scenarios.
AI to make financial decisions and how will AI disrupt financial trading
Trading: from high-frequency to high-intelligence
The work basic statisticians building trading algorithms – will be replaced at some point with the work of a neural network, constructing new trading patterns based on previous experiences. Currently, the strife is to program predictive capabilities into these systems to make them ready for a change before it happens in the market.
AI is handy as a wise personal assistant. Financial institutions can require programmers to design algorithms that use the client’s data to track spending habits and make recommendations. Having your own personal robot-advisor is a service a lot of careless credit card users may value. Balancing your budget based on your behavior is a service that was unavailable at traditional banks, but could improve credit scores significantly.
The AI should be able to detect if this is a real threat or a one of a kind situation by correlating other readily available information about the client, such as an airfare ticket purchase or even geo-locating the clients. Cognitive technologies could be of great use in fraud detection due to their ability to detect patterns in raw data, a task that would take months for a forensic team could mean seconds for a clustering tool. Another excellent feature of fraud detection using AI is that the system has no qualms about learning. If it raises a red flag for a regular transaction and a human being corrects that, the system can learn from the experience and make even more sophisticated decisions about what can be considered fraud and what cannot. Decision-making & risk management
Futurists paint a scary picture of computers running the world on their own terms. Before this is the case, the algorithms should be able to take rational decisions in all situations, in a similar way to people. One of the financial tasks requiring sound judgment is creating better investment portfolios, where studies show that neural networks surpass conventional methods.
The Future of AI in Fintech
Even legislative changes are encouraging Fintech development. This legal framework will ensure both a universal compliance standard, secure payments and more data available to clients. There is a clear advancement towards using more technology in the financial sector, not only to increase productivity but to create a more personal relationship with the customer.