7 Ways AI is Set To Impact Financial Services in 2018

Finance has long driven artificial intelligence and machine learning

In fact, after World War II, governments around the world worked with private and public entities to develop sophisticated financial computer infrastructure to improve economies. This trend continues today, and artificial intelligence and machine learning are having a major impact on finance. Here are seven ways artificial intelligence is transforming financial services.

Making Sense of Big Data

Computers are excellent at capturing and storing information, and the low cost of storage means financial companies are storing more than ever before. However, making sense of this information is difficult, as humans struggle with especially large data sets. Artificial intelligence, especially when assisted by machine learning, is great at finding small signals within large data sets, and this information can be critical in fields as competitive as the financial industry.

Laws and Regulations

The financial industry is riddled with complex laws and regulations. Proper reporting is a mainstay of keeping companies compliant, and artificial intelligence can help automate the process. Furthermore, companies can use computer systems to ensure all parts of the business are operating within expected parameters, and detecting deviations from normal operations can let companies uncover potential problems and react accordingly. Specialty software can even supplement audits, both mandatory and optional, to ensure compliance.


Engaging Customers

For decades, people have complained about calling a customer service line and having to deal with an automated system. Old systems were clunky, and listening to seemingly countless menu options could be incredibly frustrating, especially for performing less common tasks. However, AI is revolutionizing these interfaces, especially when used through web browsers and on smartphones. Sophisticated language parsing enables today’s virtual custom service bots to provide real value, and more realistic text-to-voice systems making phone systems friendlier. In fact, some people prefer computer-based customer service systems if they can sufficient replace humans.

Customer-Facing Artificial Intelligence

Artificial intelligence research in the financial industry often deals with servers. However, companies are also investing in technology used on customer-facing devices. Smartphones, for example, are increasingly being used as personal assistants, and financial advice through a smartphone can provide an excellent way for customers to improve their financial habits. A personal assistant can help customers make wiser decisions with their money, but the industry as a whole benefits as well. Better customer reliability leads to more stable business, and programs that encourage more rationality can help create a stronger economy.

Counterintuitive Decisions

Economics is based on the assumption that individuals and organizations tend toward making optimal decisions, but the field itself is keenly aware that irrationality is rife. Because of this, assumptions that rely on rational behavior often fail to provide realistic results. Artificial intelligence and machine learning can analyze data without assuming all decisions will be made rationally, and this can lead to counterintuitive information that no human would be able to discover. Accounting for uncertainty and irrationality is essential for maximizing financial systems, and more sophisticated computer analysis will lead to financial models that better represent the real world.

Detecting Fraud

Perpetrators of fraud are smart, and many produce paper trails that look legitimate to human eyes. Artificial intelligence, on the other hand, can look for signs humans wouldn’t. Through artificial intelligence, financial entities can detect suspicious activity early on and investigate, potentially preventing expensive fraudulent transactions. Copycats are common when it comes to fraud, and machine learning can provide a powerful means of preventing future fraudulent activity. If used regularly, these tools can deter would-be fraudsters in the future, making the financial industry as a whole more stable.

Trading Algorithms

Sophisticated trading algorithms already rule the world’s markets, and the speed with which computer systems have transformed stock trading is staggering. Although automation reigns in the trading world, even the most complex algorithms stick to basic artificial intelligence reasoning. The rise of machine learning is poised to change the norm by placing an emphasis on making decisions based more on hard data and less on trading theory. Over time, these systems can train themselves to become more efficient and to better detect tiny signals that represent an opportunity for better optimization.

Finance, for better or worse, is at the core of the world’s economy. While humans will always play a role, especially in terms of regulation and for making major decisions, more and more financial transactions and decisions are making their way to computer systems. This, combined with the highly competitive nature of the field, means investment in artificial intelligence and machine learning will be one of the most defining elements of the field. Fortunately, these technologies have the potential to stabilize, not disrupt, the financial industry, which can lead to better job stability and even reduce the likelihood of market crashes.