While many people are wont to think of artificial intelligence (AI) and machine learning (ML) as the stuff of futuristic science fiction and films with dystopian themes, AI and ML in this day and age are actually being used as a force of good. They are technologies that afford numerous industries with benefits many of which wouldn’t even be possible if we only ever relied on antiquated or traditional technologies.
One important sector in which artificial intelligence and machine learning are being put to good use is financial services, where they are employed to carry out tasks in order to save time, trim down costs, and bring added value. Because banks and other financial institutions sit on the intersection of an extraordinary stream of information, they can make the data stream more powerful by deploying an intelligence framework against it. This affords financial institutions to a number of advantages, from streamlining their operations and meeting customer needs more efficiently to managing regulatory risks better and deal with financial fraud more effectively.
In order for you to better understand the benefits of AI and machine learning, we’ll explore the following areas in which they are proving to be of advantage for the world’s financial institutions.
Fraud Discovery and Prevention
Financial fraud comes in many variants, from cheque and credit card fraud to and securities and general bank fraud. While financial criminals that commit fraudulent activities have become more sophisticated in recent years, artificial intelligence and machine learning technologies have also been playing an increasing role in minimizing the losses of victims.
The algorithms used by these technologies may vary depending on the developer, the financial institutions that use them, and the tasks for which they are deployed, but fraud detection systems typically work on the same basic principles. These include studying and learning about the individual actions of users, decide on which behavioral patterns may be considered nonstandard or irregular, and determining specific situations when an action should be flagged for possible fraud. Because almost everything is automated in this set-up, financial institutions are able to lose no time in discovering and apprehending culprits.
Anti-Money Laundering
Another insidious financial crime that many financial institutions struggle with is money laundering, which is especially dangerous due to its connection to more nefarious criminal activities like drug trafficking and terrorist financing.
Anti-money laundering AI and ML software work in much the same way as software meant to detect fraud in that the former finds subtle patterns that may be hidden across multiple types and layers of data. With help from subject matter experts, anti-money laundering technologies can make the determination of the rules or scenarios that should trigger an investigation of an individual or a group of users, who may be laundering dirty money by letting it run through legitimate financial channels.
Automating Tasks
Many of the tasks that banks and financial institutions previously accomplished only via manual transactions, reviews, and extrapolations can now be automated with the help of artificial intelligence technologies. For example, AI software can now use image recognition technologies to analyze digital documents, as well as chatbots to conduct conversations with customers through auditory or textual methodologies. These techniques can help financial institutions save money, time, and resources.
Creating Better Customer Experiences
In the near future, many activities within the financial services umbrella, including banking, investments, trading, and lending will be increasingly aided by artificial intelligence and machine learning technologies. These technologies will be used to generate better insights, provide better risk assessments, and develop more personalized financial products and services—all of which are aimed to improve customer experiences.
Among the many technologies developed in the digital age, artificial intelligence and machine learning technologies may be the most significant and may have the most far-reaching effects. In the realm of financial services, their benefits are only beginning to become apparent.
