The financial sector has gone through a host of positive changes since it was introduced to artificial intelligence (AI) and has incorporated it into its daily operations. Many organisations use AI in their daily activities to benefit from all the advantages it has to offer.
These benefits include increased effectiveness and better security among other things. According to Forbes, the leading adopters of artificial intelligence and machine learning systems in the financial sector are investment banking firms, followed by retail. Other industries that have adopted the use of AI are healthcare, agriculture, legal, and entertainment. Let us look at the uses of AI in finance in greater detail.
Money Laundering and Fraud Detection, Management and Prevention
AI algorithms go through transactions detecting patterns. Through these patterns, AI can separate normal activities from those that are not. This is how it can detect potential money laundering activities, credit card fraud, or other fraudulent activities.
Through the use of Machine Learning (ML), AI can establish baseline behaviour which it will use to search for anomalies and detect irregular financial activities. This analysis will help businesses take appropriate measures against the suspected illegal activities.
Some industries have adopted AI to support fraud detection and anti-money laundering efforts. Let’s explore those now:
Online Casinos
Online casinos, especially real money casinos, are potential victims of money laundering and fraud; therefore, the use of AI to fight fraud and money laundering is a huge benefit for both the player and the platform provider. Gaming enthusiasts who play at online casinos for real money need some form of assurance that their money and financial information are safe, and AI tech offers this reassurance.
Cryptocurrency Exchanges
Crypto exchanges use AI to monitor their networks for any out-of-place activities to prevent fraudulent activities that include money laundering. The algorithms analyse transaction patterns, identify suspicious behaviour, and comply with regulatory requirements for anti-money laundering in the cryptocurrency space.
Insurance
The insurance industry uses AI to prevent fraudulent claims. Machine learning models analyse claim data, looking for inconsistencies and patterns that might point to potential fraud. This helps insurance companies reduce losses and maintain the fairness of their claims processes.
Risk Assessment and Management
Financial institutions can assess if an individual or company is creditworthy by using AI technologies. They can evaluate the risk associated with lending decisions by analysing things like credit history, income, and market factors.
Banks are an example of a financial institution that uses machine learning to see if a person can be given a loan they will be able to pay back in time. Once a financial risk is identified, the bank or financial institution can take measures to prevent losses.
Customer Service and Support
Most financial institutions have gone digital, meaning that the majority of their services can now be done online – without the need to visit the physical banking building. Sometimes, in these businesses, there are no dedicated customer service employees to attend to customer queries and inquiries in real-time. Artificial intelligence fills in this gap by using virtual assistants and chatbots, which can attend to customers all day and night. Thanks to the use of Natural Language Processing (NLP), virtual assistants and chatbots can understand and respond to user inquiries effectively.
Personal Recommendations
By analysing customer data, including transaction history, buying trends, or frequented sites, AI can recommend financial products to customers such as investment opportunities and banking offers. These tailor-made recommendations help in saving time and improving efficiency.
Ethical Challenges Associated With AI
Although AI is a great tool to use in a business environment, there are some ethical dilemmas that have been raised in relation to Artificial intelligence and its usage. These include bias, unjustified actions, discrimination, and moral responsibility. Normally violation of personal data is used in reference to the unethical use of AI since it is difficult to maintain a person’s privacy while gathering valuable perceptions from data that is related to them.
The Future of AI in Finance
The world cannot ignore the progress that has come about due to the use of AI. More and more companies will continue to integrate the use of AI in their businesses if they want to remain competitive. Because of this, companies will pay more attention to understanding how using AI in their business processes can improve their overall performance. The use of AI should be safe and responsible.
Conclusion
Using AI in finance has transformed the industry for the better, making it more efficient. The adoption of this technology has seen it being used in areas such as risk assessment, risk management, and customer service and support. However ethical considerations are necessary to maintain a balance between responsible use and innovation.
