By Kevin Smallen, Chief Information Security Officer, PenChecks Trust®
Artificial Intelligence (AI) is a rapidly growing field with the potential to revolutionize the financial services industry. In recent years, AI has been used extensively in financial services to improve the customer experience, streamline operations, and identify fraud. It transforms the financial services industry in many ways, enabling faster data processing and more accurate market trend predictions. However, using AI in finance is not without its harmful effects, which can have significant consequences for businesses and consumers. This blog will discuss the positives and negatives of this game-changing technology.
AI’s Positive Impact on the Financial Services Industry
Financial services companies have much to gain from using AI technology.
- Improved Customer Experience. One of the most significant impacts of AI in the financial services industry is improved customer experience. AI-powered chatbots and virtual assistants have become increasingly popular in recent years as they provide customers with a 24/7 support system. These chatbots can answer customer inquiries, provide personalized recommendations, and even help customers complete transactions. AI-powered customer service systems can also analyze customer data to identify patterns and trends, which can be used to improve products and services. For example, AI can help financial institutions personalize their marketing campaigns by analyzing customer data to identify specific customer needs and preferences.
- Operational Efficiency. AI-powered systems improve operational efficiency by automating many tasks, such as document processing and data entry, which can reduce the need for manual labor. This can lead to cost savings for financial institutions and allow employees to focus on higher-value tasks. AI can also optimize business processes like loan approvals and risk management. AI-powered risk management systems can analyze large amounts of data to identify potential risks and make recommendations to mitigate them.
- Fraud Detection. AI-powered fraud detection systems are becoming increasingly popular due to their ability to analyze customer data, identify potentially fraudulent activities, and alert financial institutions to act. This can help prevent fraud and reduce losses for financial institutions.
- Investment Management. AI-powered systems improve investment management by analyzing large amounts of data, identifying investment opportunities, and making recommendations based on historical trends and current market conditions. This can help financial institutions make more informed investment decisions and potentially increase returns.
- Regulatory Compliance. Regulatory compliance is a significant concern for financial institutions. AI-powered systems can analyze large amounts of data to ensure financial institutions comply with regulations and identify potential issues before they become problems.
The Negatives of Artificial Intelligence
Financial services firms need to keep a close watch on the potential downsides to using AI in their businesses.
- Job Losses. One of AI’s most significant adverse effects is causing job losses. With the increasing use of AI in finance, many jobs previously performed by humans, such as data entry, analysis, and customer service, are becoming automated. This can lead to a significant decrease in employment opportunities for people who previously worked in these roles.
- Lack of Human Interaction. AI can also have an adverse effect on human interaction. Many customers prefer to speak to a human when they have a financial query or problem. However, the increasing use of AI means they can only interact with a machine, which can frustrate customers and reduce customer satisfaction.
- Bias and Discrimination. AI systems can perpetuate prejudice and discrimination in the financial services industry because their algorithms are only as unbiased as the data they are trained on. If the data contains biases or discriminatory patterns, the AI system will replicate them, leading to unfair outcomes for certain groups of people.
- Over-Reliance on AI. Becoming too dependent on AI can lead to adverse outcomes. While AI can provide valuable insights and predictions, keep in mind that it is only a tool. Over-reliance can lead to a lack of critical thinking and analysis, which can be detrimental to decision-making.
- Cybersecurity Risks. As with any technology operating on computer networks, AI systems are vulnerable to hacking and cyber-attacks. Theft of sensitive financial information can have severe consequences for businesses and consumers, including financial loss and damage to reputation.
Handle AI With Care
AI is having a significant impact on the financial services industry, improving customer experience, operational efficiency, fraud detection, investment management, and regulatory compliance. As AI technology continues to develop, we will likely see even more significant impacts in the future. Financial institutions that adopt AI technology will be better equipped to meet the needs of their customers and remain competitive in the industry. However, while AI has the potential to revolutionize the financial services industry, we need to remain vigilant to the adverse effects it can have, especially over-reliance on AI and cybersecurity risks. As long as we stay aware of the risks and take steps to mitigate them, AI’s will benefit financial industry customers and the businesses that serve them.
Kevin Smallen MS, CISSP, ITIL-F is PenChecks Trust’s Chief Information Security Officer with more than three decades of experience in the Information Technology and Data Security field. Roles in systems engineering/architecture and technical management have enabled him to become a well-rounded information security specialist. Kevin holds a Master of Science in Cybersecurity from Liberty University and continues to approach cybersecurity objectives with Confidentiality, Integrity, and Availability (CIA) as the main tenants of how an organization handles data when it is stored, transmitted, and processed.