How Artificial Intelligence and Technology Is Changing the Finance Industry

Financial institutions must adopt emerging technologies like those evolving from artificial intelligence (AI) to stay relevant and competitive. Finance has long been inseparable from new technologies, from the abacus to filing cabinets to spreadsheets. This intersection between finance and technology has evolved into its own industry in contemporary times: fintech.

The academic study of finance must also keep ahead of the tech curve. Reflecting this, the online Master of Business Administration with a concentration in Finance program from Murray State University emphasizes the study of business analytics. Business analytics fuses the power of AI-driven data science, analytics and visualization technologies with the critical analytical thought needed to take data-informed, decisive action.

Here are a few of the many ways modern technologies like those employed in business analytics are changing the field of finance:

Embracing AI as an Underlying Technology

Machine learning (ML), deep learning, neural networks and natural language processing (NLP) are examples of AI technologies that we knowingly or unknowingly use every day.

AI is integral to the many technologies disrupting, impacting and driving change in the finance industry. Fintech startups, agile, online financial companies and tech giants entering the finance sector have been quick to leverage the potential of AI technologies. McKinsey & Company addresses the need for this in stark terms, stating:

“To compete successfully and thrive, incumbent banks must become ‘AI-first’ institutions, adopting AI technologies as the foundation for new value propositions and distinctive customer experiences.”

McKinsey further explains that advanced AI can “improve upon human decision making in terms of both speed and accuracy.” The predictive and prescriptive analysis advanced AI can offer insight into financial forecasts, trends and investment opportunities. This insight informs effective data-driven decision-making in investment activities amidst turbulent markets.

AI for Robotic Process Automation

Technologies like optical character recognition, screen scraping software, ML and NLP have enabled increasing automation of repetitive, mundane finance tasks, known as robotic process automation (RPA).

According to Capacity, RPA can “automate repeatable, high-volume workflow tasks, thus freeing up your employees and allowing them to focus on more challenging work.” McKinsey notes that RPA is currently the most used AI technology for financial institutions.

RPA technologies are evolving to accomplish increasingly complex tasks. This ability further allows financial professionals to prioritize high-value, human-centric activities.

AI-Driven Customer Service

McKinsey reports customer service is the second most common application of AI technologies. Virtual assistants and conversational interfaces like chatbots can process customer inquiries, providing the timely information and personalized service modern consumers expect.

These technologies can also analyze complex customer inquiries and direct them to appropriate people as needed, which helps focus financial professionals’ time on the issues they are best suited (and have the authority) to address. As a result, customers benefit from rapid access to targeted expertise and less time waiting and reiterating issues after call transfers.

Cloud-Based Solutions for Remote Collaboration and Mobile Banking

World Wide Technology explains that the COVID-19 pandemic largely shifted financial services to remote, digital environments for businesses and consumers. Cloud-based computing technologies enabled this transition, furthering an ongoing trend toward digital and mobile banking as well as decentralized finance operations.

Cloud-based solutions for companies allow for productivity and efficient collaboration in remote work environments. Enterprise-scale cloud solutions can help integrate information systems, improving consistency of information flow and data security across operations.

Financial sector activities surrounding stocks, bonds, securities and other investment opportunities are also global in scope. Collaborative technologies enable international workforces, targeting markets across the globe. These technologies also facilitate regular, face-to-face engagement with clients when in-person meetings are not possible.

For consumers, personalized, omnichannel, mobile and digital banking has become the norm. Consumers expect access to financial services from everyday banking to mobile pay to mobile application-based investment opportunities on their devices at all times.

Security and RegTech

The security vulnerabilities inherent to remote work, data privacy concerns and regulations all have complex ramifications for the finance industry. Concurrently, AI technologies that can address these issues are rapidly evolving.

Financial firms and regulatory bodies increasingly use regulatory technology (RegTech) and compliance technologies. These technologies use ML and NLP to monitor transactions and risks, track compliance and provide regulatory reporting.

Organizations are using AI-driven cybersecurity software to protect organizational and consumer data. Such software can identify security vulnerabilities, anticipate and monitor potentially malicious behavior and assist in rapid incident response. Similarly, professionals employ AI-driven biometric technologies like fingerprint and facial recognition to improve identity management and security.

Further technological disruptions like cryptocurrency are changing how professionals conceive of money and transactions. Technology is reshaping the finance industry. Professionals must have a clear understanding of these technological developments and a willingness to embrace those to come in order to succeed in the future of finance.

Learn more about Murray State University’s online MBA with a concentration in Finance program.

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