Commonly referred to as “AI,” artificial intelligence is making headlines for the profound impact that it is having on a number of different professional disciplines and business sectors. This article will take a relatively brief but comprehensive look at the integration of AI in the world of fintech (financial technology). AI is radically reshaping the fintech landscape from predictive analytics to personalized customer experiences to enhanced security measures.
Understanding Fintech and AI
Fintech is a blanket term that encompasses the numerous ways that technology is used in the financial services sector. Initially limited to the backend computer systems of central banks and early consumer tech applications such as ATMs, fintech has come a long way over the years. Fintech AI, powered by advanced digital tools and algorithms, transforms financial services and management for consumers and organizations by leveraging various technologies within the financial services sector.
Artificial Intelligence in Financial Services
Today’s banks, investment firms and other financial services organizations know that AI offers countless ways to boost operational efficiency and drive wealth generation. In fact, no corner of the financial services world has been left untouched by AI and its various benefits.
Impact of AI on Traditional Financial Institutions
The prominence of artificial intelligence in fintech is having a tremendous effect on financial institutions, many of which have endured for centuries. In the words of the venerable business research firm Deloitte, “The emergence of AI is disrupting the physics of the industry, weakening the bonds that have held together the components of the traditional financial institutions, and opening the door to more innovations and new operating models.”
Applications of AI in Fintech
So, how widespread is artificial intelligence for fintech, and how is this AI being used? Read on to learn about just a few of the areas of financial services currently being transformed by AI.
Automated Financial Advisory Services
Otherwise known as robo-advisors, automated financial advisory services have gotten considerably more customizable and sophisticated in recent years. Quite popular with ordinary investors who have limited resources and experience, automated financial advisory services draw upon large amounts of investor and market information to automatically recommend optimum investment strategies. Even experienced investors commonly use these services for help with portfolio rebalancing, tax-loss harvesting and other time-consuming investment and accounting tasks.
AI-Powered Credit Scoring and Risk Assessment
Credit scoring and risk assessment have long been essential investment vetting processes. Although it has yet to reach its full promise in these areas, modern artificial intelligence has already automated countless credit scoring and risk assessment processes and made them far more efficient. The business analytics giant SP Global writes, “We believe the use of artificial intelligence, in connection with firms’ alternative datasets (i.e., digital fingerprints) can…generate more accurate and timely signals for credit risk management and investment purposes.”
Personalized Customer Experience
Artificial intelligence has powerful forward-facing capabilities revolutionizing the customer experience (CX) field. Thanks to is unique ability to analyze massive amounts of customer data, AI tech can gain significant insights into each individual consumer’s unique financial preferences, habits and goals. Fintech professionals can then use these insights to deliver highly customized CX that speaks directly to personalized wants and needs.
Enhanced Security and Fraud Detection
According to the major AI development company Leeway Hertz, AI’s growing role in the worlds of cybersecurity and anti-fraud measures represents more than a passing trend, it “signifies a fundamental shift in how fraud detection is approached, transforming the entire landscape.”
Utilizing AI for Fraud Prevention and Detection
With its reliance on rigid authoritative systems and predefined “red flag” thresholds, traditional fraud detection methods have struggled for years to keep pace with the sophisticated strategies of modern financial fraudsters. Artificial intelligence, however, offers a far more flexible and dynamic approach to security and fraud detection that allows fintech professionals to keep pace with even the savviest of today’s financial criminals.
Compliance and Regulatory Considerations
Different sectors of the financial services market are subject to different rules and regulations to prevent crimes, protect consumers, and generally ensure fair and equitable industry operations. Highly precise and largely automated, AI tech is a useful tool for ensuring full compliance with all relevant security and anti-fraud laws as well as avoiding potential regulatory fines and other legal penalties.
Advancements in Payment Processing
Driven by rapidly evolving technology such as digital wallets and contactless transactions, AI is transforming the world of payment processing in several ways.
AI-Powered Payments and Digital Wallets
When it comes to making cashless payments and payments in general, more and more Americans are using digital wallets from providers such as Apple Pay and PayPal. According to a survey by Forbes Advisor, 53 percent of U.S. consumers used digital wallets more than they used traditional payment methods in 2023, while 64 percent reported using them roughly as often. AI drives innovation in digital wallets and electronic payments by boosting customer personalization, strengthening cybersecurity, widening accessibility, and facilitating cryptocurrency transactions.
Transactions Using Machine Learning Algorithms
A principal subcategory of artificial intelligence, machine learning (ML) occurs when AI can autonomously “learn” from the information it receives, effectively teaching itself to perform tasks better. Its incredible capacity to identify and classify data patterns makes ML tech an ideal tool for payments industry professionals who want to determine if transaction activity is typical or suspicious.
Future of Cashless and Contactless Payments
In the wake of the COVID-19 pandemic, consumer desire for cashless and contactless payments skyrocketed, and the market has only continued to expand since then. AI and ML tech is playing a key role in that expansion. Per research experts at Markets and Markets, the contactless payment market is projected to hit $18 billion by 2025, up nearly $8 billion from the height of the COVID-19 pandemic in 2020.
AI-Driven Financial Analytics and Insights
Today’s financial services professionals rely on AI-driven analytics platforms such as Alphasense and Kavout to gain key market insights and produce financial forecasting models of exceptional complexity and precision. Thanks to the sheer amount of information that AI can speedily process, these platforms allow fintech professionals to accurately assess the financial health of organizations and both evaluate and predict market trends to make the very most out of emerging investment opportunities.
Predictive Analytics for Market Trends and Investment Opportunities
Fintech professionals analyze market trends and consumer preferences to develop models that uncover current insights and forecast future opportunities and challenges. Armed with this detailed information and trustworthy predictions, organizations and individuals alike are far more likely to make successful investment decisions.
AI-Based Portfolio and Wealth Management
From personal robo-advisors to industry-wide fraud prevention, artificial intelligence is enhancing portfolio and wealth management in countless ways. Beyond its incredible ability to process large amounts of information in small amounts of time, AI brings exceptional accuracy and precision to financial services processes. Because AI operations are generally automated, the risk of human error causing accidental discrepancies is minimal or nonexistent in most cases.
Challenges and Considerations
Although the benefits discussed above make a compelling case for the widespread implementation of artificial intelligence in finance, the technology is not without its problematic challenges. Before diving into fintech AI training, consider these factors to understand its complex implications and to navigate your fintech career path more effectively:
Ethical Implications of AI in Finance
One of the primary challenges that AI faces, both in financial services and elsewhere, is its perceived lack of transparency. Because AI works automatically and often without human supervision, the potential for misuse is certainly real. Furthermore, AI’s reliance on big data raises reasonable and noteworthy concerns about privacy violations and cybersecurity risks.
Bias and Fairness in AI Algorithms
Although there is nothing inherently discriminatory about artificial intelligence, AI systems are only as good as the data that they receive, and this data is often subject to human biases. This is the underlying idea behind algorithmic bias. Due to the powerful role that AI plays in modern financial services, algorithmic bias has been linked to unfair decision-making and outcomes based on race, age, gender and other personal characteristics. In some cases, these accusations have led to legal action.
Future Trends and Outlook
The increased integration of AI within the finance sector and a myriad of others is bound to face challenges and criticism from people. But if it continues to offer such tremendous competitive advantages, the use of AI is only likely to grow for the foreseeable future.
Predictions for the Evolution of Fintech and AI
Award-winning global AI thought leader Aruna Pattam states most of the top areas of innovation in fintech for 2024 involve some form of artificial intelligence. Specific growth areas to watch include regulatory technology (regtech), third-party banking process outsourcing (BaaS), green finance and blockchain. In terms of blockchain use, Pattam predicts increased industry adoption of smart contracts, which are composed of code, securely stored on a blockchain, and automatically self-executing to guarantee that agreed-upon outcomes occur.
Future Opportunities in Finance
Looking to start or expand your career in financial services? You will have to possess a solid understanding of fintech because fintech is so central to all types of financial services operations today. Should you want to be a part of the driving force behind modern financial services innovation, you should aim to go far beyond mere fintech proficiency and center on one or more specific, relevant areas of fintech with an in-depth focus. As the predominate form of technology impacting financial services today, AI must be an essential component of the professional training and workplace experience of anyone seeking to take advantage of future opportunities in the sector.
To Learn More
At Keiser University, we have several different academic programs to meet the unique needs of all kinds of existing and aspiring fintech professionals. Take a close look at our Master of Science in Financial Technology program, Master of Science in Information Technology Leadership program, and our Master of Business Administration in Technology Management program to see which, if any, might be right for you. For more information about any of the educational offerings and opportunities at Keiser University, visit our official school website to fill out a brief online graduate admissions counselor contact form.
