AI in Financial Technology (Fintech), Explained

Financial technology, or fintech, refers to the use of digital tools to improve and automate financial services. From banking and investing to payments and credit scoring, fintech is transforming how people and businesses manage money. While the term gained traction after the 2008 financial crisis, the fusion of finance and technology dates back decades—beginning with innovations like the ATM in the 1960s.

Kwamie Dunbar, associate professor in The Business School at Worcester Polytechnic Institute (WPI) and director of the university’s Master of Science in Financial Technology program, explains that fintech has emerged as the “next logical step in finance,” combining economics and accounting concepts with technologies like mobile apps, machine learning, blockchain, and artificial intelligence.

Fintech is now used across the spectrum of financial services by consumers, banks, credit card companies, lenders, payment platforms, financial advisors, investors, traders, hedge funds, and more.

“As the fintech industry evolves, regulatory challenges, cybersecurity concerns, and financial inclusion must be addressed to ensure sustainable growth,” Dunbar warns.

Artificial intelligence (AI) has become a “foundational tool” in fintech, according to Dunbar, enabling efficiency, automation, and enhanced decision-making. AI is also revolutionizing credit assessment, fraud prevention, trading, and advisory services.

For example, elements of AI, such as natural language processing (NLP) and machine learning, in finance lead to more accurate predictions and optimized transactions. Many institutions also use generative AI in finance applications to produce reports quickly.

Currently, key applications of AI in finance and fintech include:

• Credit scoring: AI-powered credit-scoring models use alternative data sources, such as transaction history, utility payments, and even social media behavior to assess creditworthiness more accurately than traditional methods do, or for credit underwriting to offer more inclusive loan approvals.
• Fraud detection: AI-driven fraud detection models analyze transactional patterns in real time, identifying anomalies that may indicate fraudulent activity.
• Robo-advising: AI-powered robo-advisors provide personalized investment recommendations and portfolio management services with minimal human intervention. For example, some popular investment services use AI to offer automated wealth management solutions.
• Algorithmic trading: Some trading platforms now use AI-driven trading models that analyze vast datasets to predict market movements and execute high-frequency trades at optimal moments. These algorithmic trading solutions are for hedge funds and individual investors alike.

AI in financial services has the potential to help bring more people into the traditional financial system, especially those who are underbanked or unbanked. For example:

• People with a substandard or insufficient credit history can demonstrate their creditworthiness via alternative data sources, thanks to AI-driven credit scoring.
• Banking services are more accessible due to neobanks (i.e., fintech companies that provide banking services like checking and savings accounts but do not have physical branches). Neobanks empower individuals to access banking services with fewer barriers to entry, lower fees, and more competitive interest rates.

Dunbar adds, “AI in the finance industry is an additional tool that enhances efficiency, not replaces humans.” Although the ATM has been a mainstay for nearly 60 years, we still have tellers today.

Despite its numerous advantages, fintech also has its drawbacks, according to Dunbar. They include:

• Cybersecurity risks: Digital platforms are prime targets for hacking and data breaches.
• Regulatory uncertainty: Rapid innovation often outpaces regulation, leading to oversight and compliance challenges.
• Lack of face-to-face interaction: Automated services reduce human customer support, which some users prefer.
• Financial exclusion risks: AI-based credit scoring may unintentionally exclude individuals with insufficient digital footprints.

Like any technology, fintech poses some risks, such as:

• Data breaches: Sensitive financial data is a high-value target for hackers.
• Phishing attacks: Cybercriminals impersonate fintech platforms to steal user credentials.
• Insider threats: Employees with access to sensitive financial data may pose a risk.

To mitigate security risks, fintech firms implement the following tactics:

• End-to-end encryption: For example, neobanks use encryption to protect user transactions.
• Biometric authentication: Digital wallets use facial recognition and fingerprint scanning to verify the identity of users.
• Blockchain for security: Fintech companies use blockchain-based security platforms to enhance transaction security.

“Fintech fosters financial inclusion, enhances efficiency, and drives innovation,” Dunbar says. It does so by:

• Expanding access to financial services: Digital wallets and microloan platforms empower unbanked populations.
• Reducing costs for consumers and businesses: Peer-to-peer payment solutions lower transaction costs.
• Increasing market efficiency: AI-powered trading platforms enhance liquidity and price discovery.
• Enabling cross-border payments: Blockchain technology, like cryptocurrency platforms, makes international transactions and economic opportunities more accessible.

Fintech firms operate in highly regulated environments and must comply with several challenging regulations, including:

• U.S. Financial Crimes Enforcement Network (FinCEN) regulations: Both customers and fintech companies must comply with anti-money laundering rules and Know Your Customer standards as required by FinCEN. These regulations are designed to help detect and report illegal activity, such as securities fraud and market manipulation, that could lay the foundation for money laundering and terrorist financing.
• Data privacy laws: Regulations such as Europe’s General Data Protection Regulation and the California Consumer Privacy Act have strict requirements around how the personal data of consumers must be handled, processed, and protected. Violations result in heavy penalties.
• Licensing and banking regulations: Digital banks must navigate licensing requirements imposed by financial regulators like the U.S. Securities and Exchange Commission (SEC), Consumer Financial Protection Bureau, and Office of the Comptroller of the Currency. Likewise, digital banks with customers in Europe must comply with regulatory bodies such as the European Banking Authority and the European Securities and Markets Authority.
• Cryptocurrency regulations: Fintech firms operating in the crypto space also face regulations by the SEC and global financial authorities. These regulations are intended to protect investors from crypto asset scams and other cyber-related threats.

For more information on fintech regulations and initiatives in the U.S., visit the Office of the Strategic Hub for Innovation and Financial Technology (aka FinHub), a division of the SEC.

Universities worldwide now offer specialized degrees in fintech to prepare professionals for the industry. Available degrees include:

• Bachelor’s in fintech, built for undergraduates exploring finance and technology.
• Master’s in fintech, designed for finance professionals and engineers seeking to build their AI, blockchain, and investment expertise.
• Fintech certificates, ideal for professionals who want to transition into fintech or advance in the field.

“The future of fintech lies in AI-driven personalization, blockchain innovations, and the expansion of open banking ecosystems,” Dunbar says. Be on the lookout for these emerging fintech trends:

• Decentralized finance (DeFi): Platforms like decentralized crypto lending protocols and crypto exchanges are reshaping lending and trading.
• Embedded finance: Companies that provide buy now, pay later (BNPL) services integrate financial services into e-commerce platforms.
• AI-driven personalization: Machine-learning solutions can automate credit underwriting and help make more equitable lending decisions.
• Green finance and environmental, social, and governance (ESG) investing: Such platforms focus on sustainable investments.

Open banking is a system where banks share financial data with third-party providers via application programming interfaces (APIs), which enable the exchange. Fintech apps and payment services use the open APIs provided by data-transfer platforms for essential banking connections.

Open banking enhances competition and innovation by paving the road for automated processes, increased transparency, and more direct consumer control. Fintech companies can use the information available via open banking APIs to speed up the development of new products and services. Open banking also creates the potential for individuals to have a more comprehensive credit profile, which could benefit those with limited or no traditional credit history.

AI and open banking APIs work synergistically, as AI analyzes financial data to offer personalized financial recommendations, strengthen the security of transactions, and simplify decision-making.

Blockchain and AI drive innovations in fintech via the following capabilities:

• Smart contract automation: AI enhances contract validation in blockchain platforms, allowing self-executing agreements known as smart contracts, with terms written directly into code on the blockchain. By eliminating the need for intermediaries, smart contracts increase transaction efficiency. However, traditional smart contracts have limitations, including vulnerabilities to coding errors and security risks.
• Fraud detection in crypto: AI tools analyze transactions to detect suspicious activity in cryptocurrency exchanges. Because crypto transactions are immutable and decentralized, they are attractive tools for money laundering, illicit trade, and fraud. While traditional financial institutions have relied on centralized oversight for fraud prevention, decentralized finance must rely on AI-powered tools to monitor blockchain transactions in real time.
• Predictive analytics in trading: AI-powered platforms like crowd-sourced hedge funds develop predictive machine learning models for the crypto market. Providing up-to-the-minute data analysis and risk assessment, AI tools can predict market conditions and help users optimize their investments.

Fintech innovations, particularly ones related to AI, are transforming adjacent industries:

• In accounting tech: AI-powered bookkeeping tools automate financial record-keeping.
• In regtech: Compliance solutions help firms meet regulatory requirements using AI-driven monitoring.
• In insurtech: AI-supported insurance firms use machine learning for automated claims processing and risk assessment.

Fintech firms generate revenue through various business models, including:

• Transaction fees: Payment processors charge fees per transaction.
• Subscription models: Robo-advisors charge monthly fees for asset management services.
• Interest on loans: Digital lenders earn interest on personal and business loans.
• Interchange fees: Neobanks earn revenue from interchange fees when customers use their debit cards.
• Licensing and software-as-a-service models: Fintech companies license their API-driven financial data services to banks and other fintech firms.

Several prominent companies have revolutionized traditional financial processes. They include:

• Affirm: Prominent U.S. BNPL provider, often seen on e-commerce sites.
• Apple Pay: Widely used digital wallet embedded in the Apple ecosystem.
• Binance: One of the largest global crypto exchanges by volume.
• Cash App: Popular digital wallet and investing app owned by Block, Inc.
• Chime: One of the leading neobanks in the U.S., focused on consumer-friendly banking.
• Coinbase: Leading U.S.-based cryptocurrency exchange with strong brand and revenue.
• Google Pay: Major mobile payment solution with global reach.
• Klarna: Major BNPL provider with a strong international presence.
• PayPal: Global payment giant offering digital wallets, merchant services, and peer-to-peer transfers.
• Plaid: Backbone of many fintech apps, connecting banks to apps via application programming interfaces.
• Revolut: Global neobank offering banking, investing, and crypto services.
• Robinhood: Commission-free trading platform that disrupted the brokerage industry.
• Rocket Mortgage: Top digital mortgage lender in the U.S. and part of Rocket Companies.
• SoFi: Comprehensive personal finance platform covering lending, investing, and banking.
• Square (now Block, Inc.): Known for point-of-sale systems with a strong presence in retail and crypto.
• Stripe: Major payment processor powering e-commerce businesses with robust application programming interfaces.
• Venmo: Peer-to-peer payment service owned by PayPal that’s especially popular among younger users.

Disclaimer: The fintech companies mentioned in this explainer are provided as examples for educational purposes only. Their inclusion does not constitute an endorsement or recommendation of their products or services. This material is intended solely to illustrate concepts and trends within the fintech landscape. Readers should conduct their own research and due diligence before engaging with any financial technology provider or service.

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