The best generative AI use cases in fintech in 2024: Reviewed by Digimagg

Generative AI plays a pivotal role in fintech's evolution, offering advanced fraud detection, personalized banking experiences, and AI-driven stock selection. Its ability to process vast data, automate tasks, and forecast outcomes makes it indispensable in various financial sectors.

By harnessing generative AI, fintech firms enhance decision-making, risk management, and customer service, empowering financial institutions to deliver tailored solutions and optimize their operations.

The best generative AI use cases in financial services

GenAI's application in fintech shines in fraud detection and prevention

It processes vast transaction data streams instantly, flagging any anomalous behavior indicative of fraud.

With machine learning algorithms, these systems refine their fraud detection capabilities over time, leveraging past data for continuous improvement.

This not only aids in swiftly pinpointing suspicious behavior but also minimizes false alarms, thereby enhancing transaction security and fostering customer trust.

Richard Berkley, head of data, analytics, and AI in financial services at PA Consulting, highlights that AI's integration is reshaping how financial institutions make both micro and macro decisions.

Berkley notes that boards are recognizing the necessity of spearheading the shift from digital to intelligent organizations to maintain relevance and profitability in today's dynamic landscape. He explains that these organizations have been implementing AI frameworks and are now gearing up to develop generative AI capabilities for 2024, setting up enterprise-level AI platforms, and readying their organizations for the safe integration of AI technologies.

Changing the operational landscape of financial institutions

"In the realm of financial services, AI is poised to revolutionize investment strategies, reshape client expectations for AI-driven innovations and flexibility, redefine supplier governance in AI adoption, and enhance transparency in external reporting regarding AI usage," Berkley explained.

He further emphasized the importance for financial institutions to leverage AI to enhance human capabilities, addressing user needs through insights and automation. This approach fosters synergy between AI and human skills, ensuring they complement each other rather than compete.

Expediting compliance with regulations

For instance, financial institutions are employing generative AI solutions to anticipate how regulatory changes will affect their policies, processes, and obligations. These solutions generate alerts to notify stakeholders appropriately. Additionally, they utilize generative AI to compare regulatory reporting across various jurisdictions and ensure compliance with relevant regulations.

Generative AI assists the business's first line in understanding its obligations and policies by leveraging previous inquiries typically addressed by the second line of defense. It aids in consolidating insights into the regulatory landscape, encompassing horizon scanning, regulatory engagement, policies, procedures, and related change endeavors.

Deals with economic misconduct

Some platforms are beginning to utilize generative AI to combat economic misconduct, according to Berkley.

This involves incorporating AI and machine learning into transaction monitoring systems, analyzing behavior to detect unusual activities, and incorporating biometric authentication for identity verification to combat identity theft. Berkley further mentioned:

"However, such solutions require careful attention to ethical considerations, including data privacy management, addressing algorithmic biases, ensuring the reliability of outcomes from generative AI systems, and addressing societal concerns about the potential job displacement caused by generative AI."

Real-World generative AI examples in Fintech

The examples below illustrate the potential future applications of generative AI in FinTech. They present limitless possibilities for how AI technology will revolutionize the operations of FinTech businesses and the banking industry.

PayPal using AI to combat fraud

PayPal leverages generative AI to detect patterns and irregularities in user behavior, particularly identifying fraudulent activities. By gathering data on devices, sessions, and third-party sources, PayPal builds comprehensive user and transaction profiles. Through machine learning models analyzing device data, sessions, verification checks, IP addresses, and behavior patterns, PayPal ensures the safety and security of transactions.

Crediture uses Gen-AI for credit scoring

Crediture, a prominent credit scoring platform, utilizes generative AI to develop credit scoring and risk management procedures. By training their systems on vast financial data, they analyze economic conditions, industry trends, and other factors. This enables accurate predictions of bear markets, unusual events, market volatility, and recessions. Additionally, Crediture employs generative AI algorithms to provide personalized lending options to business borrowers. These algorithms generate customized credit product recommendations based on a company's financial standing, utilizing Variational Auto-Encoders (VAE).

Bridgewater Associates (the world’s largest hedge fund) uses AI

While many businesses deliberated on the adoption of AI, Bridgewater Associates, the world's largest hedge fund, had long embraced and implemented it. Through extensive analysis, they recognized the ability of AI and large language models to effectively analyze data, test hypotheses, and enhance decision-making processes.

Greg Jason, co-chief information officer at Bridgewater Associates, highlighted in an interview the potential of ChatGPT and other artificial intelligence (AI) models. He emphasized that with gen-AI applications, there's a notable enhancement in efficiency, cost reduction, and accuracy in market predictions.

Cleo, a personal financing app, uses ChatGPT tech

Cleo serves as your virtual financial assistant, powered by AI technology. Utilizing ChatGPT, this app analyzes your financial data and offers personalized budgeting and saving recommendations. Upon connecting your bank account, Cleo promptly assesses it, delivering real-time insights and advice to help you make informed decisions. Moreover, Cleo employs gen-AI and natural language processing to address your financial inquiries within the app.

FintechOS, a cloud-based platform that helps financial institutions manage their regulatory compliance and reporting requirements

FintechOS assists banks and financial institutions in implementing digital solutions. Their recent update, FintechOS 22, emphasizes enhancing digital transformations through a no-code or low-code approach. Additionally, they consistently update their services to ensure compliance with financial regulations. In essence, FintechOS provides tailored solutions while adapting to regulatory requirements across different financial organizations.

The future of GenAI in Fintech

In the fintech sector, the significant opportunity lies in how banks can leverage customer data along with other data sources to directly benefit customers, stated Dom Couldwell, head of field engineering EMEA at DataStax, a real-time data for AI company.

"For banks and fintech providers, this will be the battleground, determining who can offer the best customer experience and how they can utilize data within that experience," he noted. "Teams are already developing chat services that deliver more personalized experiences by leveraging each customer's data."

Banks are contemplating the next evolution. Similar to how the iPhone popularized apps like Instagram, Uber, and Spotify, there's now a race to create the first ubiquitous app for generative AI, Couldwell explained. "However, this journey is just beginning," he added. "Integrating a new technology into the core of operations will require time."

Generative AI holds the potential to enhance operational efficiency for organizations in meeting regulatory requirements by analyzing and presenting data in the appropriate format. Couldwell emphasized that while this may not be the most glamorous use case, it offers substantial benefits, especially in streamlining operations beyond commonly discussed areas like improving Know Your Customer operations or fraud monitoring.

Despite its advantages, there are drawbacks to using generative AI in fintech. PA Consulting's experts have identified emerging economic crime risks associated with generative AI, including phishing, social engineering, and the generation of fraudulent data, which could enable more sophisticated illicit activities.

"It's crucial for fintech firms and financial institutions to grasp the risks of generative AI and the potential for misuse," Berkely concluded. "As the misuse of generative AI for fraudulent purposes poses an increasing threat to these institutions and their customers."

In summary, the application of generative AI across different scenarios within the fintech sector demonstrates its versatility and potential.

Consequently, this technology holds promise for transforming numerous facets of the financial industry by enhancing efficiency, precision, and overall customer satisfaction.