FinTech: How AI Is Accelerating Business Growth, Shifting Industry Hiring Needs

The McKinsey Global Institute estimates that among industries globally, generative AI could add the equivalent of $2.6 to $4.4 trillion annually in value. Banking is expected to be one of the largest beneficiaries with an annual growth potential of $200 billion to $340 billion – the equivalent of 9 to 15 percent of operating profits in the traditional banking sector – largely from generative AI contributing to streamlining and increasing productivity.

While smartphones took many years to transition banking to a more digital destination — mobile banking only recently overtook the web as the primary customer engagement channel in the United States — adoption of generative AI tools has been occurring at breakneck speed. Traditional investment firms and larger banking institutions like Goldman Sachs have reportedly started using an AI-based tool to automate ‘test generation’, a test designed to exercise various functionalities and identify potential errors or defects in a given software, hardware, or model. Prior to the latest advances in AI, ‘test generation’ on software like banking apps proved to be a manual, highly labor-intensive process; even Citigroup recently integrated generative AI to model and assess the impact of new US capital rules and its effects on long-term profits.

AI leads the way in FinTech growth

In a 2023 McKinsey survey, CFOs cited capability building and advanced technologies as the two most effective ways to build resilience into their organizations.  Less than a year after generative AI tools became widely available, 24 percent of staff in financial services companies have already begun integrating them in their work. 

Nevertheless, the market for AI in FinTech is anticipated to be worth $42.83 billion in 2023 and grow to $49.43 billion by 2028, making it undoubtedly necessary for companies to adapt to the new technology. Nonetheless, it has been the emergence of digital FinTech solutions that have challenged traditional banking models and generated so many new opportunities for consumers and businesses alike, eschewing traditional institutions which had been founded on the practice of establishing lines of credit.

Accounting for 77.5% of the global revenue, the FinTech “solution segment” – comprising applications for mobile banking, digital loans, insurance, credit scores, buying and selling activities, and asset management – dominates the flourishing market. This has initiated a wellspring of startup FinTech companies in the United States and abroad hoping to capitalize on a market still in its infancy. 

Due to prominent AI software and system vendors, projections unanimously suggest North America will continue to lead the market for AI over five years, further emphasizing that AI and its FinTech services is not only here to stay; but it is absolutely imperative that we take a closer look at some of the emergent companies who have staked a claim in the FinTech sector and embedded AI technologies into the fabric of their business models.

Buy Now, Pay Later: FinTech companies at the forefront of AI 

Released just in time for the holiday season last year, Amazon unveiled its first Buy Now, Pay Later (BNPL) checkout option for the millions of small business owners who use the ecommerce giant’s online store. The tech giant revealed its partnership with Affirm expanding to include Amazon Business, the e-commerce platform that caters to companies. Quickly gaining popularity as consumers have turned to alternative business solutions, Buy Now, Pay Later (BNPL) digital loans offer a way to split purchases into fixed installments, without accruing interest in most cases and incentivizing payment on time. Here's a breakdown of their key features:

Basics

• You choose BNPL as a payment option at checkout online or in-store.
• You provide basic information for a quick credit check (often softer checks that don't impact your credit score).
• If approved, you pay an initial down payment (usually 25-50%) and the remaining balance is split into equal installments (typically 2-4 payments).
• Payments are automatically deducted from your debit card, credit card, or bank account on specific due dates. 

Providing loans ranging from $100 to $20,000, Amazon’s new service has been designed specifically for sole proprietors or small businesses owned by a single person – the most common form of business ownership in the U.S. 

After Affirm’s closed end installment loans, offered through its partnership with Peloton saw a reduction in sales, the San Francisco based Affirm laid off nearly twenty percent of its workforce earlier last year in an attempt to slash costs and devote itself to applying high-level strategy for the future of the company. Expecting demand for its short-term consumer loans to increase if interest rates stay high for an extended period, Affirm’s shares immediately jumped 19% once the news broke of its partnership with Amazon. 

Affirm CEO Max Levchin, a former citizen of Kiev who grew up under the iron fist of USSR’s socialist policies and creator of PayPal, recently spoke to Wired’s “Have a Nice Future” podcast to discuss his vision for a consumer friendly BNPL society:

“We are borrowing money every time we swipe a credit card. Full stop. Now, those of us who live on the coasts and make excellent salaries probably just pay it off at the end…But for the vast majority of Americans, it goes into this big bucket and most of them — something like two-thirds of the country — is revolving on seven-and-a-half thousand dollars. A lot of those seven-and-a-half thousand dollars are groceries and milk and all the various things that we have to buy to feed our families. A much better model is when you will be done paying off all of your debt, whether it's for bicycles or couches or milk by a certain date. That should give you a sense of certainty and sense of control.”

One of BNPL’s most outspoken advocates, Levchin has stressed the importance of reclaiming the consumer’s autonomy and eliminating the predatory practices associated with longstanding lines of credit. In its recent annual report, Affirm expressed that the Consumer Financial Protection Bureau’s supervision of the FinTech BNPL space is desired and  imminent, seeking greater industry wide guidance from the Consumer Financial Protection Bureau on companies’ adherence to federal and state lending regulations. 

How does AI play into all this? 

Although Generative AI does not make any underwriting or lending decisions for Affirm and reiterated that he does not see that being a part of the company’s immediate future, AI has been instrumental in the collection of potential customer data, which in turn enables FinTech lenders like Affirm to more comprehensively evaluate a potential loan at an expedited rate. Levchin continued:

“We use lots of machine learning, which sometimes gets lumped into the overall AI umbrella, but it's very different. We model out what we believe to be a good estimate of your personal cash flow, and then ask the question, can you afford to borrow money? And what have we seen in the history of your repayment that indicates whether you're going to be willing to pay us back or not?”

As highlighted, AI is an instrumental component of FinTech’s BNPL sector, allowing lending companies to crunch data and assess customers at an accelerated rate required for continued growth.  

Much like Affirm, consumer and business lending leader Enova was founded on the principle of serving underrepresented markets.While there are some conflicting reports regarding the company’s origin, it is most commonly acknowledged that Enova was founded by Al Goldstein under the name Check Giant. Previously an investment banker, Goldstein sold the company to Cash America in 2006, and subsequently, Enova International established itself as a pioneer in the fintech world, focusing on online financial services for non-prime consumers and small businesses. 

Enova has built its reputation on advanced analytics and technology, providing credit access to those underserved by traditional banks. The FinTech company has been marked by steady growth, strategic acquisitions, and a commitment to serving underserved markets, leveraging proprietary technology, data analysis, and a customer-centric approach to offer financial solutions for those who might otherwise struggle to access them. 

Headquartered in Chicago and serving millions of customers globally, Enova went public on the NYSE in 2008 and has accounted for $52 billion in loan originations and financing. With over 1,500 employees, Enova International has started to bill itself as not only a leading financial technology company that provides online financial services but through its proprietary machine learning-powered Colossus platform all the while boasting that 90% of its models have been AI generated, a transition from earlier of the company’s proprietary technology. 

Formerly a pre-qualification for loan decisions, the currency iteration of Colossus performs a multitude of functions within the FinTech company, including:

1. Flexibility and Adaptability: Unlike many analytics platforms, Colossus isn't limited to specific industries or problems. It can handle data from a diverse range of sources and build generalized models, making it adaptable to various business needs. This feature allows companies to use the platform for tasks like predicting customer enrollment in programs or insurance purchases, regardless of their particular field.
2. Streamlined Integration: Colossus simplifies data handling by consolidating information from various sources into a single platform. This eliminates the need to integrate multiple systems, saving time and resources. Additionally, new models can be implemented quickly by business analysts, reducing dependence on IT departments.
3. Machine Learning for Continuous Improvement: Colossus leverages machine learning, allowing it to constantly learn and improve its accuracy over time. This ensures that the platform remains effective and adapts to changing data patterns on its own.
4. Ease of Use: The platform is designed to be user-friendly, requiring only a single API call for implementation. This makes it accessible to companies without extensive technical expertise.
5. Efficiency and Accuracy: Colossus can automate various operational decisions related to fraud, credit risk, marketing, and more. This improves efficiency and accuracy compared to manual processes.
6. Focus on Specific Use Cases: Enova offers versions of Colossus tailored to specific needs, such as Headway Capital's use for credit risk assessment and marketing offers. This customization can further enhance the platform's effectiveness.

In Envoa’s annual report, the company’s total revenue of $584 million in the fourth quarter of 2023 increased 20% from $486 million in the fourth quarter of 2022. Such growth can be directly attributed to the advances in AI technologies and machine learning utilizing the Colossus platform, which has transformed from a basic pre-qualification tool to a versatile real-time analytics engine serving a multitude of industries and lending related needs.

Key hires for AI related FinTech

In an attempt to stay at the forefront of FinTech’s AI demand and compete with traditional  mobile banking, companies like Affirm and Enova will need to bolster their AI and machine learning hires, preparing their BNPL products for a highly competitive market. 

Crucial hires will include: 

• AI Product Managers: Bridging the gap between the technical aspects of AI and the financial industry's specific needs and regulations, AI product managers focus on strategy and vision as well as a company’s alignment with business goals and regulatory requirements. Additionally, they oversee the development and implementation of AI projects, managing teams of data scientists, engineers, and other specialists while establishing best practices for data collection, storage, and usage of sensitive financial information.
• ML Ops & Developers: Using their expertise in ML algorithms, frameworks, and libraries like TensorFlow, PyTorch, and scikit-learn to build and train models that analyze large datasets and make predictions or recommendations, ML developers recommend BNPL plans tailored to individual borrowers' financial situations and repayment capabilities. This promotes responsible borrowing and financial wellbeing for the customer and business alike.
• Java Developers: Leveraging Java's strengths in security, scalability, and performance, developers often collaborate with other professionals like data scientists, AI engineers, and financial analysts to bring AI-powered FinTech solutions to life. A developer's duties may also include fraud detection and prevention, algorithmic trading and risk management, personalized financial services, and backend infrastructure and integration. 

While the FinTech space is already experiencing explosive growth fueled by AI, we are only witnessing the beginning. As companies like Affirm and Enova demonstrate, AI plays a crucial role in streamlining processes, expanding accessibility, and personalizing financial solutions. Looking ahead, expect continuous innovation in AI-powered lending, algorithmic trading, and fraud detection, further transforming the financial landscape for both businesses and consumers. This dynamic space demands constant adaptation, particularly with regard to hiring on behalf of established financial institutions which need to keep pace with more nimble startups accustomed to moving much faster. 

As AI utilization in FinTech expands, regulatory oversight becomes increasingly important. While Affirm welcomes guidance from the Consumer Financial Protection Bureau, ethical considerations, data privacy, and fair lending practices demand rigorous regulatory frameworks. This presents a unique set of challenges for FinTech startups and scaleups in the months and years ahead. Striking a balance between fostering innovation and ensuring consumer protection will be vital in shaping a responsible and inclusive FinTech future.