Innovation offers neobanks a key to growth

AI, APIs and machine learning can play an important role in strategic planning and offer digital challengers a clearer path to future success.

Neobanks are considered by some to be the future of banking. According to the latest Neobanking Market Report, growth is expected at a compounded annual rate topping 50% through 2030. It’s an impressive projection, but like all financial institutions, economic uncertainty and a looming recession threaten that outlook.

As neobanks fight to gain traction, they face higher costs of doing business, rising interest rates and competition from both traditional banks and other innovators. Simple, considered the first neobank in the United States, shut its doors last winter amidst rising pressures and Varo, among others, has recently announced layoffs. Efforts to reach profitability are proving elusive for most neobanks: A recent report found that of the world’s 400 or so neobanks, fewer than 20 are running in the black.

To ensure their future, these fintech challengers need effective ways to cut costs and hold onto cash. They also need competitive advantages to counter traditional banks, which have embraced digital transformation. Tech innovation, including the adoption of powerful technologies like artificial intelligence (AI), machine learning (ML) and application programming interfaces (APIs) can provide important benefits that help them not only survive, but get ahead.

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Here’s a closer look at key benefits these technologies can provide for neobanks and their customers as they navigate these trying times and look to establish a foothold in the future:

Time and money saved through APIs: APIs are one of the most important technologies available – without them, tools like AI can’t be used to their full potential.

By plugging into different software programs, APIs unlock data and allow sharing of information and functionality. For instance, APIs can enable efficient sending and receiving of payment and invoice data between accounts payable, accounting and enterprise resource planning (ERP) software without user intervention.

This seamless communication also allows neobanks’ financial systems to connect and share data much faster and at lower costs. Instead of spending months or longer to build finance applications, neobanks can create them in days or even hours– a time savings that quickly translates to cost savings.

Competitive advantages with AI: AI was once a tool used only by the largest enterprises, but cloud-based software solutions have removed cost barriers and made the technology more affordable for smaller players. Neobanks can leverage AI in multiple business applications to transform internal and external processes to seize competitive advantages.

Perhaps mostly importantly, the technology enhances ongoing compliance and real-time protection against fraud and money laundering, potentially saving banks from expensive fees and reputational damage. It also significantly speeds processing of invoices and payments via more secure electronic payment methods.

AI can also replace time-intensive manual processes and free up back-office employees for more strategic work. This could help neobanks avoid staffing cuts that other institutions have resorted to reduce costs. By elevating roles for back-office staff, there is greater likelihood of enhancing job satisfaction, which could aid retention efforts.

According to Bankrate, there are approximately 23 million neobank customers today and that number is expected to hit 50 million by 2025. To ensure customer loyalty and satisfaction, neobanks can leverage AI-powered chatbots to provide more personalized and convenient service to customers.

Machine learning to future-proof operations: Neobanks have created a viable alternative to traditional banking, yet myriad factors – including tough economic times and intense competition – threaten their growth. The need exists for neobank leaders to protect their cash flow and capitalize on ways to future-proof their operations. Ensuring survival means creating new efficiencies to cut costs and better analyze data to monitor the health of the business and guide future decisions.

Machine learning, a popular type of datacentric AI, enables neobanks to analyze historical financial data to detect behavioral patterns in supplier payments and invoices and predict the likelihood of those behaviors continuing. It can also help make predictions on market or vendor payment risks, forecast future spending needs and provide loan assessments.

Continued investment in innovation – namely AI, ML and APIs – can play an important role in business continuity and strategic planning. It can offer neobanks a clearer path to success amidst the challenges that currently pose threats to their survival.

Boyce Adams is senior vice president of growth at AvidXchange.