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How AI Boosts Fintech: 7 Promising AI-Powered Industries To Follow




When Willie Sutton, once one of America’s most wanted fugitives, was asked why he robbed banks, his response was remarkably simple, “Because that’s where the money is.”

This is the same answer that could be given to those who inquire about the growing tendency towards regulation in the fintech sector, and who believe that increasing legislation could damage innovation in the field. That’s where the money is, therefore, the stakes are high, and more regulation will be there. This will most likely happen sooner than later, as Michael Hsu, Acting Comptroller of the Currency, said recently. Therefore, we can expect compliance to be at the forefront of the conversation, and to become a priority for venture capitalists, CFOs, and other stakeholders alike.

Although the volume of fintech deals globally fell from $63.2 billion to $52.4 billion from H22022 to H12023, as well as the stock prices of publicly-traded fintech declined, including Affirm, Block, PayPal, and SoFi, nevertheless, in my opinion, the sector is far from being dead and in fact, it still holds immense potential. First, even though EU and APAC fintech market was shrinking, the US fintech market experienced steep growth from $28.9 billion to $36.1 billion during the same period. Second, the caveat is that to realize fintech potential, we first need to understand that the rules of the game have changed. While some years ago, the main focus for fintech startups–and for the venture capitalists that backed them–was to acquire more customers, now, there is a growing emphasis on profitability. And while there are still segments of fintech–like DeFi–which still operate in some sort of liberal paradise without many regulations, there is one technology that I believe will radically transform the industry, and help it thrive despite the regulatory pressure.

This technology is AI, and here are seven verticals within fintech that, from my perspective, are worth watching because of their enormous potential.

1. Personalization

By leveraging generative AI to deploy chatbots and make enhancements to both the user interface (UI) and user experience (UX), as well as to collect extensive volumes of data and detect accurate patterns, companies can personalize their financial products and services so that they can meet a specific customer’s needs. This is part of a larger trend that is taking place across industries, given the fantastic capabilities that AI offers for customization.

Let’s remember that money is something deeply personal, therefore, being able to ultra-personalize the products and services that a firm offers can substantially catalyze its connection with its customers, and substantially improve conversion rates, which in turn enhance revenue. Banks and financial institutions would be, from my perspective, more than willing to partner with a venture that helps them accomplish these goals.

2. Risk management

AI is completely redefining risk management. A study by KPMG identified three key abilities possessed by artificial intelligence systems that are now being integrated by financial institutions, despite their initial reticence to evolve technologically. These include superior forecasting accuracy, improved variable selection processes, and higher precision when segmenting.

Taking advantage of these capacities, financial institutions can, for example, have a clearer picture of their credit risk and their exposure to default, and make better decisions when determining which subjects are worthy of credit. Also, they could improve their fraud detection processes, which already cost banks $4.36 in expenses for every dollar they lose. Last, but not least, they can also improve compliance with practices like AML (anti-money laundering) and due diligence.

3. Treasury automation

Making a solid cash flow forecast in a world ridden with geopolitical and economic uncertainty is a daunting challenge, given the increasingly growing number of variables that could impact a business’ operation, from supply chain disruptions due to border closures to a foreign partner facing legal challenges due to poor labor practices.

At the same time, there is more and more data that companies need to deal with. Here’s where AI comes into play. By integrating AI-powered technologies with existing company systems, such as an ERP (Enterprise Resource Planning) and a CRM (Customer Relationship Management), executives can have clearer visibility and more precise forecasts with which to make decisions. AI can integrate historical data, market patterns, and customer behavior to provide better predictions and prepare a pro forma cash flow statement. At the same time, certain treasury tasks could be automated.

For example, if a currency in which we have sales is devaluing, AI can automate a treasury strategy to hedge that risk. Similarly, with the help of AI, a financial manager can know the levels of cash that are needed to operate the business, and automate short-term investments that can provide immediate liquidity yet generate additional financial gains for the company.

4. Open, integrated banking

Given that substantially more financial transactions are being conducted digitally, there is a need for open, integrated banking where a customer’s data can no longer remain exclusively within a bank’s own system.

With AI, companies can make financial management practices easier by verifying their multiple accounts and integrating that data within a single platform, allowing for seamless operations and giving individuals a holistic view of their financial situation.

For example, Plaid, an open banking API, enables a person to make transactions by connecting their accounts at different banks–like Interactive Brokers, Bank of America, and Wise. Some of the world’s largest banks are implementing open banking APIs, including Capital One, Barclays, and Nordea. By incorporating AI, open banking services can be made more secure, for example, by enhancing customer authentication, preventing fraud, and giving users personalized financial insights.

5. Buy Now Pay Later (BNPL-as-a-service)

Buy Now Pay Later services are becoming more popular. However, for a company or for a smaller bank, integrating these services into a platform can be costly and reduce its attractiveness.

By leveraging the capacities of AI, more companies can integrate BNPL services and acquire those customers who do not have the possibility of paying cash right away. With AI, businesses can, right away, detect a potential borrower’s eligibility for credit, and even provide personalized recommendations to a BNPL active user–who is in good standing–for future products.

6. Cross-border payments

According to the World Bank, sending a remittance costs approximately 6.20% of the total amount sent. This is huge, especially considering that most recipients of remittances are located in developing countries. Think about this. You send $100 to a loved one in Nigeria, or in Thailand, and they only receive $94. This affects them right away, and this is why the World Bank has set the target of reducing the total cost of remittances to 3 percent.

To do this, fintechs can be of great help. First and foremost, because they don’t have the behemothic infrastructure of, for example, Western Union. However, there are still many legal and regulatory challenges that cross-border payment companies need to deal with, and these could be optimized by capitalizing on AI and DeFi usage. For example, DeFi can help to reduce transaction costs, and AI may help to distribute the technology globally and make it risk-free and fully transparent, which would help fintechs offer a more affordable service. They can also enhance security and even assist with predicting currency rates to make cross-border transactions more efficient.

7. Social finance

Some studies show that we are more likely to achieve our goals when we share them with others. In finance, this has created a boom called social finance–not to be confused with the social enterprise vertical also named that way–which allows people to collaboratively save for shared goals.

For example, if a group of friends has the intention of traveling to the next FIFA World Cup, an AI-powered app can facilitate all of them to optimize target cost and to share a specific account for that purpose, or to integrate their savings account into one platform in order to measure progress. Then, AI can help them attain their goals by identifying patterns and giving them insights surrounding their financial behaviors. This increases the likelihood that they will meet their joint financial objective.

There is plenty of room for AI-driven innovations in this space, including automated and customized notifications, real-time communication with AI chatbots, automated transfers based on income cycles, and even AI-powered roboadvisors that can help the team members invest their money on autopilot for it to grow.

Final Thoughts

Even if many analysts and experts are talking about the potential doom of fintech, from my vantage point, it is not dead. As the examples above show, there are plenty of opportunities in fintech, and for those who understand the new rules of the game, these opportunities are more exciting than ever. This is because now, the sector has more emphasis on profitability rather than on exorbitant user acquisition, which is good for the overall sustainability of the venture. Also, with the incorporation of AI-driven technologies, the fintech sector can enhance its compliance with new regulations and provide a much-needed boost to many areas of the financial industry, including risk management, treasury, social finance, and cross-border payments.

Egor Savvin is a Partner of Alfin Ventures and a seasoned investment professional, with over 10 years of experience in private equity and venture capital. He has considerable expertise in a wide array of industries, including fintech, AI, web3 and climate tech.