When Willie Sutton, once certainly one of America’s most wanted fugitives, was asked why he robbed banks, his response was remarkably easy, “Because that’s where the cash is.”
This is similar answer that could possibly be given to those that inquire concerning the growing tendency towards regulation within the fintech sector, and who imagine that increasing laws could damage innovation in the sphere. That’s where the cash is, subsequently, the stakes are high, and more regulation will likely be there. This may probably occur prior to later, as Michael Hsu, Acting Comptroller of the Currency, said recently. Due to this fact, we are able to expect compliance to be on the forefront of the conversation, and to grow to be a priority for enterprise capitalists, CFOs, and other stakeholders alike.
Although the amount of fintech deals globally fell from $63.2 billion to $52.4 billion from H22022 to H12023, in addition to the stock prices of publicly-traded fintech declined, including Affirm, Block, PayPal, and SoFi, nevertheless, for my part, the sector is much from being dead and in actual fact, it still holds immense potential. First, despite the fact that EU and APAC fintech market was shrinking, the US fintech market experienced steep growth from $28.9 billion to $36.1 billion in the course of the same period. Second, the caveat is that to appreciate fintech potential, we first need to know that the principles of the sport have modified. While some years ago, the foremost focus for fintech startups–and for the enterprise capitalists that backed them–was to amass more customers, now, there may be a growing emphasis on profitability. And while there are still segments of fintech–like DeFi–which still operate in some form of liberal paradise without many regulations, there may be one technology that I imagine will radically transform the industry, and help it thrive despite the regulatory pressure.
This technology is AI, and listed here are seven verticals inside fintech that, from my perspective, are value watching due to their enormous potential.
1. Personalization
By leveraging generative AI to deploy chatbots and make enhancements to each the user interface (UI) and user experience (UX), in addition to to gather extensive volumes of information and detect accurate patterns, firms can personalize their financial services in order that they’ll meet a selected customer’s needs. This is a component of a bigger trend that’s happening across industries, given the improbable capabilities that AI offers for personalization.
Let’s keep in mind that money is something deeply personal, subsequently, with the ability to ultra-personalize the services that a firm offers can substantially catalyze its reference to its customers, and substantially improve conversion rates, which in turn enhance revenue. Banks and financial institutions can be, from my perspective, greater than willing to partner with a enterprise that helps them accomplish these goals.
2. Risk management
AI is totally redefining risk management. A study by KPMG identified three key abilities possessed by artificial intelligence systems which can be now being integrated by financial institutions, despite their initial reticence to evolve technologically. These include superior forecasting accuracy, improved variable selection processes, and better precision when segmenting.
Benefiting from these capacities, financial institutions can, for instance, have a clearer picture of their credit risk and their exposure to default, and make higher decisions when determining which subjects are worthy of credit. Also, they may improve their fraud detection processes, which already cost banks $4.36 in expenses for each dollar they lose. Last, but not least, they may also improve compliance with practices like AML (anti-money laundering) and due diligence.
3. Treasury automation
Making a solid money flow forecast in a world ridden with geopolitical and economic uncertainty is a frightening challenge, given the increasingly growing variety of variables that might impact a business’ operation, from supply chain disruptions attributable to border closures to a foreign partner facing legal challenges attributable to poor labor practices.
At the identical time, there may be increasingly more data that firms have to take care of. Here’s where AI comes into play. By integrating AI-powered technologies with existing company systems, comparable to 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 offer higher predictions and prepare a professional forma money flow statement. At the identical time, certain treasury tasks could possibly be automated.
For instance, if a currency through which we now have sales is devaluing, AI can automate a treasury technique to hedge that risk. Similarly, with the assistance of AI, a financial manager can know the degrees of money which can be needed to operate the business, and automate short-term investments that may provide immediate liquidity yet generate additional financial gains for the corporate.
4. Open, integrated banking
On condition that substantially more financial transactions are being conducted digitally, there may be a necessity for open, integrated banking where a customer’s data can now not remain exclusively inside a bank’s own system.
With AI, firms could make financial management practices easier by verifying their multiple accounts and integrating that data inside a single platform, allowing for seamless operations and giving individuals a holistic view of their financial situation.
For instance, Plaid, an open banking API, enables an individual to make transactions by connecting their accounts at different banks–like Interactive Brokers, Bank of America, and Sensible. A few of the world’s largest banks are implementing open banking APIs, including Capital One, Barclays, and Nordea. By incorporating AI, open banking services could be made safer, for instance, by enhancing customer authentication, stopping fraud, and giving users personalized financial insights.
5. Buy Now Pay Later (BNPL-as-a-service)
Buy Now Pay Later services are rising in popularity. Nevertheless, for a corporation or for a smaller bank, integrating these services right into a platform could be costly and reduce its attractiveness.
By leveraging the capacities of AI, more firms can integrate BNPL services and acquire those customers who wouldn’t have the potential for paying money immediately. With AI, businesses can, immediately, detect a possible borrower’s eligibility for credit, and even provide personalized recommendations to a BNPL energetic user–who’s in good standing–for future products.
6. Cross-border payments
In accordance with the World Bank, sending a remittance costs roughly 6.20% of the entire amount sent. This is large, especially considering that the majority recipients of remittances are situated in developing countries. Take into consideration this. You send $100 to a loved one in Nigeria, or in Thailand, they usually only receive $94. This affects them immediately, and because of this the World Bank has set the goal of reducing the entire cost of remittances to three percent.
To do that, fintechs could be of great help. Firstly, because they don’t have the behemothic infrastructure of, for instance, Western Union. Nevertheless, there are still many legal and regulatory challenges that cross-border payment firms have to take care of, and these could possibly be optimized by capitalizing on AI and DeFi usage. For instance, DeFi may also help to scale back transaction costs, and AI may help to distribute the technology globally and make it risk-free and fully transparent, which might help fintechs offer a more cost-effective service. They may 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 usually tend to achieve our goals after we share them with others. In finance, this has created a boom called social finance–to not be confused with the social enterprise vertical also named that way–which allows people to collaboratively save for shared goals.
For instance, if a gaggle of friends has the intention of traveling to the subsequent FIFA World Cup, an AI-powered app can facilitate all of them to optimize goal cost and to share a selected account for that purpose, or to integrate their savings account into one platform in an effort to measure progress. Then, AI may also help them attain their goals by identifying patterns and giving them insights surrounding their financial behaviors. This increases the likelihood that they may meet their joint financial objective.
There may be loads of room for AI-driven innovations on this space, including automated and customised notifications, real-time communication with AI chatbots, automated transfers based on income cycles, and even AI-powered roboadvisors that may also help the team members invest their money on autopilot for it to grow.
Final Thoughts
Even when many analysts and experts are talking concerning the potential doom of fintech, from my vantage point, it isn’t dead. Because the examples above show, there are many opportunities in fintech, and for individuals who understand the brand new rules of the sport, these opportunities are more exciting than ever. It’s because now, the sector has more emphasis on profitability fairly than on exorbitant user acquisition, which is sweet for the general sustainability of the enterprise. Also, with the incorporation of AI-driven technologies, the fintech sector can enhance its compliance with recent regulations and supply a much-needed boost to many areas of the financial industry, including risk management, treasury, social finance, and cross-border payments.