According to Grand View Research, the volume of AI tools in the fintech domain has already reached a shocking $9.45B just in 2021. And it shows no sign of stopping. Experts predict that from 2022 to 2030, the market will increase at an unbelievable average annual rate of 16.5%.
It is hardly surprising, as we are already watching tech giants like Microsoft, Google, Salesforce, Intel, and Amazon harnessing AI’s power to captivate the market.
So back to fintech – where exactly do we see disruptions? And where else to expect them in the future? We asked fintech opinion leaders, advisors, and experts to share their visions on the future of AI in fintech.
So let’s see!
A small market recap
Despite the global economic downturn, fintech keeps growing. According to CB Insight, 983 deals totalled $15B in Q1’23 (+55% QoQ). That said, early-stage fintech startups make for the lion’s share of this amount – 72%, which is the highest number the industry has ever seen in Q1.
Although the venture capital market slump has taken a toll on some particular fintech domains (like well tech), areas like payments, digital lending, insurance, and capital market technologies received the most funding.
This success is attributed mainly to AI – in 2022, investors gave $4.5B to AI-powered products, while in 2018, it was only $408M.
“Initially, AI helped fintech firms automate processes, analyse threats, reduce fraud, and improve the customer experience. All these benefits have brought about better efficiency and higher margins.
However, AI can go further. Enhancements in credit scoring or loan prediction in lending, advanced algorithmic in trading or Chatbots in whatever segment are now useful deployments.
Besides data-driven segments such as Insurtech or Wealth Management, AI can automate their analysis for a more accurate and efficient decision-making process. The opportunity is immense, and the industry should harness its invaluable applications.” – says Jose A. Somalo, Startup Consultant and Fintech Advisor.
So, it is evident that AI integration is no longer a fancy whim for fintech startups but a must for startups that seek a competitive edge.
“AI can boost fintech apps’ Unfair Advantage and vastly increase the products’ competitive edge.”, – says Yan Likarenko, Product Development Manager at Uptech.
So how exactly can fintech harness this breaking technology? Here are the main ways to do it.
Enhanced fraud detection
Fraud has been a severe problem in the financial sector, which costs businesses billions. Moreover, reliable security is a cornerstone of user trust, essential to the app’s success.
AI can process volumes of data via machine learning and deliver unique security solutions to companies. Thus, AI algorithms can track suspicious behaviour and spot fraudulent activities within the user’s account.
“Machine learning models can learn from historical data to identify patterns, anomalies, and potential risks, thereby enhancing security measures and protecting both businesses and consumers.” – Luis D. Ferreira, Fintech Expert and Crypto/Web3 Enthusiast.
AI-powered security systems will contribute mainly to user trust, which is a factor that can hardly be overestimated when talking about financial security.
Both user acquisition and retention rates are key metrics investors look at when funding a startup. So investing in AI-driven security solutions brings you a win in user increase and capital fundraising.
On this, Dima Kovalenko, CEO & Co-founder at Uptech and cofounder at Rozmova comments:
“Users join apps that promise data security and stick with the ones that provide it. In fintech you can hardly overestimate the value of user’s trust – customers will stay with the service that they rely on.
Overlooking the factor of trustworthiness in your relationships with customers is a mistake that can cost you new investments from fundraisers.
Solid security is a core in building trust with users and consequently gaining and retaining customers. “
Personalisation in user experience
Personalisation is becoming the leading trend for fintech, especially among neo banks startups. Customers, active users of Chat GPT, expect to receive tailored AI-driven financial suggestions and experiences in their mobile banks.
“Conversational AI agents have the potential to revolutionise the Fintech buying experience by reintroducing trust, enhancing, understanding and reaching the underserved by bringing the technology closer to the users. Users can engage in conversations with these AI agents to receive financial education, gain clarity on various products, seek assistance with onboarding processes, and ultimately build trust.” – comments Romain Servant, Financial Expert and Startup Advisor.
The most popular personalisation tool is chatbots. While round-the-clock chatbots have been in the industry for a while, AI can take it to another level. Thus, leveraging natural language processing (NLP), AI can personalise customer assistance by analysing their requests and previous experience using the app and understanding the user’s intentions.
On that Luis D. Ferreira says:
“By analysing customer preferences and historical data, AI can offer tailored banking solutions, improving customer satisfaction and loyalty”.
Virtual assistants can also suggest tailor budgeting advice or investment opportunities, and other highly customised services that meet personal needs of customers.
“AI gives grandiose opportunities in terms of personalised services. But it is important to strike a balance between machine-power service and human interaction. It is still necessary to let users connect with human representatives. A balanced blend of AI and human touch can result in a seamless custom experience, which includes both efficiency driven by machines and empathy stemming from a human.”, – says Yan Likarenko.
Credit risk evaluation
AI can make credit assessments by analysing a vast amount of public information available about the client – including financial records, credit history, and even social media profiles.
For example, ZestFinance, an AI-powered lending app, evaluates potential lenders’ creditworthiness by analysing data such as employment profiles, web search history, and social media activity.
Financial market forecasts
Data-driven investment decisions are totally no news – it has been around for a few years already. Thus, in 2018, for example, thanks to computer generated strategies the quant hedge fund industry closed at $1T.
The difference is that these days the computer-driven take on investment no longer triggers criticism, but rather incites interest. For example, even Wall Street already uses AI in market analysis, while crypto enthusiasts also use the power of AI in crypto trading.
“AI-powered trading platforms can make intelligent predictions, automate trading strategies, and execute trades with minimal human intervention. This enables traders and investors to make data-driven decisions, optimise trading performance, and potentially reduce risks”, – notes Luis D. Ferreira.
Compliance
Compliance is a big deal in the fintech industry. As the amount of regulations grows annually, it is becoming more and more challenging to keep up with all the emerging rules.
Thankfully, AI is here to help. AI-driven tools can track transactions and user behaviour, ensuring entities comply with the anti-money laundering (AML) and know-your-customer (KYC) regulations.
For instance, Tookitaki, a fintech startup from Singapore, analyses user behaviour and spots any nontypical suspicious activity that can be money laundering.
“Using AI in the AML process can significantly optimise costs and bear the risks to a minimum” – Dima Kovalenko.
Balance between AI and human touch
AI will definitely take us far. Customers still need a human touch in their mobile banking services, which you can’t substitute.
“AI-powered technology can enhance user experience in fintech on 3 different levels at once, offering convenience, personalisation, and security. Banks can provide customers with a more engaging and tailored service by following a user-centric approach in development and leveraging AI to implement it. This, in turn, will drive their user acquisition and retention rates, making them more attractive investment opportunities for venture capitalists.” – Yan Likarenko, Product Development Manager at Uptech
Also, data privacy is also an important factor to keep in mind when leveraging AI for your fintech business.
“AI has not had its Kodak moment yet in the Fintech space, as it ultimately needs to balance the user experience with data privacy. “ – adds Romain Servant.
Conclusion
AI tools have massive potential in the financial industry. Moreover, they’re already successfully used. Implementing more of these tools can bring about crucial changes in the market. Whether someone likes it or not, the progress is unstoppable. The best approach here is to make the most of the AI-driven solutions.
Andriy Bas is a Ukrainian startup entrepreneur and cofounder of Uptech Product Studio.