Artificial Intelligence in fintech: challenges, best practices, highlights for future

Igor Izraylevych

7 min read

Artificial Intelligence in fintech: challenges, best practices, highlights for future

AI (Artificial Intelligence) is on course to transform the financial space. With that transformation, however, will come some complications as the industry adjusts and learns to define best practices around this dynamic technology. While there will be some time of transition needed, AI will define a bright new future for fintech that brings new value to the business and customer side of the industry. 

AI’s Big Challenge: Managing the “Threat”

Risk management is already part and parcel of fintech. The prevalence of private, customer data and the high stakes involved in financial exchanges make risk management a ubiquitous practice in the space. Over the last few years, the instances of fraud have gone down but total losses have gone up. Total fraud losses in 2019, according to research done by Javelin Strategy and Research, totaled $16.9 billion at banks, while instances of fraud went down by 1.4 million. That means criminals are getting smarter, and much of that may be due to their leveraging increasingly advanced technologies, including AI.

Addressing the Threat

The advent of AI in fintech brings with it a fresh challenge, driving individual financial institutions and regulatory bodies to explore new ways in which to manage the ‘threat’ of AI.

How exactly does AI act as a ‘threat’ in fintech? They vary from low-risk scenarios to the highly problematic. On the low-risk end, one can imagine a chatbot in a CS use case “tricking” a customer into thinking it’s a human being. High-risk scenarios might involve violating a customer’s basic rights to privacy or using AI-enabled manipulation techniques to influence financial decisions. 

The European Union has already taken steps to mitigate these risks around AI in fintech. A series of introductory rules recently defined by the governing body are some of the first regulations in the world to define how AI is used in the financial services sector. 

The AI Intelligence Act, drafted by the EU in early 2021, breaks down risk use cases associated with artificial intelligence into a tiered pyramid. The use cases at the top and the bottom of the pyramid are the ones that have the most significant impact on fintech. At the ‘top’ of the pyramid are rules that prohibit any use of AI that could subliminally or directly manipulate a human, including so-called “deepfakes.” The base of the pyramid addresses transparency in fintech applications of AI; in other words, if a financial institution leverages a chatbot, for example, in customer service use cases, the customer must be given a clear indication that they are engaging with AI and not a person. 

AI as a Social Entity

An interesting subcategory of risk related to AI writ large and AI in fintech is that AI may actually end up functioning as a biased entity in our society. Why is this? For one, those biases already exist in the data the AI parses. Additionally, algorithms are, by nature, discriminatory in that they are designed to identify categories and filter out based on unwanted criteria. As Dr. Garfield Benjamin, a researcher at Solent University looking into AI as a social entity put it, “The whole point of algorithmic decision-making is to discriminate – to judge people according to certain criteria like where they live, their age, their occupation.” 

What has already been seen with AI is that this tendency has created a social bias in certain use cases. A recent study published in an international partnership between universities in the U.S. and South Korea established that social biases, including racism and sexism, are already defined within robots that leverage AI. 

What does this mean for fintech? Imagine this use case: AI is used to push out certain financial products to certain groups. A biased AI may exclude marginalized groups from these products. This has already happened in the social media space, where women and African Americans have been excluded from ad displays for higher-value products. 

As rules and regulations continue to develop around AI in fintech, vendors and regulating bodies alike will need to ensure that protections against discrimination exist, ensuring a fair, financial landscape for any human interacting with AI-driven products. 

Malicious Use of AI

Since the advent of the internet and digital applications, cybercrime has been a central threat to the fintech space. Now with AI in the mix, these malicious incursions are getting even more complex. 

One way in which AI aids malicious incursions is by adding new levels of complexity to traditional techniques used by hackers. A recent demonstration at DEF CON showed that a single algorithm could exploit several vulnerabilities in a system. The open-source AI tool developed by Dan Petro and Ben Morris was able to execute web penetration of a system without any extant knowledge of that system.  AI-based tools have also started appearing in the crypto space, impacting trades and markets. 

To counteract these malicious incursions, financing institutions will need to leverage their own AI use cases as early as they can in the digital banking lifecycle. AI will speed up the threat identification process, replacing human-driven, manual work. Potential use cases include leveraging AI-driven systems to:

  • Speed up verification checks and enhance KYC measures
  • Enhance screening of clients against watch lists
  • Engage in more effective transaction monitoring to identify incursions early in the cycle

While AI does have malicious applications, fintech can gain the upper hand by implementing its own AI-driven protections as soon as possible.

The Fintech Customer and AI

Now, on to the positives. One significant highlight in the future of AI in fintech is how much value it will bring to the customer experience. Artificial intelligence is positioned to extend a never-ending list of solutions that streamline the customer experience and give fintech companies a competitive edge when it comes to customer service. 

As will be explored in greater detail below, one immediate and personal way in which the customer in the fintech space will be touched by AI is in the form of the chatbot. AI-driven chatbots will be a first line of defense for customer service departments, efficiently triaging cases and funneling them as needed to human CS agents. 

The onboarding experience will be shorter and easier for customers with the advent of AI. AI will streamline customer verification, for one, making opening an account much faster for the average consumer. Finally, AI’s efforts against malicious attacks will provide financial customers with an additional and powerful line of protection against a range of incursions, including data theft. 

Fintech’s Future with AI

Artificial Intelligence in fintech: challenges, best practices, highlights for future - photo 2

The future is bright for AI in financial services if fintech firms take the right actions and implement them now. This technology will drive a massive increase in opportunities and revenues. According to a McKinsey study, it is estimated that AI will create up to one trillion US dollars in value add for international banks, for example. Below are just some of the ways in which that will happen. 

Innovation Through Software Development

Fintech companies looking to ride the wave of AI as its use cases increase in the space will benefit from partnering with seasoned software development companies. We at S-PRO have already begun exploring multiple areas of digital transformation in fintech, as well as in other data-sensitive, data-rich industries such as healthcare and energy. Our Fintech and AI software development services for allow fintech companies to develop bespoke solutions that answer directly to their business needs and customer demand.

Artificial Intelligence in fintech: challenges, best practices, highlights for future - photo 3

How AI-Driven Chatbots Will Accelerate Fintech

Chatbots will be central in this new future in fintech, impacting the customer experience at several points in the customer cycle. Chatbots will bring an automated conversational component to websites and applications, messaging interfaces, social media and voice assistance. Gartner estimates that 80 percent of consumer apps will include chatbot components by 2023, allowing businesses to deepen customer engagement.

Artificial Intelligence in fintech: challenges, best practices, highlights for future - photo 4

AI-driven chatbots will be able to introduce hyper-personalization into the CS mix, leveraging a customer’s native language, introducing complex financial topics in an accessible and friendly way, and creating a more comfortable space for customers in general. These bots will also be able to take on a range of automated tasks at a financial institution. Everything from resetting a password to executing online payments can be overseen by a “friendly” chatbot that efficiently guides the consumer through a process.

Given the opportunities on the horizon, what are some of the trends gaining momentum in AI in fintech? Let’s walk through some of the highlights. 

Predictive Analytics

Making the best financial decisions requires analysis of data. Now that AI is on the scene, fintech development firms can develop solutions that leverage predictive analytics to drive better financial decisions for their customers. 

How would this play out in the real world? As part of an online banking app, a financial institution could leverage AI-driven analytics to push out suggestions to consumers. The AI could analyze a customer’s spending habits, for example, then make recommendations. This would not only impact a customer’s daily financial decisions but also longer-term goals related to savings and retirement. 

Generative AI

Another trend positioned to make a big impact in fintech is generative AI.  Generative AI leverages AI and ML to parse data, generate insights from that data, and then push out operational decisions to the C-suite. A CIO at a fintech firm could use this technology to suggest solutions that will better drive revenue growth, according to VP Moutusi Sau of Gartner. Additional fintech use cases include using generative AI in detecting fraud, building risk factor models, and predicting trade trends. 

Increased Automation

Manual processes and analog workflows have been a problem in the finance sector for decades now. Perhaps no other industry has stayed married to the analog as finance. AI used in tandem with RPA, or robotic process automation, will go a long way toward eliminating the manual in the space. AN RPA is a collection of bots that execute repetitive workflows and then transfer the information to human staff, who can then review the tasks and approve them more efficiently. 

AI-Driven Investments

Brokerages have long been tasked with finding innovative and consistent ways in which to make financial recommendations. Toeing the line too closely leads to minimal returns, while bold moves can expose customers to risk. With AI-powered tools, financial advisors can now provide data-driven, algorithm-based advice to their investors. This will mitigate exposure and risk, while also streamlining the entire process. 

Improved Authentication

Finally, and perhaps most importantly, AI is ideally positioned to enhance authentication in financial transactions. Previously, the authentication process involved multiple factors, creating a long and arduous workflow. With AI-driven solutions, authentication can now take just a fraction of the time by leveraging digital data such as scanned iris images or fingerprints. Financial institutions will be able to onboard new customers much more quickly while also protecting themselves from KYC violations and fraud.

Looking for a technical partner?
Contact us to discuss your project with experienced engineers
Get in Touch
ellipse logo

AI – a Future of Innovation for Fintech

The next several years will be interesting as fintech companies, financial institutions, and banks navigate a new technological terrain with AI. At the governmental level, policies will continue to evolve in real-time as regulation tries to keep pace with developing tech. From the business side, any entity in fintech needs to begin exploring their options, making AI work for them instead of against them.

Partnering with software developers such as S-PRO is the best way forward. We develop solutions that leverage AI dynamically, improving workflows, enhancing security, and streamlining the customer experience. Whether the starting point is a chatbot or a full-service platform, start exploring how a company like S-PRO can help your fintech endeavors stay ahead of the curve. Contact our team today to learn more about how you can innovate a new AI-driven future for your company.


Igor Izraylevych