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GenAI in Fintech: Exploring Its Game-Changing Possibilities

Paulina Twarogal

Content Specialist

Andrzej Puczyk

Head of Delivery

Every generation witnesses breakthrough technologies that change the way we live and work. Think back to the late ‘90s when the internet and smartphones burst onto the scene. Initially met with skepticism, they eventually transformed industries and careers worldwide.

Twenty-five years later, and who can possibly imagine a world without them? But this year has marked another significant milestone: the emergence of generative artificial intelligence (GenAI), a significant leap forward in AI technology.

ChatGPT, Bard, DALL-E, Midjourney, DeepMind…Does any of these ring a bell? You’re likely familiar with at least one of them, perhaps ChatGPT, a publicly available GenAI tool able to converse with users. Released by OpenAI in late 2022, it’s the kind of thing that changed the world overnight. It made AI accessible to organizations and individual users like never before.

The outcome? GenAI is not only reshaping numerous industries but has also found a central role in the fintech sector, opening doors to an era filled with potential and opportunities.

In this first part of our three-part series, we’ll explore what GenAI really is, how it works, and what game-changing solutions it brings to the fintech industry.

What is GenAI and how does it work?

Imagine for a moment—what if artificial intelligence could not only solve puzzles but also invent entirely new ones? That’s the essence of GenAI, a fascinating branch of AI that pushes the boundaries of creativity.

GenAI uses the power of algorithms and models to produce new and original content. While traditional AI systems rely on pre-existing rules and patterns, generative AI takes things to the next level. Its models learn from extensive data sources and then turn that knowledge into entirely new outputs.

GenAI models can generate text, images, sounds, and many other forms of content. What’s truly remarkable is that their creations are often indistinguishable from human-made content. This makes generative AI not just a tool for content generation but a catalyst for innovation.

The impact of GenAI on fintech



The impact of GenAI on the fintech industry is clearly visible. Take a look at the numbers below. They speak for themselves. 

The AI market in fintech is expected to reach $31.71 billion by 2027, growing at an impressive rate of 28.6%. It’s not just a future trend; artificial intelligence is already being used in many different cases. According to the Cambridge Centre for Alternative Finance, a whopping 90% of global fintech companies have already embraced AI and machine learning.

When it comes to generative AI, recent forecasts are equally promising. By 2032, it’s predicted to exceed $6.2 billion in the fintech market, from its $865 million value in 2022. That’s a remarkable increase, isn’t it?

GenAI holds the promise of transforming the fintech landscape in several ways. It’s not just about improving customer service and streamlining processes but also mitigating risks and enhancing decision-making.

Game-changing possibilities offered by GenAI in fintech 

All the hype and big claims aside, you might still be wondering how generative AI relates to fintech in practice. And so, without further ado, let’s get straight to the real-life examples.

Fraud detection and prevention



As the fintech industry continues to thrive, so does the unfortunate rise in fraudulent activities. Perpetrators are continuously innovating new methods to breach digital financial systems, resulting in a steady rise in identity theft and money laundering cases.

The truth is that the battle against fraud has never been more critical. Not only did the fintech sector see a 15% increase in the rate of identity fraud but also a staggering 92% rise in attempted payment fraud cases from 2021 to 2022. That means that the need for solutions to safeguard customer data is more urgent than ever. 

Hopefully, GenAI is there to help. By being able to analyze large volumes of data, it can identify potential fraud patterns and develop predictive models to flag any suspicious activity in real time. As a result, generative AI could help banks and fintech organizations protect their systems and customer accounts. A study by IBM found that employing GenAI can reduce fraud losses by 50%.

For example, Mastercard, Visa, PayPal, and Bank of America have already used GenAI to mitigate fraud. In the case of Visa, its real-time payment fraud monitoring system, known as Visa Advanced Authorization (VAA), helped prevent around $27 billion in fraudulent transactions. By using various AI and machine learning techniques, VAA system can quickly assess whether a transaction is likely to be fraudulent in just 300 milliseconds.

Risk assessment

In today’s fast-paced and dynamic financial landscape, staying ahead of risks is crucial for fintech companies. 

Generative AI can analyze historical data, market trends, and other important information to assess the risk that comes along with financial transactions and investments. It can also simulate various financial scenarios to help organizations in anticipating and mitigating risks.

A study by Deloitte revealed that GenAI could help fintech companies identify and mitigate risks even 10% more effectively compared to traditional methods.

While this number might not appear impressive at first glance, it’s important to keep in mind that we’re only scratching the surface of AI’s impact on the financial world. As AI continues to advance, we can anticipate much more significant improvements in the years ahead.

Let’s take Planck PLUS as an example—a tool that’s set to revolutionize business risk analysis. Planck’s platform aids commercial underwriting and risk assessment by converting real-time data into actionable insights for insurance carriers. This enables underwriters to access hidden risk information, make informed decisions, and reduce losses. 

As the VP of product strategy in Planck says: “It’s like having a veteran underwriter sitting next to you.”

Customer service automation



In the business of safeguarding people’s finances, delivering exceptional customer care is non-negotiable. And one of the fundamental aspects of achieving this is ensuring round-the-clock availability for customers. This, however, turns out to be the Achilles heel of many fintech companies. Why? 

Well, excessive workload, resource limitations, operational constraints, or the need for employee rest and shift schedules…These are just a few of the many reasons why companies struggle to deliver 24/7 support and fast resolutions. And, let’s face it, when it comes to finances, customers don’t like to wait. They want their problems sorted out right away, no matter the time.

Using GenAI to automate customer service processes, like employing virtual assistants, seems to work well in this case. A study by Gartner found that by 2026 GenAI could automate up to 30% of customer service tasks.

Of course, not every interaction can be completely automated, particularly when handling sensitive customer information. However, GenAI models can be used to automate recurring tasks and resolve low-complexity issues. This, in turn, will free human agents from dealing with basic tasks and allow them to concentrate on more complex requests. 

To illustrate how it works in real life, let’s examine Bank of America’s virtual financial assistant, Erica. Simply speaking, Erica is an AI-powered virtual assistant integrated into their mobile banking app. It relies on its natural language processing abilities to provide customers with human-like responses, offering valuable assistance whenever needed. 

Impressively, as of October 2022, Bank of America reported that over 32 million customers have actively engaged with this digital personal assistant since its launch. This makes Erica one of the most favored AI tools among banking customers in the United States.

Personalized financial advice 



Investors often look for tailored financial guidance that matches their specific goals and risk tolerance. By analyzing their individual financial data, spending habits, risk preferences as well as market trends and economic conditions, GenAI can offer personalized advice and recommendations. It can provide strategies to enhance savings, optimize debt repayment, and pinpoint cost-saving possibilities. This will make it easier to make smart choices.

A recent survey of American consumers conducted by the CFP Board reveals that nearly 1 in 3 investors is open to receiving financial guidance directly from generative AI programs. And they’re willing to do this without verifying such advice with any other source. This clearly highlights the growing trust in AI-driven recommendations. 

Brex Finance Assistant is a good example of how generative AI can offer personalized financial advice. This ChatGPT-style CFO tool, developed by fintech company Brex and set to launch in 2023, acts as a smart financial assistant. It provides CFOs with valuable insights into their budgets and spending, tracks trends, and offers comparisons with businesses in the same industry. With this tool, CFOs can make informed decisions to foster business growth.

Another noteworthy example is JPMorgan Chase’s IndexGPT, expected to launch between 2026-2027. It will enable customers to explore various investment options in the market, make informed decisions based on their financial status, and receive guidance on future investments in stocks and funds.

Loan processing 

Loan processing is rather a cumbersome task, often involving a mountain of paperwork and extensive manual effort. This is where generative AI steps in, offering a solution. By analyzing a user’s financial data, credit score, and other relevant factors, the loan processing procedures become much faster and more accurate. This, on the other hand, decreases the time and expenses.

Wondering how it all comes to life in practical scenarios? Let’s explore some real-world examples:

AXIS by AIO Logic is a commercial loan management platform that uses GenAI to assess risks, determine interest rates, and create tailored loan structures. It’s said to achieve a significant reduction in both time and costs compared to legacy systems, possibly up to 5 times higher.

Ocrolus might be yet another example of how GenAI can streamline loan processing. Ocrolus is a software that leverages generative AI to automate document processing for digital lenders. This innovative technology not only accelerates document analysis but also significantly reduces the workload on human analysts, ultimately driving operational efficiency and business growth.

In conclusion

The potential of GenAI in fintech is enormous. We’ve just discussed its game-changing possibilities, examining how it currently revolutionizes various aspects of fintech, from detecting fraud and managing risks to automating customer service and delivering personalized financial guidance.

As for the future, let’s brace ourselves as there is yet a lot to come.

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