Author

Dan Brightmore

Published

13 March 2025

Estimated Read time

5Mins

Fouzi Husaini, Chief Technology & AI Officer at Marqeta, answers our questions about Agentic AI and its applications for businesses

Agentic AI is emerging as the leading AI trend of 2025. Industry figures are hailing Agentic AI as the broadly transformative next step in GenAI development. The year so far has seen multiple businesses release new tools for a wide array of applications. 

The technology combines the next generation of AI tech like large language models (LLMs) with more traditional capabilities like machine learning, automation, and enterprise orchestration. The end result could lead to a more autonomous version of AI: Agents. These agents can set their own goals, analyse data sets, and act with less human oversight than previous tools. 

We spoke to Fouzi Husaini, Chief Technology & AI Officer at Marqeta about what sets Agentic AI apart whether the technology really is a leap forward in terms of solving AI’s shortcomings, and how Agentic AI could solve business problems.

1. What makes AI “agentic”? How is the technology different from something like Chat-GPT? 

“Agentic refers to the type of Artificial Intelligence that can act as agents and on its own. Agentic AI leverages enhanced reasoning capabilities to solve problems without prompts or constant human supervision. It can carry out complex, multi-step tasks autonomously.

“GenAI and by extension Large Language Models, the most famous example being ChatGPT, require human input to solve tasks. For instance, ChatGPT needs user prompts before it can generate content. Then, sers need to input subsequent commands to edit and refine this. Agentic AI has the capability to react and learn without human intervention as it processes data and solves problems. This enables it to adapt and learn much faster than GenAI.”

2. Chat-GPT and other LLMs frequently produce results filled with factual errors, misrepresentations, and “hallucinations”, making them pretty unsuited to working without human supervision – let alone orchestrating important financial deals. What makes Agentic AI any better or more trustworthy? 

“All types of AI have the possibility to ‘hallucinate’ and produce factually incorrect information. That being said, Agentic AI is usually less likely to suffer from significant hallucinations in comparison to GenAI. 

“Agentic AI’s focus is specifically engineered to operate within clearly defined parameters and follow explicit workflows, making it particularly well-suited for having guardrails in place to keep it on task and from making errors. Its learning capabilities also allow it to recognise and adapt to its mistakes, ensuring it is unlikely to hallucinate multiple times.”

“On the other hand, GenAI occasionally generates factually incorrect content due to the quality of data provided, and sometimes because of mistakes in pattern recognition.”

“In fintech, Agentic AI technology can make it possible to analyse consumer spending data and learn from it, allowing for highly tailored financial offers and services that are more accurate and help to create a personalised finance experience for consumers.” 

3. How could agentic AI deployments affect the relationship between financial services companies and their customers? What about their employees? 

“The integration of Agentic AI into financial services benefits multiple parties. First, 

integrating Agentic AI into their offerings allows financial service companies to provide their customers with bespoke tools and features. For instance, AI can be used to develop ‘predictive cards’. These cards can anticipate a consumer’s spending requirements based on their past behaviour. This means AI can adjust credit limits and offer tailored rewards automatically, creating a personalised experience for each individual.

“The status quo’s days are numbered as consumers crave tailor-made financial experiences. Agentic AI can allow fintechs to provide personalised financial services that help consumers and businesses make their money work better for them. With Agentic AI technology, fintechs can analyse consumer spending data and learn from it. This allows for more tailored financial offers and services.   

“As for employees, Agentic AI gives them the ability to focus on more creative and interesting tasks. Agentic AI can handle more routine roles such as data entry and monitoring for fraud, automating repetitive tasks and autonomous decision making based on data. This helps to reduce human error and enables employees to focus more time and energy on the creative and strategic aspects of their roles while allowing AI to focus on more administrative tasks.”

4. How would agentic AI make financial services safer? 

“Agentic AI has the capability to make financial services more secure for financial institutions and consumers alike, by bringing consistency and tireless vigilance to critical financial processes. With its ability to analyse vast strings of information, it can rapidly identify anomalies in spending data that indicate potential instances of fraud and can use its enhanced reasoning and ability to act without human prompts to quickly react to suspicious activity. 

“While a human operator will be susceptible to decision fatigue, an AI agent could always be vigilant and maintain the same high level of precision and alertness 24/7. This is vital for fields like fraud detection, where a single missed signal could lead to significant consequences.

“Furthermore, its capability to learn without human interaction means that it can improve its ability to detect fraud over time. This gives it the ability to learn how to identify new types of fraud, helping it to adapt as schemes become more sophisticated over time.” 

5. What kind of trajectory do you see the technology having over the next year to eighteen months?

“In fintech, Agentic AI integration will likely begin in the operations space. These areas manage complex, but well-defined, processes and are perfect for intelligent automation. For instance, customer call centres where human agents usually follow set standard operating procedures (SOPs) that can be fed into an AI system, which makes automation easier and faster than before.

“In the more distant future, I believe we will see Agentic AI integrated into automated workflows that span entire value chains, including tasks such as risk assessment, customer onboarding and account management.” 

  • Artificial Intelligence in FinTech

Author

Nicholas Holt

Published

29 October 2024

Estimated Read time

4Mins

Nicholas Holt, Head of Solutions and Delivery, Europe, Marqeta on how AI has the potential to revolutionise payments

The financial services sector has witnessed a profound transformation over the past two decades. It has been propelled by technological advancements. From online banking to mobile-first platforms like Revolut and Monzo, the industry is continuously evolving. The integration of Artificial Intelligence (AI) into financial services is set to push the boundaries even further. Offering enhanced convenience and changing how we manage our money.

AI offers the ability to process and analyse vast amounts of data in real-time. It promises to make financial services intuitive, intelligent, and personalised to individual needs. And it can also help to make it more secure.

AI-Powered Personalisation

AI can interpret a consumer’s transaction history and spending patterns to create tailored financial recommendations. These include optimising payment methods, choosing better reward programmes, or suggesting savings opportunities. This degree of personalisation is far more sophisticated than the broad, one-size-fits-all approach currently offered by banks.

The technology can enable ‘predictive cards’ to leverage machine learning algorithms to set personalised credit limits and rewards based on an individual’s financial behaviour. By predicting future needs, AI-powered tools can offer a more holistic view of one’s finances. They can improve financial literacy and promote better financial decision-making.

Consumers are increasingly warming to the idea of AI in financial services. According to Marqeta’s 2023 Consumer Pulse Report, 36% of consumers in the US and the UK expressed interest in using AI tools to help manage their finances. This figure rose to over 50% for consumers under 50, indicating a clear demand for personalised AI-driven solutions.

Unlocking Access to Credit

Access to credit is a significant factor in financial inclusion. AI has the potential to expand this access by transforming how creditworthiness is assessed. Traditionally, credit approval processes have relied heavily on limited data points, such as a person’s credit score and income. However, AI can analyse a broader range of data, from spending patterns to social media behaviour. This can provide a more nuanced assessment of an individual’s creditworthiness.

By using advanced machine learning models, AI can process this data at incredible speeds. This allows more people to be approved for credit faster and with greater accuracy. It can be particularly beneficial for individuals who may have struggled to secure credit through traditional methods, such as younger consumers or those without a lengthy credit history.

Generative AI (GenAI), which builds upon traditional AI by predicting and creating entirely new behaviours and patterns, also holds promise in this area. As the use of GenAI tools grows, we can expect more tailored financial products that respond to each consumer’s unique needs. Moreover, this could include personalised loan offerings or dynamic credit options that adapt in real-time to a person’s financial situation.

Fighting Fraud

While personalisation is one of AI’s most exciting applications, its ability to detect and prevent fraud is another crucial benefit. Fraud detection is a near constant battle across financial services, with millions of transactions processed every minute across the globe. Identifying suspicious activities quickly and accurately is essential for maintaining trust and security.

Machine learning algorithms are adept at spotting irregularities that might be missed by human analysts or even traditional software. Additionally, these systems can identify patterns that indicate potential fraud and alert financial institutions instantly, allowing them to take swift action.

Furthermore, as fraud techniques evolve, AI systems will continuously learn and adapt, staying one step ahead of cybercriminals. This capacity to evolve will make AI an invaluable asset in the fight against fraud.

AI and Embedded Finance

Embedded Finance, the process of integrating financial services into non-financial platforms, has already begun reshaping how consumers and businesses interact with money. AI is set to accelerate this trend, enhancing the capabilities of embedded financial tools with real-time data processing and hyper-personalisation.

For instance, businesses could use AI-powered embedded finance solutions to offer tailored payment options at checkout based on a customer’s purchasing behaviour. This could include personalised financing options, such as Buy Now, Pay Later (BNPL) services, or optimised rewards based on previous transactions. Companies like Marqeta are already exploring AI’s potential to elevate embedded finance, making these interactions seamless and highly personalised.

The Future of Finance

Financial services in 20 or just 10 years from now will likely be unrecognisable compared to today. AI will play a central role in shaping this evolution. Consumers and businesses can expect a future where financial products are deeply integrated into everyday life. However, not as separate, standalone services, but as seamless, invisible enablers of transactions and financial management.

GenAI will become increasingly sophisticated, offering predictive insights that can help consumers manage finances with greater precision. For businesses, AI-driven solutions will enable more efficient operations, cost reductions, and enhanced customer engagement through personalised offerings.

In this future, consumers will enjoy unparalleled convenience and flexibility. Payments, credit, and financial planning will be customised to fit the individual, with AI continuously learning and adapting to offer better recommendations and insights. This will lead to greater financial literacy, broader access to credit, and improved financial security. Additionally, financial service providers will gain much greater control over fraud and other security challenges.