Artificial intelligence (AI) has rapidly infiltrated nearly every business sector. Finance, traditionally dominated by human expertise, is no exception. But how will we fare when algorithms begin to make the critical decisions?

As AI algorithms become increasingly sophisticated, it’s crucial to explore not only how AI will transform finance but also how it will work alongside humans. How will it reshape the industry’s future?

FAIRNESS AND TRANSPARENCY 

Fairness and transparency are crucial when considering AI in finance. Ali Abulhasan, Co-Founder & CEO at Tap Payments, says, “AI’s potential in finance is undeniable, but its ethical use is paramount,” He stresses that AI should not discriminate, and combating bias involves using diverse training data, regularly auditing AI models, and establishing clear procedures for addressing and correcting unfair outcomes.

Acknowledging the “black box” problem, Abulhasan highlights the need for AI decision-making processes to be understandable. This entails explaining how AI models operate, the data they use, and how they reach conclusions.

Lastly, when AI makes mistakes, someone needs to be responsible. “Robust governance frameworks, clear lines of responsibility, and channels for recourse are essential,” adds Abulhasan.

We’re diving into a landscape of opportunities and significant ethical challenges when discussing AI in finance. At the heart of it, there’s the risk of algorithmic bias, says Nameer Khan, Founder and CEO of Fils and Chairman of the MENA Fintech Association (MFTA).

AI models in finance can unintentionally reflect or amplify societal biases. For example, a credit scoring system might disadvantage certain groups if it uses biased historical data. This real concern could impact people’s lives by limiting their access to financial products.

Data privacy is a major concern, as AI systems handle vast amounts of sensitive information. The challenge is balancing data use for improved services with safeguarding privacy, as Khan emphasizes, “We can’t afford to compromise on data security. It’s non-negotiable in today’s digital age.” 

He suggests implementing rigorous bias testing, investing in explainable AI techniques, and establishing strong governance structures. He also emphasizes the importance of industry collaboration in setting standards and sharing best practices.

However, Renier Lemmens, Chairman at TransferGo & Divido and Former Group CEO at Geidea & PayPal Europe, explains that while many traditional processes and systems are neither fair nor transparent, AI research is advancing in developing models that can explain other models. This effort aims to make complex algorithms more understandable and accountable. Nonetheless, as AI continues to evolve, there’s a concern that our focus might shift. 

FINANCIAL INCLUSION 

AI is crucial in making financial services more accessible to traditionally underserved populations, says Imad Gharazeddine, Co-Founder & CEO at Mamo. By leveraging AI, banks and fintech companies can innovatively analyze data to develop products tailored to these groups.

“For example, AI can help develop alternative credit scoring models that allow individuals without a formal credit history to access loans. AI enables us to design financial products that meet people where they are. We can use AI to create solutions that are more inclusive and address the needs of those who have been left out of the traditional financial system. This approach can help bridge the gap and bring more people into the financial fold.”

Mohammed Al-Delaimi, co-founder at PayLater and founder and managing director at SkipCash, says AI-driven solutions enable flexible financing options, enhancing accessibility and affordability. This fosters a more inclusive financial ecosystem and drives regional economic growth. 

Abulhasan adds that businesses can tailor products like micro-loans and savings plans for underserved communities through data-driven personalization while developing innovative offerings like flexible payment options and alternative credit scoring models. 

AI further enhances credit access by accurately assessing creditworthiness, even for those without formal histories. Additionally, AI-powered automation reduces operating costs, allowing financial institutions to offer more affordable services and promote greater economic participation.

Khan says AI can provide new methods for assessing creditworthiness by leveraging alternative data—such as mobile phone usage or utility bill payments —enabling people without traditional credit histories to access loans.

“Moreover, AI can personalize financial services at a scale we’ve never seen before. It’s not just about offering advice or products but tailoring those offerings to each individual’s unique needs and circumstances.”

Robo-advisors now allow individuals with smaller investment portfolios to access high-quality financial guidance once reserved for the wealthy. In regions with limited banking infrastructure, AI-powered mobile apps provide essential services, using multilingual capabilities and natural language processing to ensure usability. However, addressing challenges like digital literacy is crucial to making these AI-driven tools accessible. Balancing innovation with protection for vulnerable populations is key to achieving true financial inclusion.

MANAGING CYBERSECURITY

AI is already widely used to detect attacks and fraud, says Lemmens. 

“The bad news is that the bad guys also use AI. We will see more rather than less fraud and cyberattacks at an organized or state-sponsored level in the near term.”

But Khan says cybersecurity is one area where AI shines. 

Financial institutions can detect and respond to threats in real-time with AI. AI can analyze vast amounts of data and spot unusual patterns that might indicate fraud or a cyberattack. “This is something traditional systems often miss.”

AI doesn’t just detect threats—it can also prevent them. For instance, in fraud prevention, AI systems can monitor real-time transactions and flag suspicious activity more accurately than older methods. Regarding authentication, AI-powered biometric systems provide a much higher level of security than traditional passwords.

But we can’t just set and forget these AI systems. Khan adds that cyber threats are evolving, so it’s important to continuously update and train these systems. 

“Human oversight is also crucial to complement the AI, ensuring we’re not relying on machines alone to protect us.”

Ihab Ayoub, Co-Founder at Nymcard, says AI can significantly enhance financial institutions’ cybersecurity by enabling them to harness vast amounts of transaction data to detect anomalies and potential threats in real-time through advanced pattern recognition. 

It also automates threat response and mitigation, reducing reaction times to cyber-attacks. Additionally, AI enhances risk assessment and prediction capabilities, allowing for proactive security measures. These AI-driven solutions offer more robust, efficient, and adaptive cybersecurity for financial institutions.

CREATING GREEN FINANCIAL PRODUCTS 

AI plays a key role in promoting sustainable finance. For example, it can assist financial institutions in developing green bonds or sustainable investment funds that attract environmentally conscious consumers. “AI can help us create products that meet financial goals and contribute to a healthier planet, aligning financial interests with environmental stewardship,” says Gharazeddine.

Additionally, Khan adds that AI is increasingly important in pushing sustainable finance by significantly contributing to ESG (Environmental, Social, and Governance) scoring. 

AI processes vast data from various sources to provide a comprehensive view of a company’s ESG performance, aiding investors in making more informed decisions. It also helps assess climate risks by modeling complex scenarios and predicting their potential impact on assets, enabling better risk management for financial institutions. 

AI optimizes site selection and performance prediction in renewable energy, enhancing project viability. Furthermore, AI supports the creation of innovative financial products, such as green mortgages or eco-friendly credit cards, that reward environmentally conscious behaviors.

Khan says, “As we develop these tools, it’s crucial to ensure transparency and avoid practices like greenwashing, where companies might overstate their sustainability credentials.”

Lastly, AI tools can identify potential fraud in carbon markets by analyzing transaction patterns and market data and detecting anomalies that may indicate fraudulent activities. This helps maintain the integrity of these markets and ensures that investments contribute to environmental sustainability. 

By leveraging AI, financial solutions can be developed to support sustainable development and the transition to a more eco-friendly economy, contributing to broader environmental objectives, notes Al-Delaimi.

NEXT WAVE OF AI-DRIVEN INNOVATION 

Ayoub says the future of AI in finance is promising and transformative. It is expected to revolutionize various aspects of financial services through its ability to analyze and assess vast amounts of data at incredible speed. 

AI-powered chatbots and virtual assistants can offer 24/7 personalized customer service at lower costs. At the same time, AI enhances risk assessment by quickly evaluating transaction and behavioral data, benefiting areas such as cybersecurity and credit scoring.

To prepare for AI-driven innovation, institutions should focus on three key areas: developing adaptable systems to keep pace with evolving AI regulations, combining AI tools with human oversight for practical ethics and risk management, and investing in AI talent and workforce upskilling. However, Khan notes that AI won’t replace human financial experts. “We’ll see more collaborative AI systems that learn from and adapt to the expertise of individual professionals.”

Looking further ahead, quantum computing, while still in its infancy, promises to revolutionize finance with ultra-fast calculations and enhanced cryptography. Institutions should start preparing for these advancements, even if they’re still a few years away.

To be fully prepared for these innovations, financial institutions must take several steps, adds Gharazeddine. First, institutions need to stay updated on AI technology and invest in R&D. This includes exploring new AI applications and refining existing ones. Second, fostering a mindset that embraces change and experimentation within the organization is important. As AI continues to evolve, ensuring that employees are equipped with the skills needed to work alongside AI technologies will be essential. 

Third, collaboration with tech companies, AI startups, R&D organizations, consulting firms, and institutions that can provide the expertise and resources needed to innovate effectively is crucial.

Preparing for AI’s future in finance isn’t just about adopting new technology—it’s about creating an environment where innovation thrives and is guided by ethical considerations. By doing so, financial institutions can lead the way in the next wave of AI-driven change, says Gharazeddine.