The financial sector is entering a phase where AI is no longer optional but necessary. However, success goes beyond just adopting AI, fintech solutions and systems that prioritise customer needs, sincere considerations, and resilience must be built.
The evolution of artificial intelligence (AI) in the financial sector has completely changed the way businesses deliver services.
During the Techeconomy Business Series session titled “Major Lessons for Techies in Building Resilient, Customer-Centric Financial Solutions in an AI-Driven World”, experts shared their experiences and insights on how to innovate and maintain resilience while meeting customer needs.
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Defining Resilience in Financial Solutions
Peter Kwakpovwe, founder of Draco Intelligence Ltd UK, broke down the concept of resilience in financial solutions. He stated, “Resiliency in financial solutions is the ability of the system to recover from shock, attack, or disruption, ensuring delivery and usage by customers.”
He noted that resilience goes beyond simply fixing problems; it requires proactively creating systems that withstand disruptions.
Kwakpovwe shared a real-world example from his career: “We developed an AI-powered digital lending platform aimed at ease of banking, lending, and credit rating for customers. However, we faced challenges like political unrest and economic instability. To overcome these, we built an advanced anomaly detection algorithm to flag fraudulent transactions, an automated failover system, and a robust recovery and backup system.”
These measures ensured the platform could withstand disruptions and continue serving customers efficiently. According to him, “This reaffirmed my belief in AI-driven initiatives within the financial landscape.”
Ethical AI and Balancing Customer Needs
Ayodeji Ogunmola, director of Product Management at Northsnow Ltd UK, spoke on balancing rapid AI innovation with customer expectations. He noted, “The first thing customers want from financial institutions is to have their problems solved. AI brings simplicity to this process, but ethical considerations and transparency are important.”
Ogunmola highlighted two major issues:
- “How ethical can the AI go?”
- “Are customers trusting enough to allow AI integration into financial institutions?”
He explained the importance of defining what aspects of financial transactions are handled by AI versus humans. “We’ve seen human errors in resolving issues, but AI can bridge this gap, especially in interactions like chatbots that offer faster service.”
However, he also stressed the need for transparency: “Businesses must inform customers about what AI can and cannot do to build trust.”
Building Trust in AI: Transparency, Ethics, and Customer-Centricity are Key
On building trust in AI-driven financial systems, Moniade Adeniyi, product innovation and business growth strategist at Northsnow Limited, stressed the importance of transparency, fairness, and customer-centricity in AI solutions.
He stated, “When you’re building an AI solution, it should be clearly explained how the AI system works. Customers need to feel safe and more confident about using the solution.”
Adeniyi also highlighted the need for ethical considerations, urging financial institutions to ensure that AI systems are unbiased. He said, “A financial institution must make sure that AI systems are fair and they don’t favour or harm any group of people.”
Personalised Financial Services
Ogunleye Oluwatobiloba, a data analyst with a fintech background, delved into how AI enhances customer experiences. “AI plays a huge role in delivering personalised financial services by leveraging data-driven insights,” he said.
He outlined key applications of AI:
- Customer Segmentation: “AI analyses customer data, such as transaction history and credit behaviour, to create detailed profiles.”
- Tailored Recommendations: “AI-powered engines suggest financial products like loans or investment options based on individual goals.”
- Chatbots and Virtual Assistants: “These tools, like UBA’s ‘Leo’, offer 24/7 support, handle transactions, and reduce the workload on human staff.”
- Fraud Detection and Prevention: “AI monitors user behaviour for anomalies, flags potential fraud, and notifies users immediately.”
Mitigating Risk with AI
The speakers collectively agreed that risk mitigation is an essential component of resilient fintech solutions. Kwakpovwe mentioned, “AI helps businesses holistically understand risk landscapes and develop de-risking strategies.”
Ogunmola added that iterative feedback and customer research are essential: “AI gathers data, analyses usage patterns, and helps businesses improve their offerings.” This aligns with the overarching goal of resilience—adapting to challenges while maintaining seamless customer experiences.
AI’s prospects in the financial sector are broad but require careful integration. Ogunleye said, “AI’s strength lies in its ability to personalise, automate, and innovate while addressing individual customer needs.” However, ethical considerations, transparency, and robust systems are essential to fostering trust and ensuring resilience.
The panel emphasised the importance of cross-disciplinary collaboration, with Kwakpovwe noting, “You need a strong, high-risk-skinned team to navigate the complexities of AI-driven solutions.”
Building Customer-Centric Financial Solutions Through AI
Peter Kwakpovwe emphasised the importance of leveraging AI to enhance financial literacy and inclusion. He highlighted the Central Bank of Nigeria’s (CBN) ongoing efforts to improve financial literacy through collaborations with banks and financial institutions.
“By implementing this innovative admin solution, financial services can be customised for people who are particularly underserved and those who are in the underbanked population. But again, AI is data, data, and more data,” he said.
However, Kwakpovwe noted that while AI offers improved efficiency, fraud detection, and personalised customer services, the technology also introduces significant risks.
Adeniyi further noted the role of customer feedback in designing effective AI solutions, stating, “Every AI solution you are building should be tailored towards the customer… When you do all these things, trust is built, and they will want to use your system.”
The Dark Side: Data Privacy and Security Risks
Kwakpovwe did not mince words about the gravity of data privacy breaches, calling it the “data apocalypse.” He cited examples of data leaks in Nigeria, including breaches from major banks and the National Identity database. “The day you plug your product to AI, it automatically has access to everything you’ve had today—your data,” he warned.
To mitigate such risks, he recommended:
- Robust Encryption: “If you build a database system and there are no strong encryptions, it’s a problem.”
- Compliance with Data Protection Laws: He stressed the importance of adhering to regulations like GDPR and conducting regular audits.
- Bias and Fairness Audits: Peter shared a Silicon Valley example where AI algorithms unintentionally discriminated against certain genders in loan approvals, showcasing the need for robust datasets and transparent algorithms.
Over-Reliance on AI: A Critical Pitfall
Kwakpovwe spoke on issues about the over-reliance on AI systems, which can lead to a reduced human thinking process. “Even the most intelligent people today are relying so much on AI,” he said. To address this, he suggested:
- Ensuring human oversight for key decisions
- Using AI as a support tool, not the primary driver of actions
- Investing in education and training to empower professionals with foundational skills
Technological Failures and Systemic Risks
Reflecting on a recent major banking system outage in the UK, Kwakpovwe noted the catastrophic impact of technological failures. “A core banking software issue shut down everything. It became a social media brouhaha,” he said.
To prevent such occurrences, Peter called for:
- Redundancy and Backups: “I’m a big fan of redundancy. You must have backups that have backups.”
- Incident Reporting Plans: Establishing clear protocols for managing AI system failures.
Scaling through Regulatory and Compliance Challenges
On regulatory hurdles, particularly in Nigeria and South Africa, Kwakpovwe stressed the importance of aligning AI systems with financial regulations to avoid fines and restrictions. “You must have regulatory engagement,” he said, adding that ethical AI frameworks and continuous monitoring are essential for compliance.
Adeniyi also stressed the importance of regular audits to maintain compliance and customer confidence, noting, “Regularly review the AI system to ensure they follow the law and meet high standards… This should be transparent to the customer.”
Leveraging AI to Drive Innovation in Fintech Solutions
Speaking on the importance of a systematic approach to deploying AI in financial services, Kwakpovwe said: “First off, there has to be this continuous learning of your data. AI can make decisions for you, but that shouldn’t be the final leg,” he noted.
He called for hiring and training skilled professionals who can create and refine data models, stating, “You need over a billion scenarios… AI can help you create those scenarios, but you need someone to fine-tune and look at it also.”
Kwakpovwe emphasised the essence of closed user group testing before AI deployment. He explained: “Bring stakeholders into the room… go back to the product requirement document, tick all the boxes one by one… ensure your AI-driven product has achieved what you set out to do. When that’s done, move on to continuous improvement.”
He likened AI development to raising a child: “When you deploy it, AI starts learning on its own. It feeds on data, so regular audits and framework adjustment sessions are critical to ensure the system delivers sustainable value.”
Security and Scalability in AI Systems
The panellists highlighted the importance of cybersecurity in AI-driven systems. Pointing out the emergence of new roles such as large language model (LLM) cybersecurity experts: “These are people building systems to safeguard AI technologies. Such jobs didn’t exist five years ago, but they’re now crucial for protecting data and ensuring system integrity.”
Opportunities for AI in Africa
Addressing the future of AI in Africa, Ayodeji Ogunmola said: “There’s a lot of money in Africa that has not been harnessed yet. Voice-over AI could revolutionise financial inclusion by enabling people, especially those who aren’t tech-savvy, to access services through phone interactions. This can include account creation, KYC processes, and transactions.”
Ogunmola noted the benefits for underserved populations, such as rural farmers: “A farmer named Musa could get access to microloans because AI analyses his farming patterns and mobile data.”
AI’s Role in Fraud Detection and Improved Customer Experience
Fraud detection is an important subject when it comes to AI. Ogunleye Oluwatobiloba expatiated this: “AI can help in fraud detection and prevention by monitoring transaction patterns and reducing fraud rates, building customer trust.”
He noted additional benefits of AI, including:
- Smart payment gateways for instant, secure cross-border transactions.
- Dynamic currency conversion providing real-time rates.
- AI-driven credit scoring systems enabling microloans for customers based on their transaction histories.
AI and Human Expertise: A Synergistic Future
Countering fears of job displacement by AI, Moniade Adeniyi reassured professionals: “AI does not have a mind of its own; it resonates based on the information you provide. Professionals must train AI to respond effectively to human needs. Instead of losing jobs, we’ll be creating scenarios and guiding AI’s learning process.”
Adeniyi noted that this approach would open opportunities across sectors, urging professionals to stay proactive in adapting to the AI era.
Organisations must embrace AI responsibly, ensuring human oversight and continuous improvement. “If you follow these guidelines, you’ll create a system that works as it should—delivering value to both the organisation and its customers in a sustainable way.” This will drive innovation, inclusion, and resilience across the financial sector.
