MONEY

Continued conflicts prevent the central African nation from fully exploiting its natural riches.

Other powers, like the EU, India, Saudi Arabia, Russia, and the Persian Gulf states, are jockeying for position. In recent months, two United Arab Emirates giants, NG9 Holding and International Resources Holding, have secured major mining and renewable energy deals in the DRC.

“The scramble for minerals allows DRC to renegotiate contracts, push for local value addition, and assert greater control over pricing and benefits,” says Innogence’s Djimpe. But the high levels of interest come with potential risks, he adds, such as fragmented governance and opaque deals made for short-term geopolitical alignment.

In June, an audit by the country’s Court of Auditors unearthed significant discrepancies in revenues reported by mining companies, amounting to $16.8 billion. Notably, mining makes up for over 95% of export earnings, according to the US State Department.

“One way for the DRC to overcome the resource curse is better enforcement of tax payment: that is, making sure that companies are paying their dues,” says Chatham House’s Vandome.

Anglo-Swiss giant Glencore, China’s CMOC Group, and Canada’s Ivanhoe Mines are among the largest mining companies operating in the country. Luxembourg-based Eurasian Resources Group and Metorex, a subsidiary of the Chinese multinational Jinchuan Group, also have significant interests.

Beyond Mining

While mining remains central to the DRC’s economic renaissance, other sectors, such as energy, agriculture, transport, financial services, and mega infrastructure, are also attracting global attention.

In renewable energy, the country boasts 100,000 megawatts of hydroelectric potential, yet less than 3% is currently exploited. In agriculture, the DRC has over 80 million hectares of arable land and 4 million of irrigable land.

Yet, it has managed to utilize only 1% of them, according to the Food and Agriculture Organization of the UN.

For this reason, the country remains dependent on food imports, spending $3 billion annually.

Financial services, spanning banking, microfinance, insurance, and fintech, is another low-hanging fruit for investors. Although mobile penetration—currently at about 50%—is the lifeline for financial services access through mobile money, the DRC wrestles with low financial inclusion. The banking penetration rate is estimated at just 6% while the broader financial inclusion rate stands at below 40%, according to State Department data.

To close the gap, foreign banks from Kenya, Tanzania, Nigeria, and South Africa are making forays into the central African nation. Kenyan lenders KCB Bank and Equity Bank have become big players after entering the country through the acquisition of Banque Commerciale du Congo (BCDC) and Trust Merchant Bank, respectively. EquityBCDC, which has 2 million customers in the DRC, expects to grow to 30 million clients by 2030.

For the country’s people, socioeconomic transformation is intertwined with peace. Critics, including the Oakland Institute, argue that the US-brokered peace deal is a gimmick to open “a new era of exploitation.” But popular opinion holds that the deal offers the DRC its best chance at stability and prosperity.

In banking as in other industries, AI is rapidly becoming a core business driver. The biggest gains will come from a foundational rethink of operations, not marginal improvements.

The financial sector is undergoing a profound transformation, powered by AI. Banks’ strategic integration of AI is moving beyond simple efficiency gains to make the technology a core business driver, focused on hyper-personalization, augmentation of human talent, and robust governance.

The real opportunity, says Andy Schmidt, vice president and global industry lead for Banking at CGI, [our AI in Finance judging partner], lies not in simply applying AI to existing workflows, but in fundamentally rebuilding processes with AI at the core.

A key aspect of this transformation is the shift towards an ultra-personalized and predictive customer experience. AI is moving past rudimentary chatbots to become an “agentic, conversational assistant” that can proactively anticipate a customer’s needs: from preventing payment failures by automatically increasing card limits to providing tailored financial guidance and real-time product recommendations.

Going forward, this intensified focus on customer experience will be a significant component of return on investment (ROI), Schmidt predicts.

“The real value comes in improved customer experience,” he stresses. “Being able to onboard customers more quickly, being able to transition from opportunity to revenue more quickly, and optimizing the customer experience so that they remain satisfied and stay with the bank over time.”

Schmidt highlights success stories in wealth and personal finance where GenAI drives personalization recommendations. DBS Bank’s harnessing of AI, for example, has drastically accelerated customer journeys, demonstrating the potential for significant scale and opportunity.

Human-AI Augmentation

The case for AI adoption in banking centers on strategic augmentation, were AI becomes a co-pilot for human experts. The goal is to automate repetitive and low-value tasks, freeing up human capital to focus on such complex, high-value activities as strategic decision-making, advisory sales, and conflict resolution.

Further driving this internal empowerment is the democratization of GenAI tools across the workforce, accelerating research, analysis, and data synthesis. Crucially, banks must commit to the principle of human oversight, ensuring that for complex matters, a human being is always in the loop and remains the final decision-maker.

AI’s role in risk management is evolving from reactive analysis to real-time, predictive analytics. By continuously monitoring vast internal and external data streams, AI can anticipate potential risks and perform complex what-if scenario planning. This capability couples with enhanced fraud detection, where sophisticated AI, including neural networks, provides real-time surveillance and prevention across massive transaction volumes.

AI is also streamlining the traditionally costly and time-consuming realm of regulatory compliance. Schmidt emphasizes the value of AI in bringing “transparency, auditability, and repeatability to key processes, especially when it comes to compliancerelated processes like KYC [know your customer].” Relatedly, AI is automating tasks like credit report preparation and enhancing the rigor of due diligence on complex M&A transactions.

Maximizing ROI Gain

A significant lesson emerging from AI deployment is that the most substantial returns come from a foundational rethink of operations, not marginal improvements. The financial industry is recognizing that “adding AI to existing processes will make them marginally better,” Schmidt notes, but that “optimizing processes to leverage AI will make them dramatically better.” The best way to realize the benefits of AI transformation, he adds, is in “examining these long-standing processes, optimizing them, and fundamentally rebuilding them. The goal is to integrate AI at the core of the process, rather than sprinkling it on top as an afterthought.”

With every aspect of AI adoption, however, the best approach is to proceed in stages. For those beginning their AI journey, Schmidt suggests adopting large language models (LLMs) as a starting point before transitioning to more specialized, purpose-built models. The effective integration of AI requires continuous change management to sustain capabilities and maximize ROI over time.

Meet The Winners

Winner Insights

Artificial intelligence is transforming the banking industry, streamlining operations, improving risk management, and enhancing the customer experience.

Best Payments

Akbank

Aiming to enhance back-office efficiency and reduce friction, Akbank implemented an AI-driven solution in 2024, training an open-source LLM on over 100,000 banking documents. The custom-tailored LLM tool reinforces secure and compliant operations within the bank’s own data centers and is accelerating back-office automation, significantly improving accuracy, security, and overall efficiency, and underscoring the bank’s dedication to AI innovation and regulatory compliance.

Akbank is utilizing this AI-driven model primarily to automate payment order processing for both customers and regulatory institutions; it also plays an important role in automating back-office transaction orders, significantly reducing the need for manual intervention.

Best Chatbots & Virtual Assistants

CaixaBank

CaixaBank’s employees now have access to NOA, a GenAI-powered assistant designed to provide accurate answers to internal questions using NLP. The tool is a first for CaixaBank, setting a new standard for AI-driven operational efficiency at CaixaBank. Unlike traditional knowledge management systems, it eliminates the need for manual searching by directly retrieving precise information from the bank’s extensive internal documentation. In so doing, NOA has fundamentally altered the process by which 45,000 CaixaBank personnel access information, reducting the necessity for escalating issues and enhancing query resolution efficiency. The system currently handles more than 8 million queries a year, reducing response times and elevating the overall employee experience. User adoption has been swift, attributed to NOA’s intuitive interface and seamless integration within workflows.

Best Enhanced Customer Experience

DBS Bank

DBS Bank pioneered an industry-first Negative Customer Impact (NCI) Control Tower in 2024 that enhances service management by identifying customer pain points and “silent sufferers” in real time. It focuses on key customer journeys to detect performance anomalies early, enabling an effective and timely response while minimizing customer impact.

The NCI Control Tower provides crucial transparency on customer behavior and client performance data to platform and business owners, facilitating ongoing improvement of the customer journey. This comprehensive approach, covering a broad spectrum of service performance dimensions, significantly enhances DBS’s resilience and response capabilities. Since its launch, NCI teams have scaled across more than 15 customer-facing channels, encompassing the delivery of more than 300 customer journeys.

Best Personalized Financial Advice

QIB

QIB’s upgraded AI-driven Next Best Offer (NBO) 2.0 recommendation engine uses deep learning on customer behavior, transactions, and financial patterns to deliver personalized, real-time financial product recommendations. Its key feature is non-intrusive, seamless integration into QIB’s mobile app, providing tailored product information without disrupting core banking.

The AI algorithms evolve, improving accuracy and engagement over time. NBO 2.0 analyzes over 1,600 customer attributes—including demographics, holdings, transactions, and interaction data over five years—to pinpoint the customer’s financial journey stage and suggest the most appropriate products. It also provides valuable data for product portfolio refinement.

Best Private Banking

Bank of Georgia

Bank of Georgia (BoG) is setting a new standard in client acquisition with a dual strategy for identifying and converting high-potential, affluent clients who primarily bank elsewhere. By leveraging these external sources, BoG can detect “invisible” high-income individuals who have minimal engagement with the bank’s current ecosystem: a significant improvement over traditional identification methods that rely on publicly available external data. This fusion of AI and strategic intelligence provides a tailored approach to building the client base, making BOG a leader in data-driven banking innovation.

Best Fraud Detection And Prevention

Banamex

Banamex is employing AI and machine learning, specifically including neural networks, for real-time fraud detection and prevention. The bank reports a 70% reduction in attempted fraud since it integrated AI throughout its operations in March 2024. Banamex combines rules-based systems, data mining, and neural networks to activate a unified system capable of instantaneous analysis and response to potentially fraudulent activities.

A critical element involves implementing the FICO Falcon Fraud Manager solution. The real-time processing capabilities of the tool’s neural network models mitigate fraud-related losses and enhance detection accuracy by identifying fraud at the point of sale, prior to transaction completion. Its AI infrastructure processes voluminous amounts of transaction data in real time to discern patterns, anomalies, and deviations from behavioral norms, enabling it to promptly flag and potentially inhibit suspicious transactions.

Best Credit Assessment

Banamex

Banamex is leveraging AI to revolutionize its credit assessment process, shifting from slow, traditional methods to real-time evaluations. AI algorithms analyze vast datasets, incorporating up to 200 variables—including traditional financial metrics and potential alternative sources like geolocation—to create a comprehensive, multidimensional, and more accurate view of the applicant’s creditworthiness. This dynamic model significantly improves decision-making speed, the bank reports, particularly for high-volume tasks, and enhances overall operational efficiency by automating data processing and analysis.

AI and data analytics deliver tangible customer benefits as well. Faster credit approvals and personalized services, driven by AI insights, elevate the overall customer experience and thereby help Banamex maintain a competitive advantage in Mexico’s rapidly evolving financial sector.

Crucially, AI-powered credit assessment contributes to the goal of financial inclusion by providing the opportunity to enter the formal banking system to prospects with limited or no established financial history. Typically, the options available to low-income individuals or those operating only in the informal economy are limited in capacity, come with substantially higher annual percentage rates, and may involve tough collection practices. Access to financing from a formal player like Banamex can be a life-changing event for these applicants.

Best Risk Management

BBVA

BBVA utilizes Mexico’s extensive transfer network, analyzing both direct and indirect data including recurring client-to-nonclient transactions, to accurately estimate client income. This enables effective assessment of those with limited banking activity, optimizing the credit offer based on true financial stability.

Transfer analysis is the foundation of a sophisticated relationship model that identifies financial links and inherited assets and detects irregular activities like triangular movements and simulated income, enhancing accuracy and mitigating fraud. This enables BBVA to offer better-tailored financial products, promoting responsible and secure credit access.

The model is applied across BBVA’s entire client portfolio—those holding existing credit products and those not—providing a valuable tool for business units needing insights into clients’ economic standing and repayment capacity. Integrating multiple data sources—including credit bureau reports, investments, transactions, relationship graphs, and payroll—ensures thorough evaluation, reducing risk and optimizing credit allocation. This multisource approach yields precise opportunity identification, ensuring BBVA’s marketing campaigns align with its risk appetite while minimizing exposure to clients who lack financial capacity.

A critical component is assigning a predicted income range, refining the bank’s marketing campaigns to align with a predetermined risk level. This leads to enhanced prediction stability and optimized credit offers, ultimately maximizing profitability and reducing default risk.

Best Fintech

CTBC

CTBC Bank’s AI Cheque Check is notable as Taiwan’s first AI-based check recognition system, achieving over 90% accuracy in interpreting traditional Chinese handwriting, the bank reports, by integrating advanced handwriting recognition and centralized processing.

Initially developed for internal use, it has significantly boosted check processing efficiency and accuracy across CTBC Bank’s branch network, eliminating the manual verification bottlenecks inherent in traditional processing, thereby accelerating check clearance and minimizing human error.

AI Cheque Check uniquely combines optical character recognition, structured transaction data, and AI-driven compliance checks to ensure smooth automation while maintaining crucial regulatory accuracy. It benefits the Taiwanese bank’s customers as well by speeding up transaction times and improving service quality.

Gökhan Gökçay, executive VP of Technology at Akbank, explains how his bank—named the World’s Best Consumer AI Bank—uses AI and partnerships to tailor service and secure data.

Global Finance: What impact has Akbank’s AI-powered digital assistant had on customer loyalty, and how does it contribute to your 96% digital migration rate for sales?

Gökhan Gökçay: Akbank Assistant has become a cornerstone of our customer engagement strategy by delivering fast, personalized, and seamless banking experiences across all channels. By enabling customers to complete more than 200 types of transactions autonomously and resolving 250,000 monthly support sessions through the “Help Me” module, it has significantly enhanced convenience and satisfaction.

The Assistant’s proactive and context-aware guidance, combined with human-like voice interaction, has fostered stronger emotional connections and loyalty. This trust and ease of use have been key drivers in Akbank’s remarkable 96% migration rate of transactions, including sales and inquiries, to digital channels.

Moreover, the Assistant’s recommendation engine, powered by advanced analytics and large language models, has increased product conversion rates from 2% to 18%, demonstrating that intelligent personalization directly translates into customer engagement and business growth. Customers now engage with our digital platforms over 700 million times daily, reflecting a deep behavioral shift toward mobile-first, AI-supported banking.

GF: Akbank uses AI to provide “Banking IQ” insights to customers, such as cash flow analysis and spending patterns. How do these insights directly translate into better financial habits for your customers, and what is your approach to turning these insights into proactive, personalized product recommendations?

Gökçay: Through AI-powered “Banking IQ” insights, Akbank analyzes customer cash flow, spending patterns, and savings behavior to provide meaningful, actionable financial guidance. These insights empower customers to make smarter financial decisions, such as optimizing savings, avoiding overdrafts, or rebalancing investments, based on real-time data.

The same infrastructure supports our agentic recommendation engine, enabling customers to better understand their financial habits, stay in control of their goals, and develop long-term financial wellness, turning data into trusted everyday advice that drives healthier financial behavior.