Maya, a purely digital bank in Philippines, is transforming how people interact with money through artificial intelligence (AI). The company aims to bring millions of Filipinos into the formal financial system, using AI not just to automate processes but to rethink onboarding, credit scoring, prevent fraud and improve financial literacy. “We want to use AI to democratise financial access and transform how people engage with banking,” said Group Chief Technology Officer (CTO) Alfred Lo, emphasising that for Maya, inclusion is not a slogan but an imperative in one of Asia’s most dynamic but underserved markets. A market poised for digital banking growth The Philippines is fertile environment for digital finance. With over 100 million people, more than half under 30, digital adoption is surging. “The market is full of energy,” said Lo, noting that while mobile payments are expanding rapidly, traditional financial inclusion remains limited. Only one in ten Filipinos maintain a formal bank account, with informal credit still widespread. Maya seeks to close this gap through an integrated ecosystem that combines payments, savings, credit, insurance and digital assets. Its platform offers a single, accessible interface for all financial needs, tackling the fragmentation that often discourages first-time users from joining the formal banking system. Digital players like Maya are therefore not merely competing with incumbent banks; they are creating a new infrastructure for inclusion and their success could influence digital regulation across Southeast Asia. AI as a catalyst for inclusion AI sits at the core of Maya’s strategy, powering every stage of the customer lifecycle. Lo sees it as a solution to the Philippines’ structural constraints, especially in identity verification and credit assessment. “We use AI to verify identity with face recognition and cross-check government records, ensuring that customers are who they say they are,” he said. The AI-driven KYC (Know Your Customer) process has streamlined onboarding, reaching customers in remote areas with minimal friction. Credit underwriting is another area transformed by AI. With formal credit histories scarce, Maya evaluates risk using alternative data such as mobile phone usage, transaction records and behavioural patterns. “Using AI, we can analyse non-traditional indicators to extend credit to those who might otherwise be excluded,” said Lo, noting that this approach reduces dependence on costly manual assessments. Maya’s approach reflects a broader trend in fintech: moving from reactive banking to predictive financial services. By interpreting unconventional data, institutions can create products that are both inclusive and commercially viable. Transforming customer experience Beyond financial access, Maya uses AI to deliver efficiency and personalisation at scale. Where customer service teams once handled 61 percent of queries manually, AI-powered chatbots now resolve 95 percent without human intervention, achieving a 97 percent response rate— well above industry norms. The result is faster service, lower costs and higher satisfaction. AI also powers Maya’s personalised financial guidance engine, helping users manage money more effectively. “Our AI understands user behaviour and offers tailored advice on saving, lending or improving financial literacy,” said Lo. By embedding advisory features into its platform, Maya turns banking into a learning experience that grows with each customer. Managing risk in real time AI’s impact runs deep into Maya’s risk management. The bank uses machine learning and sequence embedding techniques to detect anomalies in user behaviour, cutting fraud by up to 98 percent. Continuous model updates keep systems agile. “In traditional banks, model refresh cycles can take months, but at Maya, we refresh our models monthly,” said Lo. This approach combines start-up discipline with enterprise-level governance. Yet Lo acknowledged AI’s double-edged nature. Model risk, including bias, drift and opacity, requires constant oversight. Maya’s monthly retraining of algorithms is not just a technical exercise; it safeguards trust in automated decision-making. For regulators and peers, it offers a blueprint for responsible AI deployment in emerging markets. Building an AI-first organisation Maya’s success, according to Lo, depends as much on culture as on code. “You can copy our code or infrastructure, but you can’t replicate our culture,” he said. The bank describes itself as “AI-first”— a mindset that runs across departments, not confined to engineering. This foundation encourages experimentation and data-driven decision-making, breaking down barriers between business and technology teams. Such a mindset may prove decisive as digital banking matures. Institutions that embed AI into their operating DNA will be better positioned to adapt, while those treating it as a side project risk being left behind. The future of intelligent finance Looking ahead, Lo envisions a future where banking becomes invisible. “You might conduct a financial transaction from a self-driving car, or even from your refrigerator,” he said. For Maya, the goal is to become an intelligent financial companion—anticipating needs and guiding users through life stages, from saving for school to buying a home. Maya’s trajectory highlights a broader transformation in banking: technology is no longer peripheral to financial inclusion—it drives it. By combining data, AI, and a culture of innovation, Maya is emerging not only as a national success story but also as a model for how digital banks in emerging markets can achieve scale and social impact.
