The rapid expansion of the digital economy has unlocked new opportunities for innovation — but it has also exposed consumers and financial institutions to increasingly sophisticated forms of fraud. At the center of both progress and risk is artificial intelligence (AI), a technology that has transformed how people transact, communicate, and access financial services.
From automating processes to delivering more personalised digital experiences, Artificial intelligence has become deeply embedded in modern life. Yet the same technology is also being exploited by fraudsters.
As GenAI becomes more accessible, creating convincing fake identities, documents, and communications is now easier than ever.
According to Sumsub’s Q1 2025 internal data, synthetic identity document fraud is rising sharply, gradually replacing more traditional and physical forms of fraud. Globally, more than half of all fraudulent activity now involves some form of artificial intelligence, underscoring how rapidly the threat landscape is evolving.
Meanwhile, the impact of GenAI on fraud has also become especially apparent when considering that more than 50% of fraudulent activity in the global scene involves the use of artificial intelligence.
The Philippines among hardest hit
IMAGE CREDIT: Tara Winstead
Filipino consumers are among those most affected. Data from TransUnion’s global intelligence network shows that the Philippines recorded a suspected digital fraud rate of 13.4% in 2024, ranking second-highest worldwide.
The retail and financial services sectors have been particularly targeted, placing millions of Filipinos who rely on digital platforms at risk.
As the country accelerates its transition toward a digital-first economy — driven by e-wallets, online banking, and digital lending — the need for robust fraud prevention measures has become increasingly urgent.
Understanding AI-driven digital fraud
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Digital fraud refers to the use of online and digital channels to steal funds, compromise accounts, or obtain sensitive customer information.
Today’s most prevalent threats are increasingly powered by artificial intelligence, including voice cloning scams, deepfake videos, and AI-generated phishing campaigns.
These scams often rely on GenAI to convincingly impersonate trusted individuals or institutions, tricking victims into disclosing personal information or transferring money.
The realism and scale enabled by artificial intelligence have made such attacks harder to detect using traditional fraud controls.
Fighting fraud with Machine Learning
Photo by Google DeepMind
To counter these threats, financial institutions are turning to artificial intelligence itself — specifically machine learning — as a core defense mechanism. AI-powered fraud detection systems are now widely used across banks, fintech firms, and payment providers to identify and prevent fraudulent activity in real time.
Machine learning models typically combine supervised and unsupervised learning techniques. In supervised learning, systems are trained using labelled datasets to recognise known fraud patterns and predict outcomes. Unsupervised learning, meanwhile, allows models to analyse vast amounts of unlabelled data, identifying anomalies, hidden relationships, and emerging fraud trends without prior instruction.
This dual approach enables institutions to detect both known fraud schemes and new, previously unseen attack methods.
Key use cases in fraud prevention
As financial transactions increasingly shift online, machine learning has become a critical tool in protecting users and strengthening trust in digital platforms.
One of its most common applications is identity verification, where AI analyses official documents and biometric data to confirm a user’s identity. Another is anomaly detection, which flags unusual transaction patterns that deviate from a customer’s normal behaviour. When suspicious activity is identified, the system assigns a risk score, helping fraud teams prioritise cases and respond more quickly.
Machine learning is also used in network analysis, examining relationships between accounts, devices, and entities to uncover hidden fraud rings. In addition, artificial intelligence can scan text-based channels such as emails and social media to detect scam-related keywords, patterns, and behaviors.
Beyond technology
IMAGE CREDIT: Tara Winstead
As society becomes more digital, the importance of digital security grows alongside it. While artificial intelligence has enabled new forms of fraud, it is also one of the most powerful tools available to combat them.
However, technology alone is not enough. As the Philippines continues its digital transformation, financial institutions, businesses, and consumers alike must remain vigilant. Effective fraud prevention depends on a combination of advanced technology, strong regulatory frameworks, and informed users.
Artificial intelligence may be reshaping the fight against fraud — but lasting protection will come from pairing innovation with awareness, accountability, and continuous adaptation.
