Analysts estimate that cybercrime is predicted to cost the world $10.5 trillion per year, making this one of the largest transfers of economic value in history. A huge share of that sits inside the financial system, where bank fraud is evolving faster than many institutions can respond.
In dynamic markets like Nigeria, Indonesia and the Philippines, this pressure is especially intense. Mobile and digital banking adoption is soaring, real-time payments are becoming the norm, and regulators are naturally tightening expectations. At the same time, fraudsters are professionalising; running organised networks, buying ready-made phishing kits, and moving stolen funds in seconds.
For banks and digital lenders, this can become a daily test of whether your infrastructure, data, and teams can keep up.
This article explores why fraud in the banking industry is accelerating in dynamic markets, what we can learn from recent bank fraud cases in the Philippines and Nigeria, the data and technology foundations needed to fight back, and how a modern core and data layer (like Oradian’s) changes what’s possible in 2026.
Why fraud is exploding in dynamic markets
Fraud thrives where three things intersect:
- High digital adoption
- Uneven financial literacy
- Legacy systems and fragmented data
Dynamic markets have all three.
In the Philippines, digital payments and mobile banking have surged in recent years, with e-money and online transfers now a normal part of everyday life. But that growth has come with a spike in scams: phishing, account takeovers, fake investment apps, and social-engineering schemes that trick customers into handing over credentials. Regulators like the Bangko Sentral ng Pilipinas (BSP) and the Philippine Deposit Insurance Corporation (PDIC) have repeatedly warned about rising bank fraud and cyber incidents, especially via digital channels.
In Nigeria, the story is similar. The Nigeria Inter-Bank Settlement System (NIBSS) has reported billions of naira in electronic fraud losses annually, driven by channels like mobile, internet banking, POS, and ATM. Fraud rings exploit SIM swap attacks, OTP interception, social engineering, fake support calls, and insider collusion to move funds quickly through mule accounts and cash-out points.
What makes this wave of bank fraud cases in Nigeria and the Philippines so dangerous is speed. Money now moves in seconds, so if your fraud controls depend on overnight batch jobs or manual post-hoc reviews, you’re always reacting too late.
Bank fraud cases in the Philippines and Nigeria
While individual bank fraud cases differ, the patterns behind them are remarkably consistent.
In the Philippines, many bank fraud cases have involved:
- Phishing and smishing: convincing customers to click fake links or share OTPs
- Account takeover: fraudsters changing contact details and draining balances
- Fraud networks: thousands of accounts used to launder stolen funds
While there are rules on stronger authentication, consumer protection, and shared responsibility for certain types of scams, for banks, complying on paper is not enough; they need real-time insight into behaviour: which devices, locations, and transaction patterns look “normal”, and which don’t.
In Nigeria, NIBSS and banks have grappled with e-fraud across:
- USSD and mobile channels
- Internet banking
- POS merchants
- Card and ATM rails
NIBSS fraud reports have highlighted growing incident numbers and sustained loss levels, even as controls improve. Common issues include SIM swaps, weak verification at account opening, and delayed fraud detection that lets funds move across multiple banks before anyone reacts.
In both countries, the through-line is clear: fraud in the banking industry is a data and infrastructure issue that must be addressed soon. If your systems can’t track enough, quickly enough, you can’t act.
Why legacy cores make fraud harder to fight
Many institutions still rely on legacy core systems built long before real-time payments, mobile-first banking, and machine-learning-driven fraud engines existed.
These cores often:
- Store data in silos that don’t talk to each other
- Rely on batch processing, not streaming
- Make it hard to add new rules or signals without vendor tickets
- Offer limited visibility into cross-channel behaviour
The result is you end up with fragmented views of customers and transactions, your fraud teams juggle static reports, spreadsheets, and disconnected tools, and by the time an anomaly is spotted, the funds are gone.
In this setup, it doesn’t really matter which fraud tool you buy. If you can’t give it complete, timely data, even the best algorithm will underperform.
This is where modern, cloud-native cores and the data access models they support change the game.
The new fraud defence stack: data, detection, and decisions
To get ahead of bank fraud in 2026, digital banks and lenders in Nigeria, the Philippines, and similar markets need four foundational capabilities.
A real-time, analytics-ready data layer
Fraud detection lives or dies on data, making the top priority very simple: a clean, near-real-time view of your core data available off the live system, safely.
That’s exactly what Oradian’s Database Access is built to do: provide a read-only replica of your production PostgreSQL database, continuously synced but isolated from the live core. Your fraud tools, BI dashboards, and machine-learning models work on that replica, not on production.
This gives you:
- Full-fidelity transaction and account history
- Cross-channel views across loans, savings, and payments
- The ability to run heavy analytics and pattern-detection without risking downtime
Instead of piecemeal exports, you have a single source of truth for fraud analytics.
Rules that evolve as fast as fraud does
Static rule engines aren’t enough when fraud patterns change weekly. Teams need ways to ship new logic fast.
On Oradian, features like Custom Code and event-driven notifications make it possible to:
- Add flexible decision logic directly in the core workflow
- Trigger alerts or step-up authentication when conditions are met
- Iterate quickly without long vendor cycles
For example, if your team sees a new pattern, say, multiple failed login attempts followed by a high-value transfer from a new device, they can encode that as a rule in days and route those cases to manual review.
Behavioural and network-level fraud models
The most effective fraud in banking industry fraud defences combine:
- Behavioural analytics: What does normal look like for this customer?
- Network analytics: Which accounts, devices, or merchants are connected?
With an analytics-ready replica of the core, you can:
- Train models on historical bank fraud cases in the Philippines or Nigeria, learning typical pre-fraud signals
- Map relationships between accounts, devices, and counterparties to spot mule networks
- Run models in shadow mode first before deploying to live decision flows
The global experience is clear: banks using AI-driven behavioural models have reported much higher fraud detection rates, with fewer false positives than traditional systems. That improvement is only possible with consistent, well-structured data.
Friction where it matters, not everywhere
Customers won’t tolerate constant friction. A modern fraud stack lets you:
- Step up authentication only on high-risk events
- Communicate clearly via app, SMS, or email when security checks are triggered
- Provide fast dispute and recovery flows when fraud is detected
In other words, your strategy won’t be to block more; it’ll be to block smarter, when necessary, and explain better. That’s particularly important in markets where trust in digital banking is still being earned.
A practical 90-day plan to strengthen fraud defences
You don’t need a two-year transformation to start getting ahead of bank fraud. Many of the foundations can be laid in 90 days.
Here’s a practical way to think about it.
Days 0–30: See the risk
- Turn on or strengthen your core data replica. For Oradian’s clients, that involves activating Database Access.
- Give your fraud and risk teams direct analytic access, within clear governance.
- Build a fraud baseline dashboard: channel-level losses, top attack types, time-to-detect, time-to-block.
- Identify your top three gaps: is it onboarding fraud, account takeover, or transactional fraud?
Days 30–60: Act on early wins
- Implement or refine rule-based controls for obvious patterns: unusual times, locations, device changes, velocity spikes.
- Run simple machine-learning experiments in shadow mode on the replica, for example, anomaly detection on transaction amounts or frequencies.
- Document outcomes. How many fraud cases would have been stopped? How many false positives?
Days 60–90: Embed and iterate
- Plug proven rules or models into live flows using your core’s configuration and automation options.
- Set up clear runbooks for fraud alerts: who acts, how fast, with what authority.
- Report back to leadership with measurable improvements: reduced time-to-detect, fewer manual reviews, lower loss rates per million transactions.
Institutions running on Oradian have a head start here: the cloud-native, API-first core plus Database Access means most of the heavy data plumbing and integration work is already done. That way, you can focus on designing and iterating controls, rather than wrestling with legacy infrastructure.
Building a fraud-resilient future with Oradian
Bank fraud in 2026 is a core banking problem that demands modern infrastructure, clean data, and agile teams. For banks and lenders in Nigeria, the Philippines, Indonesia, and other dynamic markets, the institutions that will beat out this trillion-dollar threat are those that:
- Treat fraud as a data and architecture problem, not just a compliance checkbox
- Invest in a real-time data layer that lets their teams see and respond quickly
- Use cloud-native cores and flexible logic to ship new rules and models at the speed of fraud
- Balance strong controls with clear communication and a good customer experience
That is exactly the future Oradian is building for our customers: a core banking platform that makes your fraud defences faster, smarter, and easier to evolve.
If you’d like to explore what a 90-day fraud sprint could look like on Oradian, reach out to vanda.jirasek@oradian.com with your top fraud concern and your current loss metrics. We’ll help you sketch a plan that’s grounded in your true reality. Because in a world where bank fraud moves in seconds, your defences can’t move in months.
