Scams have become one of the fastest-growing threats facing financial institutions worldwide, with criminals increasingly using sophisticated tactics to trick customers into sending money voluntarily. Unlike traditional fraud, where transactions are clearly unauthorised, scams often involve social engineering that persuades victims to approve payments themselves. This shift has forced banks to rethink how they detect and prevent financial crime. Commonwealth Bank of Australia has responded by deploying artificial intelligence systems designed to identify suspicious behaviour in real time and intervene before customers lose money.
The growing challenge of scam-related losses
Across many markets, scam-related fraud has surged as criminals exploit digital payments and online communication platforms. Customers may be targeted through fake investment schemes, impersonation scams, romance scams or fraudulent online marketplaces.
Because victims often authorise the transactions themselves, these cases are harder for banks to detect compared with traditional card fraud. Payment systems are also becoming faster, which leaves banks with very little time to identify suspicious activity before funds are transferred.
To address this challenge, banks are increasingly turning to advanced analytics and machine learning systems capable of detecting subtle patterns in customer behaviour.
How AI helps identify scams in real time
Commonwealth Bank has invested heavily in artificial intelligence tools that monitor transactions and customer behaviour across its digital banking platforms. These systems analyse large volumes of data to identify patterns that may indicate a scam.
AI models evaluate factors such as:
- unusual transaction amounts or destinations
- sudden changes in customer payment behaviour
- transfers to newly created accounts
- transactions linked to known scam networks
When the system detects suspicious activity, it can trigger alerts, delay transactions or prompt customers to verify payments before they are processed.
This real-time monitoring allows the bank to intervene quickly and potentially stop scams before funds are lost.
Combining technology with customer protection tools
In addition to back-end analytics systems, Commonwealth Bank has introduced customer-facing protection features designed to help users recognise potential scams.
For example, the bank provides in-app alerts that warn customers when they are sending money to accounts that may be associated with suspicious activity. Some transactions may also trigger confirmation messages asking customers to review the payment before proceeding.
These tools aim to create a second layer of defence by combining AI-driven detection with customer awareness.
Using behavioural analytics to detect manipulation
One of the key challenges in scam prevention is identifying when a customer is being manipulated by criminals.
Machine learning models can analyse behavioural signals such as unusual login activity, rapid changes in payment patterns or deviations from a customer’s typical financial behaviour. These indicators may suggest that the customer is under pressure or being guided by scammers.
By analysing these signals in real time, banks can identify potential scams that would otherwise appear legitimate.
The broader role of AI in financial crime prevention
Commonwealth Bank’s approach reflects a broader trend across the banking industry. As financial crime evolves, traditional rule-based fraud detection systems are being supplemented with AI models capable of identifying complex behavioural patterns.
Machine learning systems can analyse far more variables than traditional systems and adapt as new fraud techniques emerge. This allows banks to respond more effectively to rapidly changing scam tactics.
Many financial institutions are now investing heavily in AI-powered financial crime platforms that integrate fraud detection, anti-money laundering monitoring and scam prevention capabilities.
What this means for the industry
- Scam-related fraud is becoming one of the biggest threats facing banks and their customers.
- AI systems are enabling financial institutions to detect suspicious activity in real time.
- Behavioural analytics can help identify when customers may be under pressure from scammers.
- Customer-facing alerts and warnings are becoming an important part of scam prevention strategies.
- Banks that combine AI detection with customer education will be better positioned to reduce scam-related losses.
