Fraud management tools for transaction monitoring in the banking industry

Effective transaction monitoring in detecting and preventing transaction fraud

Robust transaction monitoring systems are essential for modern banks to proactively identify and mitigate fraud risks. By analysing vast volumes of transaction data, these systems can detect subtle anomalies that might otherwise escape unnoticed. The evolving nature of financial crime necessitates a shift for banks from traditional methods to more adaptive, intelligent systems that can respond to the complexities of modern fraud. How effective transaction monitoring works:

• Continuous monitoring and analysis: banks continuously monitor and analyse customer transactions for suspicious patterns and anomalies.
• Leveraging advanced monitoring systems: by implementing advanced technologies like machine learning and data ingestion tools to collect multiple data points from various sources, banks can gain a more comprehensive overview and detect complex fraud schemes.
• Investigating suspicious transactions: upon identifying suspicious activity, fraud officers may conduct in-depth investigations by requesting supplementary information from customers to determine if fraud is involved.
• Establishing policies and procedures: it is vital to have well-defined policies and procedures in place to identify and prevent suspicious activities. This includes establishing clear criteria for what constitutes suspicious behaviour.
• Setting up rules and scenarios: regularly analysing customer transactions is crucial for defining rules and scenarios. This ensures that alerts are triggered promptly when customer transactions match the predefined rules and scenarios.
• Implementing a robust monitoring system: banks must invest in a comprehensive monitoring system that can handle large volumes of data and adapt to changing fraud trends.
• Continuous monitoring and refinement: transaction monitoring is an ongoing process that requires regular updates and adjustments on the rules to address emerging fraud threats.

Challenges banks face with transaction monitoring

• Limited rule’s customisation: many transaction monitoring tools are designed based on general risk factors. However, each bank has a unique risk profile influenced by its customer base, transaction types, and geographic factors. Having pre-set rules can lead to missing potentially fraudulent activity.
• False positive overload: traditional systems often generate a great number of false positives, alerts that indicate potential suspicious activity that turns out to be legitimate transactions. This influx of alerts can overwhelm compliance teams, forcing them to prioritise urgent cases while potentially overlooking genuine threats. The resources drained by investigating these false alerts could be better spent on more nuanced risk assessments or proactive measures, ultimately undermining the bank's ability to respond effectively to actual fraud.
• Rule-based system: Fraudsters are becoming increasingly sophisticated, leveraging technology and social engineering tactics to exploit system vulnerabilities. Rigid, rule-based systems are not only inflexible but also predictable, making it easier for fraudsters to devise strategies that circumvent established rules, leaving banks vulnerable to financial losses and compliance failures.
• Massive transactions volumes: The rapid rise of digital banking has resulted in an exponential increase in transaction volumes. According to Statista, in Thailand, banks receive more than 1.64 million transactions in one day. Monitoring enormous data sets becomes incredibly challenging with traditional methods.
• Unique regulatory requirements: Banks in Southeast Asia (SEA) operate within a complex regulatory environment, where requirements can vary significantly from country to country. For instance, anti-money laundering (AML) laws in Singapore might differ from those in Indonesia. Traditional transaction monitoring systems often lack the flexibility to adapt to these diverse regulations, leading to potential compliance issues. Failure to meet regulatory standards can result in hefty fines and damage to a bank’s, making it essential for banks to invest in more agile systems that can accommodate varying compliance needs.

Why GBG Predator?

GBG Predator is designed to overcome these challenges to mitigate bank’s fraud risk and financial losses, and offers a wide range of advantages, including:

• highly customisable features allowing banks to tailor their fraud prevention strategies to specific risk and regulatory requirements.
• ability to triage alerts faster by performing block fraud, mark transactions as genuine or suspicious and add values to a watchlist (eg. Account number, merchant number or terminal ID) with inbuilt shortcuts in a single click. It helps bank to improve and speed up investigation process.
• tracks transactions across a variety of channels, such as e-commerce sites, digital banking, and mobile payments. This all-inclusive coverage provides a full understanding of potential dangers and guarantees the protection of all fraud entry points.
• leveraging predictive analytics, Predator proactively identifies new anomalous behavioural patterns and uses machine learning to detect evolving fraud tactics.
• ability to handle large transaction volumes, Predator can process and validate data efficiently, saving banks operational costs and manpower.
• allowing banks to setup with proven detection models and analytics for Anti-Money Laundering (AML) compliance. Additionally, Predator provides customisation of use case scenarios and workflows to accommodate differing regulatory requirements by country.

Conclusion

The ever-evolving landscape of transaction fraud demands a sophisticated defence. Traditional rule-based systems are simply no match for today's savvy cybercriminals.

GBG Predator enables banks to overcome the challenges of transaction monitoring and protect their customers' hard-earned money.

By leveraging GBG Predator, banks can:

• Customise the solution to meet specific risk and regulatory requirements.
• Efficiently triage alerts to expedite the investigation process.
• Proactively identify new fraud tactics using predictive analytics and machine learning.
• Process and validate data efficiently, reducing operational costs.
• Adhere to anti-money laundering regulations through customisable workflows and detection models.

By implementing GBG Predator, banks can significantly enhance their ability to detect and prevent fraud, protect their customers, and mitigate financial losses.

Contact GBG today to learn how you can build a robust defence for your organisation against fraud and ensure a secure banking experience for your customers.

References:

1. OJK,2023. https://www.ojk.go.id/

2. Deloitte 2023. https://www2.deloitte.com/my/en.html

3. Euromonitor International, 2023. https://www.euromonitor.com/

4. BSP, 2023. https://www.bsp.gov.ph/SitePages/Default.aspx

5. APWG, 2023. https://apwg.org/

6. Bank of Thailand, 2023. https://www.bot.or.th/en/home.html

7. CISA, 2023. https://www.cisa.gov/

8. Bank Negara Malaysia, 2023. https://www.bnm.gov.my/