Fighting financial crime with advanced machine learning capabilities

RCBC and GBG clinched two major awards at the ABF Retail Banking Awards 2022 with their enterprise risk management technology.

The adoption of the latest digital technologies has been inevitable for most banks and financial institutions amidst the changing landscape of the banking and finance industry, as well as the impacts brought by the pandemic. Organisations were urged to devise their respective digital transformation initiatives and to utilise modern technologies to ensure better operations and customer service.

Whilst this undertaking has provided plenty of opportunities for banks and financial institutions, it also comes with potential risks and issues that are necessary to address. Amongst some of the issues that are identified are fraud and money laundering, with which such exposure could be costly across every aspect of banking operations.

To address this huge concern, Philippine-based, Rizal Commercial Banking Corporation (RCBC) has deployed a robust Enterprise Risk Management technology which leverages the latest cutting-edge technology and machine learning models to detect complex financial crimes and allows them to monitor across multi-channel in a single platform on a real-time basis.

The financial crime management system enables customer and transaction monitoring for fraud detection and anti-money laundering (AML) compliance. It also improves investigator effectiveness and overall cost savings by reducing false positives.

RCBC implemented this solution by collaborating with IT partner GBG, an industry expert in global digital identity and fraud solutions. The latter holds a strong track record and reputation for being able to deliver these types of modernised solutions within project timelines and budgets.

GBG’s solution utilises machine learning to detect real-time invisible correlations in data to uncover new fraud instances quickly, whilst also ruling out the possibility of accidental human error, hence helping to reduce false positives. Beyond the features and capabilities of the solution, GBG also brought in their subject matter experts in the compliance domain to offer consultancy in dealing with pressing financial crime use cases.

The companies’ implementation of the enterprise financial crime management risk system allowed for a fraud loss reduction of 52% YoY, the fast detection of over 60% of suspicious activities with a 0.5% alert rate, and an improvement in false detection rate from 41% to 13%.

The solution is also omnichannel and scalable, providing a user-friendly Web Client user interface that allows the bank to add or maintain the banking channel as required with no development effort involved.

RCBC’s business strategy and goals are aligned with the desire to implement strong controls and automation to improve risk management, as well as to reduce fraud exposure and AML controls. Its clear and strong management support, as well as the close collaboration with GBG, were key factors in the success of the project. 

Through the delivery of this project, the bank was able to move from post-transaction monitoring to real-time transaction monitoring, which supported the bank's strategy to reduce customer experience friction and enable faster transaction authorisation without compromising risks of fraud and AML.

This remarkable solution from both RCBC and GBG has been recognised by the Asian Banking and Finance: Retail Banking Awards 2022, as the companies won the AI & Machine Learning Initiative of the Year - Philippines and the Fraud Initiative of the Year - Philippines.

The recognition highlights the close working relationship between all project parties and departments through a clear project organisation structure and escalation process.


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