Cloudera Empowers Banks in Asia Pacific to Combat Financial Crimes

Cloudera, Inc. announced that more than half of the 30 largest banks in Asia Pacific (excluding state-owned banks in China) have chosen Cloudera to enhance their data strategy to accelerate digital transformation, improve customer experiences, and meet regulatory and compliance requirements. Cloudera also counts eight of the top 10 largest banks in Southeast Asia as customers.

With 75% of companies in the Asia Pacific region falling victim to financial crime over the past 12 months, the pressure is on for financial institutions to rely on data, analytics, machine learning and AI technologies to capitalize on the information needed to combat financial crime. Given the complexity and variety of financial and sensitive customer data, many financial institutions have also transitioned to Cloudera’s cloud-agnostic platform that is optimized for the scale and complexity of the data that the industry demands.

The next generation financial crime platform leverages the power of machine learning and analytics to effectively simulate, predict, and prevent crimes.

“Financial crime is one of the greatest challenges for banks as it not only causes monetary losses but also adversely affects reputation and customer relationships,” said Mark Micallef, Vice President of Asia Pacific and Japan, Cloudera. “Criminal networks are becoming increasingly creative and ready to exploit any opportunity inside or around the edges of business operations. As the need to overcome the siloed and overwhelming data landscape increases, financial services institutions have to adopt innovative approaches to better leverage data and analytics and protect themselves from known and unknown threats, while keeping up with regulatory changes. We are proud to be chosen by top banks in the region to help them make insights-driven decisions to secure their organizations as they grow.”

Bank Rakyat Indonesia

PT Bank Rakyat Indonesia (Persero) Tbk (BRI) is one of the largest state-owned banks in Indonesia which engages in the provision of general banking services. It built a big data platform that is powered by Cloudera Enterprise to analyze the massive amount of customer data it gained over the years. This enabled it to analyze five years’ worth of historical data and use the derived insights to drive more sales through targeted cross-selling and upselling.

BRI also used Cloudera Data Science Workbench to develop a machine learning model for fraud detection. The new system will process and detect fraud in real time by highlighting anomalies found in the stream of events coming from multiple customer touchpoints such as ATMs and internet banking portals.

“As customers are changing the way they bank and given the sophisticated nature of fraud, banks need to leverage data and take a new approach to grow and protect their business,” said Indra Utoyo, Director of IT and Operations, BRI. “Cloudera’s scalable, secure, and compliant platform allows us to gain a comprehensive view of customers, enabling us to continually address their ever-changing demands as well as offer services to the underserved in Indonesia. The new platform also enables the use of machine learning to enhance our fraud detection capability, which will help address the mounting concerns around data security.”

United Overseas Bank

United Overseas Bank (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. Working with Cloudera, UOB built an enterprise-wide big data platform from which its analytics teams can access relevant and quality data to improve business processes and develop new solutions based on artificial intelligence and machine learning. For example, to help in the fight against financial crime, one of the machine learning solutions enabled UOB’s analysts to reduce false positives of suspected money laundering transactions by 40%.

“At UOB, the use of machine learning and data analytics are now core components of our approach to detecting and preventing money laundering,” said Richard Lowe, Chief Data Officer, UOB. “Our collaboration with Cloudera has enabled us to develop solutions that are sharper in identifying patterns and linkages that might signal suspicious transactions and in predicting suspicious activities more accurately.”