- Financial Services
Headquarters: Jakarta, Indonesia
- Modern Data Platform: Cloudera Enterprise
- Workloads: Analytics Database, Operational Database, Data Science & Engineering
- Key Components: Apache HBase, Apache Impala, Apache Kafka, Apache Sentry, Apache Spark, Cloudera Navigator
- Advanced Analytics Tool: Kogentix AMP
- Real-time recommendation engine
- Business intelligence
- Fraud detection
- Anti-money laundering
- 300 percent increase in conversion rate and increased customer retention
- 30 percent reduction in number of fraud incidents
- Reduced marketing costs
- Identified new fraud patterns for improved fraud detection
- Lowered capital expense cost per terabyte
Big data scale
- 1 TB ingested/analyzed daily
Cloudera powers Bank Danamon to improve customer journeys and enhance fraud detection.
Bank Danamon is one of Indonesia’s largest financial institutions, offering corporate and small business banking, consumer banking, trade finance, cash management, treasury and capital markets.
Financial service institutions globally are under immense pressure from a new generation of tech-savvy customers to deliver consumer-centric digital services. These new services represent a massive opportunity as well as a massive risk as more consumers connect to products and services digitally. For Bank Danamon, like many other institutions, one of the key challenges in advancing this digital transformation is the ability to gain a single enterprise view of customer data.
“Each line of business has their own data mart so there are a lot of data silos,” said Billie Setiawan, head, Decision Management Data and Analytics for Bank Danamon Indonesia. “By having a holistic view of the customer behavior across the bank, we can offer the right product for the right customers.”
Bank Danamon uses a machine learning platform powered by Cloudera for real-time customer marketing, fraud detection, and anti-money laundering (AML) activities. The platform integrates data from about 50 different systems and drives machine learning applications to:
- Predict customer needs and determine in real time which offers to give each customer.
- Uncover new suspected fraud patterns and develop preventive triggers to identify fraud incidents.
- Send alerts to customers in real time about potential fraud to improve customer experience and reduce customer complaints.
More than one terabyte (TB) of unstructured and structured data is ingested and analyzed daily, both in batch mode and via live streaming. Data includes transactional, product, internet banking, mobile banking, credit card, customer care, voice, digital log, social media, social economic, and other third-party and external data.
“A key focus for our digital transformation at Danamon is to improve customer service while eliminating fraud risks and compliance cost,” said Mary Bernadette James, chief information officer for Bank Danamon. “Big data technology has enabled us to better manage customer data, while enhancing data protection and managing compliance. Cloudera’s modern data management platform empowers us to achieve our digitalization goals at a lower capital expenditure per terabyte compared to traditional data management mechanisms, giving us the ability to serve our customers better and remain competitive in today’s uncertain economic climate.”
As it implemented a modern data platform, Bank Danamon wanted a full range of analytic capabilities, from descriptive to prescriptive. It used the Kogentix Automated Machine Learning Platform (AMP) to help it effectivity create the advanced machine learning models needed to improve business outcomes. “With Cloudera and Kogentix, we have the tools to help us test, train, and validate models, and analyze model performance over time and improve cost efficiency,” said Setiawan.
Bank Danamon now has the insights to interact with customers in a meaningful way. For example, staff can deliver real-time, localized, and personalized interactions to each customer at the right time, with the right content, and using the right channel. The bank can also observe the performance of interactions in real time, and, based on feedback, self-correct and learn.
In addition to deepening customer relationships, aggregating behavior and transaction data in real time and using machine learning has helped Bank Danamon identify new patterns of fraud. This enables the bank to detect potential fraud sooner and contact customers for clarification to reduce losses. “Using Cloudera, we can improve our customer experiences,” said Setiawan.