North Pacific Bank Ltd. - Disparate data integrated and analytics used to increase profitability and customer satisfaction
Company Size
1,000+
Region
- Asia
Country
- Japan
Product
- IBM FlashSystem 840
- IBM Flex System
- IBM Power Systems
- IBM Storwize V7000
- IBM Cognos Business Intelligence V10
Tech Stack
- IBM InfoSphere
- IBM PureData System for Analytics
- IBM SPSS Modeler
- IBM Tivoli
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Revenue Growth
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Finance & Insurance
Applicable Functions
- Sales & Marketing
Use Cases
- Predictive Maintenance
Services
- Data Science Services
- System Integration
About The Customer
North Pacific Bank Ltd. is the largest financial services institution in Hokkaido, Japan. The bank was established in 1917 and has since expanded through its mergers with Hokkaido Takushoku in 1998 and Sapporo Bank, Ltd., in 2008. North Pacific Bank provides a wide range of financial products and services to both individual and corporate customers. The bank employs more than 3,300 people and operates over 170 branches across Hokkaido, with more than 75 in Sapporo and one branch in Tokyo.
The Challenge
North Pacific Bank Ltd., a major financial institution in Japan, was created through the merger of three major banks. The bank faced a significant challenge in integrating and identifying customer data from each of its previous business entities. This lack of visibility into client behaviors across business channel expansions meant that the bank could not implement an effective customer relationship management (CRM) strategy, which was hindering its marketing efforts.
The Solution
To address its challenges, North Pacific Bank turned to a suite of IBM solutions. The bank implemented IBM FlashSystem 840, IBM Flex System, IBM Power Systems, IBM Storwize V7000, IBM Cognos Business Intelligence V10, IBM InfoSphere, IBM PureData System for Analytics, IBM SPSS Modeler, and IBM Tivoli. These solutions allowed the bank to use information management, business intelligence, and predictive analytics to develop a precise picture of each customer at the household level. With this solution, the bank can offer timely advice to customers based on a precise understanding of their needs, making its cross- and up-selling campaigns more effective.
Operational Impact
Quantitative Benefit
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