Mr. Pipit Aneaknithi, KBank President, disclosed that KBank handles a huge amount of big data which are increasing at all times; most of them are related to numerous types of financial transactions. These data can be analyzed for enhanced understanding of customers' needs. Through data analytics technologies, we are able to conduct forecasts and introduce new methods conducive to business operation in order to increase our competitiveness, explore new business opportunities, create income over the long term and ensure maximized efficiency yet minimized operating cost. To this end, KBank has established two departments under the Corporate Strategy Management Division. They are, i.e.,
Enterprise Data Analytics Department (EA) acts a center for bolstering capabilities for analytics use case of KBank, seeking and allocating resources to support data analysis, monitoring and handling business data analytics in order to create a data-driven culture in our organization. The department is also responsible for providing advice on in-depth data analysis to KBank units and customers in support of KBank strategies of becoming a Data-Driven Bank.
Digital Lending Department (DL) is responsible for analyzing insights derived from multiple databases to offer loan products that meet the needs of each customer at appropriate Personalized Risk Based Pricing. DL enhances opportunities to generate revenue, boost efficiency and reduce credit risk exposure for KBank. Additionally, DL supervises the framework for Digital Lending Platform to deliver comprehensive services on K PLUS application which will increase convenience and create new experiences for customers in the digital age. Clients will obtain the results of their loan applications and the loan is credited to their accounts within one minute. Lending Service Platform will also be developed to explore new revenue sources for KBank.
In addition, KBank has planned to recruit data analytics personnel and boost their capacities to make the work assignments special, interesting and different from other organizations by adding the Data Alchemist position which focuses on transforming big data with Advanced Analytics technique into a successful business formula. Data Alchemists will work seamlessly with other business units under the "Turning Data into Gold: the Ultimate of Advanced Analytics" concept as business opportunities and challenges that KBank is currently facing present the right timing for the country's data analytics personnel to learn, develop, and leapfrog their capacities. KBank has planned to revise the corporate capacity development plan and career path management to make them more effective, clear and appropriate for this group of talents.
KBank is determined to become a Data-Driven Bank by cultivating a Data-Driven Culture and establishing four key fundamentals within KBank as follows:
1. Establish the single source of data and promote interdepartmental data access and the use of data under new models while maintaining maximum customer data privacy.
2. Provide infrastructure and tools which are software programs to ensure that data analytical tools are in place and ready for various usages across the Bank.
3. Create talents by providing courses to improve skills of the targeted employees throughout KBank to enable them to use advanced data analytical tools, thus benefiting every unit within the organization. KBank has also organized a community of data analytics talents to share knowledge and experience.
4. Develop agile work process in order to realize use cases by encouraging employees to raise meaningful questions and use data for analyses in order to find business solutions, solve problems and create new business models.
Mr. Pipit added that such strategies will not only enable KBank to become a full-fledged data-driven bank, but also create useful services for our customers. KBank has also set a target to use big data for the development of at least 400 use cases within 2018, thus helping us generate income or cut costs by not less than 2 billion Baht. By 2020, KBank will use big data to generate income or reduce costs by more 50 percent.