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Data management at LINE and financial data util...

Data management at LINE and financial data utilization

LINE DevDay 2020

November 27, 2020
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  1. Data Science & Engineering Center Data Science & Engineering Data

    Governance Data Strategy Inquiry Management Business Consulting Data Product Management Data ETL Data Engineering IU Dev Data Solutions Cloudera PS/PSE Data Science 1-4 Machine Learning 1-2 DSP ML OCR Voice Speech NLP Speech & Voice Planning SET Delivery Infra Observability Infra Data Management Data Platform Data Labs Engineering Infrastructure
  2. Mission of DSE Center Democratize Data for business consumers Machine

    Learning Engineering Data Science Data Governance
  3. Role & Responsibility of Data Management We have 4 categories

    for data utilization Offense Defense System Strategy
  4. Initiatives of Data Strategy We are promoting in terms of

    3 axis such as Human Resource, Goods and Capitals Mono(Goods) Promotion Promotion of understanding data Hito(Human Resource) Education Increase people who can utilize data Kane(Capital) Value Contribute to business profit
  5. Support decision-making for customer acquisition and service improvement by sharing

    according to the business situation Offensive Data Utilization Support Data Platform Data Planner Data Scientist / ML Engineer Services LINE Users Data Management Dept. Data Labs
  6. Develop rules and provide feedback in collaboration with information security

    and legal staff Strengthening Defense Making rules Penetration Bottom Up Top Down Inquiry management Authorization Information Security Privacy Compliance Gathering requests Identifying issues Documentation Announcement Seminar Survey Improvement
  7. Systemizing for improving operational efficiency and strengthening data management Systemization

    and Product Management Data from Services Data ETL Cross-group Data Service-specific Data Data Products Platform Service Utilizing based on Data Governance
  8. Data Management Communication Data Strategist Data Evangelist Service Inquiry Supporter

    / Data Manager Data Planner Data Scientist Data Product Manager ML Engineer Data Platform Engineer ETL Engineer Data Management Department Information Security Privacy Legal Data Governor
  9. Data Voyage Program Trying to improve the level of maturity

    Maturity Level Lv0 Lv1 Lv2 Lv3 Strategy / Offense D : Education for new comer A : Data Utilization Defense B : Data Open Orientation System C : IU Boot Camp
  10. Data Voyage Program Session Menu Pgm ID Title Audience Time

    Type A1 Sharing session PM, Planner 1.5h Presentation A2 Workshop of data utilization PM, Planner 3h x 2 Workshop B1 Data Open Orientation All 1.5h Presentation C1 IU Boot Camp Planner, Engineer 3h Hands-on AC1 Tableau User Session Tableau User 1.5h Presentation D1 Orientation for new comer New Comer 1h Presentation
  11. Have to care a lot of fintech specific confirmation points

    Preparation for Using Data Data Owner Data Integration Information Security Compliance Common ID Privacy Policy Legal Confirmation FSA JV Agreement Internal Contracts Tax Requirements and others… Application Approval Data Ingestion Labeling Access Control A kind of wall…
  12. Direction of Data Utilization Own business data and group data

    Sending LINE Users LINE KPI of own business Fintech 2 1 3 Sharing Fintech Data
  13. Analyze customer behavior such as opening an account or starting

    a transaction KPI of Own Business Viewing Information Starting Trading Access Opening Account User Logs User Logs Transaction User Logs Campaign Analysis Report Understand Service Download App Application Upload KYC Check Status Consider Investment Deposits Withdrawals Order Contract
  14. Utilizing LINE User Data Approach from lookalike to LINE users

    and non-fintech users Fintech Data LINE User Data (ML Completed) lookalike Fintech User Scoring by machine learning Non-fintech User Similarity Score A:76% B:82% C:55% ・・・
  15. A Case of Lookalike LINE User Data (ML Completed) lookalike

    Non-fintech User and LINE Pay User LINE Pay User and Pocket Money User Deliver the LINE Pocket Money banner with LINE Pay official account
  16. Sharing Fintech Data Sharing Fintech specific data with LINE User

    data Fintech Data LINE User Data (ML Completed) Algorithm Fintech User Non-Fintech User Estimate the attributes of non-fintech users by machine learning (Predictive Data) …
  17. A Case of Sharing Fintech Data LINE Score Data LINE

    User Data (ML Completed) Ad Service (Segment Info.) Training Data Estimated Data Advertiser
  18. Summary About Fintech Data Management Handling data for the entire

    LINE including fintech data with very strong characteristics Performing various tasks from data analysis to contract conclusion work Building relationships globally