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GraphTour - Crédit Agricole: Making the Most of Public Information on our Clients

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Gautier Sartorius CACIB

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GraphTour - Crédit Agricole: Making the Most of Public Information on our Clients

  1. 1. Making the most of public information on our clients Gautier SARTORIUS / 2018 March 6th www.ca-cib.com
  2. 2. Page 2 PanOptes - 2018 March Crédit Agricole CIB, a 3D client focus organisation
  3. 3. Page 3 PanOptes - 2018 March “90% of the data in the world today has been created in the last two years alone” (source : IBM) “19.8% of business time 1 day per week is wasted by employees searching for information”(source: Cotrillresearch) Data exploitation relies on new solutions to sort information and collective intelligence What happens in an Internet Minute
  4. 4. Page 4 PanOptes - 2018 March For banks, information is a vital asset Identify commercial opportunity Conduct risk analysis Analyze environment
  5. 5. Page 5 PanOptes - 2018 March PanOptes, a monitoring of public information solution PanOptes is a monitoring of public information Solution. With the solution, the user can quickly consult the most relevant news:  Articles are automatically classified by identifying companies, topics, subjects, opinion, sentiments, languages, content geographies…  The knowledge database is enriching from the users actions and it will allow to improve the reading recommendation. Capitalization on COLLECTIVE INTELLIGENCE On a CLIENT And tomorrow, on a TOPICS, on a SECTOR, on PEOPLE (without client filter)
  6. 6. Page 6 PanOptes - 2018 March Provide Clients’ insights Provide Clients’ insights through access to 360° real time data from external sources thanks to machine learning and collective intelligence Intrapreunarship initiative supported by IDEA, imagined and created by Gautier Sartorius GMD securitisation I get market insights I identify a business opportunity Will be a transversal solution to sort relevant information about our clients and our sectors I read relevant news
  7. 7. Page 7 PanOptes - 2018 March PanOptes is an intrapreneurship story Growing as an internal start-up :  It was a bottom-up initiative that came from informal exchanges between Business and IT  PanOptes had no sponsor and no mandated team at first  The app was developed with no budget and on creator’s free time at first Listening and matching users’ needs :  Individuals from different product lines voluntarily helped define product  A design thinking workshop was organized to refine customer needs understanding Origination teams’ needs fostered the idea for PanOptes An idea was developed during an hackhathon Collaborative inputs from GMD, CIN and RPC users Support of Idea to prepare first fundraising Audit of the Village to validate value AN INTERNAL START-UP MAKING USERS’ NEEDS THE PRIORITY
  8. 8. Page 8 PanOptes - 2018 March DATA ACQUISITION DATA STORAGE SMART DATA ENGINE GUI DEVELOPMENT Draws strength from the diversity of expertise Data Internal expertises
  9. 9. Page 9 PanOptes - 2018 March A Graph Architecture to more Performance, Flexibility & Request efficiency SEMANTIC ANALYSIS RECOMMENDATION Machine learning … Internal dev. EXPERT SYSTEM … … Internal dev. Pauline Sales person Teddy “early detector” Alix Editorialist Machine learning Elastic Search SMART DATA ---- Event Store
  10. 10. Page 10 PanOptes - 2018 March Build suggestion tool for users, drawing benefits of clustering from Neo4j data Share easily this auto descriptive database especially with Data Scientists Add/import easily new elements direct from Excel file Insert heterogeneous data and describe links among them Modify easily the database structure and refactor when required Neo4j database offers an efficient storage
  11. 11. Page 11 PanOptes - 2018 March Contact : gautier.sartorius@ca-cib.com

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