Aurélie Fliedel Quicksign "Best practice du Data Product Management "
Comment allier Produit et Business pour mettre la data au service de ceux-ci ?
Comment aligner l'organisation pour fluidifier les process de Data Product management ?
2. • Intro
• QuickSign: who we are
• Data product management: what is it?
• Best practices
Agenda
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#4
3. QuickSign: who we are
• The European leader in digital onboarding for
financial services
• White label B2B2C SAAS platform
• 10 years of expertise
4. Digital onboarding
• Upgraded user experience
• Improved operational efficiency
• Regulatory risks kept under control
5. Real case
c
• x
• Customers’ issue : Fraud is expensive
• Manual fraud detection (often too late!)
• Ever-changing fraud behaviours
Fraud detection
6. Real case
c
• x
• Predictive approach
• Independant algorithm from already-known
fraud patterns
Our solution
7. The Data Revolution has begun
1. Passive use of data
2. Data management and reporting
3. Process and product innovation with data
4. Value generated directly with AI/DL
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#2
#3
#4
9. Key Success Factor #1
Business first
c
• Data speaks for itself… BUT before digging
into data…
• Indentify the customers’ issue and use cases
• Be clear about what the product does
• Define the KPIs to follow
12. Key Success Factor #4
Focused, aligned organization
Data
Product
Manager
Product
Owner
Data
Scientist
Data
Engineer
Dev
Multi-disciplinary feature team
Product
team
Dev back
/ front
DL team Devops
Dev ops
13. Key Success Factor #5
Monitor everything
• Acceptance criteria before going live: key
metrics depending on business goals to
determine if the AI product is accurate
enough
• Sampling to compare human decision and
AI decision all along the product lifecycle
c