You choose the customer group you want to explore – e.g., your most loyal buyers, recent defaulters, churned users, or high-conversion leads.
No data modeling needed – just your business question.
2. Data Enrichment & Profile Creation
SocialScore automatically collects and enriches external data (digital footprint, social activity, device info, communication channels, interests) for each user in the group.
Everything happens in the background – no coding, no integrations.
3. Segment & Persona Generation
Our AI engine groups users by common traits and creates dynamic personas. You now see behavioral clusters, dominant interests, preferred channels, and even risk factors.
Understand who they are – and what drives them.
4. Action-Ready Insights & Predictive Targeting
You receive a full visual analysis – ready to compare, act, or use for predictive targeting. Want to find similar future customers? Just click “Create Predictive Model” – it’s built automatically.
No data teams. No delays. Just better decisions.
SocialScore offers substantial advantages to financial institutions:
FINTECH DIGITAL CUSTOMER PERSONA
Risk Mitigation: Identify and mitigate risks by analyzing customer digital footprints and behaviors.
Enhanced Customer Insights: Tailor marketing and products with deep customer knowledge, improving satisfaction.
Fraud Detection: Detect and prevent fraud in real-time through behavior analysis.
Compliance and KYC: Streamline KYC processes and ensure regulatory compliance. KYC -> UYC (Understand Your Customers)
Competitive Advantage: Stand out with personalized services and superior risk management.
Doble verification: Uncover real personality behind the form.
Before SocialScore:
Traffic: 100,000 users/month
Applications: 10,000 (10% conversion)
Loans given/month: 3,500 (35% approval rate)
Default rate: 10% (350 loans x €5,000 = €1,750,000 losses)
Monthly revenue: 3,150 loans x €5,000 = €15,750,000
Marketing spend: €300,000 (€100 per acquisition)
After SocialScore:
Verified contact details (+20% effective communication)
Improved approval rate (+5%, now 40%, 4,000 loans)
Reduced default rate by 2% (now 8%, 320 defaults, €1,600,000 losses)
More precise targeting (+10% traffic, 11,000 applications)
The overall Gini Coefficient is 30+.
Total of 300+ variables
New Monthly Results:
Loans approved: 4,400 (40% of 11,000 applications)
Loans repaid: 4,048 x €5,000 = €20,240,000
Losses: 352 x €5,000 = €1,760,000
Revenue gain: +€4,490,000 monthly
SocialScore cost: €3,500
Annualized Net Impact: Additional €53,880,000 revenue