क्रेडिट स्कोरिंग त्रुटि से NPA हानि
Definition
Inaccurate manual assessment of post-paid credit limits or deposit requirements using mobile usage data leads to poor lending decisions, increasing non-performing assets.
Key Findings
- Financial Impact: 2-5% revenue loss on credit extended (industry standard for scoring errors); ₹5-20 करोड़ annual NPA drag for large MNOs.
- Frequency: Ongoing per customer scored
- Root Cause: Reliance on manual analysis without AI, ignoring full data patterns
Why This Matters
The Pitch: Wireless services in India lose 2-5% of loan portfolio to bad debts from faulty scoring. Automation with AI alternative data cuts NPA risk.
Affected Stakeholders
Credit Risk Manager, Billing Team, Collections
Deep Analysis (Premium)
Financial Impact
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Current Workarounds
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Methodology & Sources
Data collected via OSINT from regulatory filings, industry audits, and verified case studies.
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मैनुअल टेली-वेरिफिकेशन पर अतिरिक्त लागत
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