Revenue Model & Business Metrics
MONETIZATION_STRATEGY_CONFIRMED
LENDING_CLIENTS = 3 INR per data fetch (one-time fetch per consent)
PFM_CLIENTS = 0.10 INR per active user per month (recurring fetch users)
EXAMPLE_BILLING = 5L data fetches * 3 INR = 15L INR/month OR 5L active users * 0.10 INR = 50K INR/month
PURPOSE_CODE_CORRELATION = 103 (lending), 101/102 (PFM), 104/105 (account query)
BUSINESS_POSITIONING_UPDATED
MARKET_POSITION = Top 3 AAs in India
MARKET_LEADER = OnemoneyAA (70% share via Bajaj Finance exclusive)
GROWTH_TARGET = 2x market rate (market 10% → finvu targets 20%)
LONG_TERM_VISION = 40% market share if sustained 2x growth
COMPETITIVE_ADVANTAGE = diverse client portfolio vs single-client dependency
CLIENT_PORTFOLIO_CONFIRMED
CURRENT_CLIENTS = [Navi, Cred, Axis, RKB Finance, ICICI, Bajaj Finance]
HISTORICAL_STRENGTH = PFM-heavy client base
CURRENT_FOCUS = Diversification into lending (ICICI, Bajaj partnerships)
STRATEGIC_IMPERATIVE = Balance PFM + Lending (lending more profitable but difficult)
BUSINESS_POSITIONING = Gateway product similar to OTP providers
FUNNEL_TRACKING_COMPREHENSIVE
EXECUTIVE_FUNNEL_5_STAGE
CI = Consents Initiated
CA = Consents Approved
CF = Consents Fulfilled (1st Successful Data Fetch)
DRI = Data Fetch Request Initiated
DRF = Data Fetch Request Fulfilled
OPERATIONAL_FUNNEL_8_STAGE
AA_client_Initialization → OTP_Based_Sign_in_Sign_up → View_Consent_Details → Discovery → Linking → Approved_Consent_Requests → Rejected_Consent_Requests → FIP_Accepted_Consent_Artefacts → FIP_Rejected_Consent_Artefacts → Data_Fetch_Success → Data_Fetch_Failed → Data_Fetch_Not_Attempted
DRILL_DOWN_CAPABILITY
LEVEL_1 = 5-stage executive funnel
LEVEL_2 = 8-stage operational breakdown
LEVEL_3 = Error categorization (NO-RECORDS-FOUND/FAILED/SUCCESSFUL)
LEVEL_4 = API level analysis (eventName + HTTP response codes)
LEVEL_5 = Individual transaction logs
LATENCY_REQUIREMENT = <3 seconds across all levels
ANALYTICAL_ENHANCEMENT_REQUIREMENTS
PURPOSE_CODE_SEGMENTATION_DETAILED
101 = Personal Finance Monthly monitoring (PFM recurring revenue)
102 = Personal Finance High frequency monitoring (PFM recurring revenue)
103 = Financial Reporting One-time (LENDING per-fetch revenue)
104 = Account Query Regular monitoring
105 = Account Query One-time status check
BUSINESS_IMPACT = purpose code determines billing model + success pattern prediction
REVENUE_PATTERN = 103 drives per-fetch revenue, 101/102 drive recurring revenue
SAHAMATI_REPORTING = Purpose code wise breakdown required
CUSTOMER_IDENTITY_RESOLUTION_ENHANCED
CURRENT_LIMITATION = mobileno@finvu ≠ unique individual user
REALITY = multiple phone numbers per person for different bank accounts
SOLUTION_AVAILABLE = masked account numbers for enhanced deduplication
DW_ENHANCEMENT = proper customer identity resolution while maintaining data blind compliance
BUSINESS_VALUE = improved customer lifetime value tracking + revenue attribution
FI_TYPE_BREAKDOWN_COMPREHENSIVE
DATA_TYPES = [DEPOSIT, TERM_DEPOSIT, RECURRING_DEPOSIT, SIP, CP, GOVT_SECURITIES, EQUITIES, BONDS, DEBENTURES, MUTUAL_FUNDS, ETF, IDR, CIS, AIF, INVIT, REIT, GSTR1_3B]
BUSINESS_VALUE = different FI types have different success rates + revenue potential
ANALYTICS_NEED = FI type performance correlation with funnel success
SAHAMATI_REPORTING = FI Type wise breakdown required
DIMENSIONAL_SEGMENTATION_COMPLETE
LICENSE_TYPE = [SEBI, RBI, Others] regulatory categorization
CLIENT_TYPES = [Regulated_FIUs, LSPs(Loan_Service_Providers)]
TSP_SEGMENTATION = technical service provider performance tracking
JOURNEY_TYPE = assisted vs DIY performance comparison
USER_TYPE = new vs existing user behavior patterns
FIP_HEALTH = provider-specific performance attribution
REGULATORY_REPORTING_INTEGRATION
SAHAMATI_REPORTING_REQUIREMENTS
DAILY_METRICS = [AA-FIP performance, timelag metrics, FI ready ratios]
MONTHLY_BREAKDOWN = [Consents Raised, Consents Approved, Successful Data Fetch per consent, Successful Data Fetch per FIP]
PURPOSE_CODE_WISE = Monthly counts across all metrics
FI_TYPE_WISE = Monthly counts across all metrics
AUTOMATION_TARGET = Replace manual report generation
RBI_COMPLIANCE_METRICS
MONTHLY_REPORTS = [FIP Details, FIU Details, Business Metrics]
CURRENT_SCALE = 59 FIPs, 197 FIUs onboarded (as of May 2025)
TRANSACTION_VOLUMES = Consent + Data fetch metrics
COMPLIANCE_TRACKING = Regulatory adherence monitoring
ASSISTED_JOURNEYS = bank branch RMs, higher success rates, traditional pdf replacement
DIY_JOURNEYS = PFM users, educated audience, lower success rates
BUSINESS_INSIGHT = assisted journeys more reliable for lending conversion
REVENUE_CORRELATION = assisted vs DIY impact on billing model effectiveness
COMPETITIVE_DYNAMICS_DETAILED
VALUE_PROPOSITION = reliability vendor (not high leverage position)
SALES_CHALLENGE = selling "reliability" of financial data gateway
MARKET_ANALOGY = like UPI for financial metadata (not transactions)
DIFFERENTIATION = diverse client base vs competitor single-client dependency
FUTURE_POSITIONING = Performance + Latency + Success Rate differentiation
CLIENT_SERVICES_PLANNED = Support AI, FIU Dashboard, Debug tools
KPI_TRACKING_APPROACH_ENHANCED
LEAD_INDICATORS = top funnel volume, user growth, consent initiation trends
LAG_INDICATORS = conversion rates, revenue per client, churn analysis
ANALYSIS_FREQUENCY = daily funnel + MTD growth percentages
DRILL_DOWN_APPROACH = stage-wise drop-off analysis for improvement identification
GROWTH_RATE_FOCUS = 2x market rate achievement monitoring
MARKET_SHARE_TRACKING = progress toward 40% market share target
ORGANIZATIONAL_ALIGNMENT_UPDATED
BUSINESS_TEAM = [Vishwa (Product Manager), Dilip (COO)] → metric definitions + evolution
CUSTOMER_SUCCESS_TEAM = [Customer Support, COO, Product Team] → user experience + retention focus
TECH_TEAM = [Devs, DevOps, CTO] → reliability + performance focus
SHARED_METRIC = funnel success rate (tight coupling between sales + tech)
REPORTING_CADENCE = Daily (T-2) → End-of-day + Early morning (target improvement)
