Overview

Easily plug-and-play Scanner's Fraud Detection Suite into any customer profiling or underwriting system.

Traditional risk assessment methods no longer provide sufficient protection against sophisticated fraud attempts. Single-dimensional evaluations create vulnerabilities that bad actors can exploit.

The Fraud Intelligence API Suite is a solution designed to empower organizations with comprehensive risk insights through a multi-dimensional approach.

Scanner Fraud Detection API provides a score between 100 (baseline to create an even score distribution) to 1000.

By analyzing digital identity patterns, financial behavior, and employment stability, businesses can make confident decisions with unparalleled accuracy.

Comprising three powerful components—Digital Identity Intelligence, Financial Services Score, and Employment Stability Score—this suite transforms how businesses evaluate fraud risk, onboard customers, and protect their operations.

Traditional risk assessment relies too heavily on isolated data points, creating blind spots in fraud detection. Our Fraud Intelligence Suite fills these gaps by offering:

Comprehensive Risk Profiling: Understand potential customers across three critical dimensions
Enhanced Fraud Prevention: Detect sophisticated fraud patterns invisible to single-metric systems
Operational Efficiency: Reduce manual reviews with automated, accurate risk scoring

API Variants

The Fraud Intelligence API is available in two variants to meet different business needs:

Fraud Detection Basic API

The Basic variant provides essential fraud intelligence through our core triple-layer assessment:

Digital Identity Intelligence
Financial Credibility Score
Employment Validity Score

This variant delivers reliable risk assessment for standard verification needs with optimized API calls and cost-effective implementation.

Fraud Detection Advanced API

The Advanced variant builds upon the Basic foundation with additional dimensions:

Location Intelligence: Analyzes geographical patterns, device location consistency, and travel anomalies
E-commerce Behavior: Evaluates purchase history, return patterns, and transaction consistency

The Advanced API provides deeper insights for high-risk scenarios and premium fraud prevention needs.

Key Features of the Fraud Intelligence API Suite

Triple-Layer Risk Assessment: Evaluate users through digital footprint, financial behavior, and employment stability
Unified Risk Score: Receive a single, weighted risk score alongside detailed component breakdowns
Data-Rich Insights: Access granular data points that support the risk assessment
Enterprise-Grade Integration: Benefit from APIs designed for reliability, speed and security

Industry Application Matrix

The table below illustrates how different industries can leverage both the Basic and Advanced API variants:

Industry	Basic API Applications	Advanced API Applications	Key Benefits
NBFCs & Banks	Loan application screening, Account opening verification	Credit limit optimization, High-value transaction monitoring	40-60% reduction in application fraud
Fintech Lenders	First-level customer screening, Quick loans assessment	Alternative credit scoring, Custom risk models	30-45% improvement in underwriting accuracy
Insurance	Policy application verification, Claim validation	Premium personalization, Fraud pattern detection	25-35% reduction in fraudulent claims
E-commerce	Basic customer verification, COD order validation	Order fraud prevention, Customer lifetime value prediction	50-70% reduction in order fraud
Wealth Management	Client onboarding, KYC verification	High-net-worth client profiling, Investment risk matching	Enhanced compliance and personalization
Payment Platforms	Transaction screening, Wallet loading validation	Merchant risk scoring, Cross-border transaction monitoring	Real-time fraud detection capabilities

Fraud Intelligence Components

1. Digital Identity Intelligence - Validating Digital Identity Authenticity

The Digital Identity Intelligence component evaluates the consistency and credibility of a user's digital presence to identify potential identity fraud.

Phone Tenure Assessment: Analyze the longevity of mobile number ownership as a stability indicator
Digital Presence Verification: Evaluate social profile depth and platform diversity
Impersonation Risk Detection: Identify suspicious patterns in digital history timelines
Multi-Platform Analysis: Examine presence across 20+ digital platforms
Time-Based Evaluation: Consider the maturity of digital footprints for risk assessment

Key Metrics Provided:

Digital Age Indicators
Social Profile Depth
Phone Tenure Score
Digital-Physical Identity Alignment
Platform Verification Status

Sample Use Case: A new loan applicant has a thin credit file but shows a 10-year phone tenure and consistent digital presence across multiple verified platforms for 8+ years, suggesting lower identity fraud risk despite limited traditional credit data.

2. Financial Credibility Score - Analyzing Financial Behavior Patterns

The Financial Credibility Score component examines credit bureau data and financial behavior patterns to identify suspicious activity and assess creditworthiness.

Credit History Analysis: Evaluate established patterns from credit bureaus
Delinquency Pattern Detection: Identify concerning payment behavior with recency weightings
Utilization Pattern Monitoring: Flag both suspiciously low and high credit utilization
Account Stability Assessment: Analyze longevity, consistency and diversity of credit relationships
Inquiry Frequency Tracking: Detect potential credit stacking through inquiry patterns

Key Metrics Provided:

Bureau Score Interpretation
Delinquency History Score
Credit Utilization Patterns
Account Stability Indicators
Credit History Duration
Inquiry Frequency Analysis
Suspicious Pattern Examples

Pattern	Description	Potential Risk
Credit Stacking	Multiple inquiries across lenders in short timeframe	Bust-out fraud
Ultra-Low Utilization	Accounts maintained but barely used (<5%)	Synthetic identity
Sudden Closure	Multiple accounts closed simultaneously	Debt evasion

3. Employment Validity Score - Verifying Career Credibility

The Employment Stability Score component analyzes employment tenure, continuity, and employer credibility to validate claimed employment history.

Tenure Analysis: Measure employment duration as stability indicator
Recency Verification: Assess current employment status and gap periods
Employer Credibility Check: Validate against established employer databases
Employment Consistency: Identify suspicious patterns in work history
Documentation Validation: Verify employment claims through official records

Key Metrics Provided:

Employment Duration Score
Recency & Continuity Indicators
Establishment Credibility Rating
Employment Status Verification
Exit Reason Analysis (when applicable)

The Unified Fraud Intelligence API

The power of the Fraud Intelligence Suite lies in its unified approach. The consolidated API:

Combines all three component scores with appropriate weightings (35% Digital Identity Intelligence, 35% Financial Credibility Score, 30% Employment Validity Score)
Delivers a single, comprehensive risk score between 0-1 (higher scores indicate lower risk)
Categorizes risk into actionable levels: Low, Medium, High, and Very High
Provides both the consolidated score and individual component scores
Returns results within 300ms for seamless integration into existing workflows

Advanced API Additional Components

4. Location Intelligence (Advanced API Only)

The Location Intelligence component analyzes geographical patterns to identify suspicious location-based activities.

Address Verification: Cross-reference provided addresses with official records
Device Location Analysis: Track consistency between declared and actual device locations
Travel Pattern Analysis: Flag unusual travel patterns inconsistent with user profile
Geo-fencing Alerts: Identify transactions or activities from high-risk geographical areas

Key Metrics Provided:

Address Verification Score
Location Consistency Rating
Travel Pattern Analysis
Geo-risk Assessment
IP Location Verification

5. E-commerce Behavior Analysis (Advanced API Only)

The E-commerce Behavior component examines purchasing patterns across major platforms to identify abnormal activities.

Purchase History Analysis: Evaluate consistency and patterns in online purchases
Return Behavior Assessment: Identify suspicious return patterns that may indicate fraud
Order Value Patterns: Analyze transaction value patterns and detect anomalies
Shipping Address Consistency: Verify consistency between shipping addresses and declared residence

Key Metrics Provided:

Purchase Pattern Score
Return Behavior Rating
Transaction Value Analysis
Shipping Consistency Verification
Platform Diversity Assessment

Use Cases

NBFC & Bank Use Case Applications

Use Case	Challenge	API Solution	Sample real-world companies who can potentially plug this into their journey
Loan Application Fraud Prevention	Synthetic identities applying for loans with falsified documents	Basic API identity validation + employment verification	Major lenders such as Aditya Birla Finance, Tata Capital, Fullerton India
Account Takeover Prevention	Fraudsters attempting to reset passwords or add new phone numbers	Digital Identity Intelligence + Phone Tenure Analysis	IIFL Finance, Shriram Finance
Credit Line Increases	Determining safe credit limit increases for existing customers	Financial Credibility Score + Advanced E-commerce Analysis	Major NBFCs, Consumer Finance Companies
Digital Onboarding	Streamlining the customer acquisition process while maintaining security	Combined identity verification suite	Digital-First NBFCs, Neo-lending Platforms

Fintech Use Case Applications

Use Case	API Component Focus	Implementation Benefit	Sample real-world companies who can potentially plug this into their journey
Thin-file Borrower Assessment	Digital Identity Intelligence	Enables lending to creditworthy customers without traditional credit history	Lendingkart, Capital Float
Gig Economy Worker Loans	Employment Stability + Digital Identity	Validates inconsistent income sources	KreditBee, Flexi Loan
Buy-Now-Pay-Later Approval	Basic API + E-commerce Behavior	Instant approval with minimized fraud risk	BNPL Providers, MoneyTap
Microlending Verification	Phone Tenure + Digital Identity	Cost-effective verification for small loans	Microfinance Platforms
Line of Credit Management	Advanced API Suite	Dynamic credit limit adjustments based on behavior	Digital Credit Line Providers

Decision Outcome Matrix

This table shows typical outcomes based on different risk indicator combinations:

Digital Identity Score	Financial Score	Employment Score	Typical Decision Outcome	Suggested Actions
Strong	Strong	Strong	Automatic Approval	Offer premium products/limits
Strong	Strong	Weak	Conditional Approval	Employment verification, reduced limits
Strong	Weak	Strong	Manual Review	Additional financial documentation
Strong	Weak	Weak	High-Risk Flag	Enhanced due diligence required
Weak	Strong	Strong	Manual Review	Identity verification call
Weak	Strong	Weak	High-Risk Flag	Possible synthetic identity
Weak	Weak	Strong	Rejection	Application likely fraudulent
Weak	Weak	Weak	Automatic Rejection	High probability of fraud

Risk Indicator Patterns by Industry

Industry	High-Risk Indicators	Medium-Risk Indicators	Low-Risk Indicators
Banking	New phone number, inconsistent employment history, address mismatch	Recent credit inquiries, moderate utilization, limited digital footprint	Long phone tenure, stable employment, consistent addresses
Insurance	Multiple policy applications, inconsistent personal details, new phone number	Recent address changes, limited digital history, average claims history	Established customer, verified employment, strong digital presence
E-commerce	Address-phone number mismatch, new account with high value order, unusual device location	New account with normal order pattern, moderate digital footprint	Established order history, verified digital identity, consistent behavior
Investment	Multiple account attempts, rushed high-value transactions, thin digital identity	Recent phone number change, limited transaction history	Long-term digital footprint, verified employment, consistent behavior
Lending	Credit stacking attempts, employment inconsistencies, digital identity gaps	Recent credit inquiries, moderate digital footprint	Strong identity verification, stable employment, good credit behavior

Implementation ROI by Sector

Sector	Average Implementation Time	Typical Fraud Reduction	Cost Savings Potential	Customer Experience Impact
NBFC	4-6 weeks	40-60%	₹3-5 Cr annually for mid-sized NBFC	15% faster approvals
Fintech	2-4 weeks	30-50%	₹50-80 lakhs per 10,000 loans	30% faster onboarding
Insurance	6-8 weeks	25-40%	3-5% of annual claims value	Reduced documentation burden
E-commerce	3-5 weeks	50-70%	1-2% of GMV	Frictionless checkout for verified users
Wealth Management	4-6 weeks	20-35%	Reputation protection	Premium client experience

Advanced API Application by Customer Lifecycle Stage

Lifecycle Stage	API Components Used	Business Objective	Success Indicators
Acquisition	Digital Identity, Location Intelligence	Verify new customer legitimacy	Reduced fraud at onboarding
Activation	Digital Identity, E-commerce Behavior	Encourage initial transaction	Higher activation rates
Transaction	Financial Score, Employment Score	Optimize transaction limits	Increased transaction volume with stable risk
Growth	Full Advanced API Suite	Cross-sell/upsell safely	Higher lifetime value with controlled risk
Retention	Digital Identity, Financial Score	Identify at-risk accounts	Reduced churn, early fraud identification
Reactivation	Full Advanced API Suite	Safely re-engage dormant customers	Controlled risk in reactivation campaigns

Fraud Intelligence Use Cases

Use Case 1: Reducing Loan Application Fraud at NBFCs

Scenario: Fraudsters apply for instant personal loans using synthetic identities or stolen credentials.

Customer Journey:
A customer applies online for a ₹5 lakh loan, providing a phone number, PAN, and employment details.

How the Fraud Intelligence API Helps:

Credit History: Checks if the phone number is linked to a credit bureau profile with inconsistencies
Phone Age: Flags numbers which are very few months/days old (common in fraud applications)
Employment Verification: Detects mismatches between claimed employment and digital records

This API can be potentially plugged into systems in organizations such as:

Aditya Birla Finance
Tata Capital
Fullerton India
IIFL Finance
Shriram Finance

Use Case 2: Preventing Account Takeover Fraud in Banking

Scenario: Fraudsters attempt to hijack a customer's account by requesting a password reset or linking a new phone number.

Customer Journey:

A customer receives an SMS about a password reset request they didn't initiate
The fraudster uses social engineering to add a new phone number to the account

How the Fraud Intelligence API Helps:

Phone Age Check: Flags if the newly linked number is very few months/days old (typical of burner numbers)
Digital Age & Social Media: Detects minimal digital footprint associated with the number
Employment History: Cross-verifies if employment details linked to the phone number mismatch the customer's profile

Organizations Benefiting:

Major Private Banks
Neobanks and Payment Banks
Payment Service Providers

Use Case 3: Enhancing Underwriting Accuracy for Fintechs

Scenario: Fintech lenders need to make quick credit decisions for thin-file borrowers without traditional credit history.

Customer Journey:

A gig worker with limited banking history applies for a small working capital loan
The fintech needs to assess creditworthiness beyond traditional credit bureau data

How the Fraud Intelligence API Helps:

Digital Footprint Analysis: Evaluates stability and consistency of digital presence
Phone Tenure: Correlates phone ownership stability with repayment likelihood
Employment Verification: Confirms current employment status and income stability
E-commerce Analysis (Advanced API): Examines spending and repayment patterns on marketplace platforms

Organizations Benefiting:

Lendingkart
Capital Float
KreditBee
Flexi Loan
MoneyTap

Use Case 4: Customer Profiling for Targeted Financial Products

Scenario: Financial institutions need to segment customers accurately for personalized product offerings.

Customer Journey:

A customer visits a financial service provider's website
The provider needs to quickly determine appropriate product offerings

How the Fraud Intelligence API Helps:

Financial Stability Assessment: Determines appropriate credit limits and interest rates
Employment Stability: Identifies suitable loan tenures based on employment history
Location Intelligence (Advanced API): Customizes offerings based on geographical factors

Organizations Benefiting:

Wealth Management Firms
Insurance Providers
Investment Platforms
Mutual Fund Distributors

Use Case 5: E-commerce Order Fraud Prevention

Scenario: Online retailers need to identify potentially fraudulent orders before shipping high-value products.

Customer Journey:

A customer places a high-value order requesting express delivery
The e-commerce platform needs to verify the legitimacy of the order

How the Advanced API Helps:

Phone Tenure Analysis: Identifies newly created phone numbers
Digital Footprint Verification: Confirms the customer has an established online presence
Location Intelligence: Checks if the shipping address matches historical addresses
E-commerce Behavior Analysis: Compares the order with previous purchasing patterns

Organizations Benefiting:

E-commerce Platforms
Luxury Goods Retailers
Electronics Marketplaces
High-Value Service Providers