Scanner - Overview and Guide

Introduction

This guide provides an in-depth overview of Decentro's Scanner module, designed to augment the data retrieved from government sources in the "KYC & Onboarding" module and alternative data points from the "Bytes" module with advanced machine learning (ML) and computer vision capabilities.

The Scanner module offers a suite of APIs that deliver intelligence and actionable insights, enhancing processes such as identity verification, fraud detection, and compliance.

1. Document Forensics

Applies ML and computer vision techniques to analyze and validate documents, ensuring authenticity and quality.

The Document Forensics suite enables businesses to extract and verify information from various documents, enhancing the accuracy and efficiency of KYC processes.

API	Description	Use Case Example
OCR and Document Data Extraction	Extracts textual data from images of documents using Optical Character Recognition (OCR) technology.	KYC Onboarding: Automatically retrieve customer information from uploaded ID documents to expedite account setup.
Aadhaar Masking	Masks the first eight digits of the Aadhaar number in document images to comply with regulatory standards.	Compliance: Ensure that stored Aadhaar documents adhere to data protection regulations by masking sensitive information.
Document Classification	Identifies and classifies the type of document submitted (e.g., PAN card, passport, driver's license).	Document Management: Automatically sort and categorize incoming documents for streamlined processing.
Forged Document Check	Detects alterations or forgeries in submitted documents.	Fraud Prevention: Identify tampered documents during customer onboarding to prevent identity fraud.
Document Quality Check	Assesses the quality of document images, checking for issues like blurriness or poor resolution.	User Experience: Prompt users to resubmit clearer images, ensuring accurate data extraction and verification.

Implementing these APIs enhances document verification processes, ensuring data integrity and regulatory compliance.

2. Data Forensics

Utilizes advanced algorithms to analyze and match textual and geolocation data, improving identity verification and fraud detection.

The Data Forensics suite provides tools to compare and validate various data points, aiding in the detection of inconsistencies and potential fraud.

API	Description	Use Case Example
Name Matching	Compares names, accounting for phonetic similarities and automatic removal of salutations, to identify matches.	Identity Verification: Match customer-provided names with official records, even with minor spelling variations or different honorifics.
Text Matching	Compares textual data, including phonetic matching, to identify similarities or discrepancies.	Data Validation: Ensure consistency between user-submitted information and existing records, detecting potential fraud.
Geolocation Matching	Compares geolocation data to verify the proximity or consistency of provided addresses.	Address Verification: Confirm that a customer's stated location aligns with geolocation data from their device or transaction history.

These APIs assist businesses in validating customer information, enhancing the accuracy of identity verification processes, and detecting potential fraud.

3. Face Forensics

Employs facial analysis technologies to verify user identity and detect liveness, preventing spoofing attempts.

The Face Forensics suite offers tools to authenticate users through facial recognition and liveness detection, ensuring secure and reliable identity verification.

API	Description	Use Case Example
Passive Face Liveness Test (Image Input)	Assesses whether a single image is of a live person or a spoof (e.g., photo or mask).	Secure Onboarding: Prevent account creation using photos of photos or other static images.
Passive Face Liveness Test (Video Input)	Evaluates a video to determine if it depicts a live person, detecting movements and expressions.	Fraud Prevention: Ensure that live video submissions are from real individuals during verification processes.
Face Match Test	Compares two facial images to determine if they belong to the same person.	Identity Verification: Match a user's selfie with their ID document photo to confirm identity.

Integrating these APIs enhances security during user verification, reducing the risk of identity fraud and unauthorized access.

4. Intelligence Suite

Provides advanced analytical tools to detect fraudulent activities and identify high-risk individuals.

The Intelligence Suite offers specialized APIs designed to uncover complex fraud patterns, aiding businesses in maintaining the integrity of their operations.

API	Description	Use Case Example
Mule Detector API	Identifies potential money mules by analyzing transaction patterns and user behavior.	Anti-Money Laundering (AML): Detect and prevent the use of accounts for illicit money transfers by identifying suspicious activities indicative of mule accounts.

Utilizing this API helps businesses proactively detect and mitigate financial crimes, ensuring compliance with AML regulations.

Use Case Examples for the Entire Scanner Module

Enhanced KYC Processes: By integrating the Document Forensics and Face Forensics APIs, financial institutions can automate and strengthen their KYC procedures, ensuring accurate and efficient customer onboarding.
Fraud Detection and Prevention: The combined use of Data Forensics and the Mule Detector API enables businesses to identify and prevent fraudulent activities, safeguarding their operations and reputation.
Regulatory Compliance: Implementing the Aadhaar Masking and Forged Document Check APIs ensures adherence to data protection regulations and helps maintain the authenticity of customer documents.