More About SurfinLab Product

• e-KYC
• Anti-fraud
• Variables
• Credit Score

• e-KYC

  Quickly and accurately identify the authenticity of customer identity

  OCRSelfie&ID ComparisonBiometric RecognitionValidation

  

  Validation

  Validate CURP

  Entering CURP will return information related to the ID card, such as: surname, first name, gender, date of birth, country of birth, province of birth, etc., which can be used to compare the authenticity of self-filled information

  High Accuracy

  Various Key Information Returns

• OCR

  Return the corresponding information on the ID card through word OCR text recognition, and compare it with the self-filled info before the loan, eliminating the high labor and timeliness costs of manual review

  High Accuracy

  High Coverage

  Support Multiple ID Versions C-H

  Support Multiple ID Types INE/IFE/Passport

  Selfie&ID Comparison

  Compare the photo and selfie photo on the IFE/INE card, and return the similarity score, which is used to judge that the loan applicant is the real owner of the ID card.

  Anti-ID Theft

  Photo-blacklist

  High Robustness

  Effectively Identify Low-quality Photos

  Biometric Recognition

  Identify whether the person in front of the camera is a real person through liveness detection can effectively prevent fraudulent behavior using static photos

  Validation

  Validate BVN

  Enter the three elements of bank code, bank account, and BVN to verify the authenticity and owner of the account to prevent information theft.

  High Accuracy

  Various Key Information Returns

  Validation

  Validate Voter Status

  Enter information such as CURP and CIC&OCR to verify whether the owner of the ID card has the legal right to vote, which can effectively verify the validity of the ID card

  Validation

  Job Validation

  Enter the CURP and SSN, and return the historical work records and other information: job start time, end time, daily salary, the province where the company is located, company name or name of the person in charge and other information.

• Anti-fraud

  Multi-measures and multi-methods to identify and monitor fraud, usually within 24 hours from discovery to interception

  BlacklistMultiple-platorm DetectionAbnormal Behavior DetectionComplex Association Detection

  

• Blacklist

  Through the actual historical loan data accumulated by the industry, it detects the blacklist associated with the user's mobile phone number or ID number

  Multiple-platorm Detection

  Through industry big data, based on KYC information such as user's mobile phone and ID number, it can detect the user's loan information on multiple financial platforms, which can effectively prevent the risk of joint debt groups.

  Abnormal Behavior Detection

  Relying on the SDK and H5 as the medium to make risk control on the user's pre-lending behavior data, it can effectively identify abnormal behaviors. Applicable to Android, IOS, H5 platforms.

  Complex Association Detection

  Using complex user relationship graph based on user's unique identity, mining group fraud cases through multiple user profile dimensions.

• Variables

  Use big data to develop personal variables,text variables and relationship graph variables to provide 'bullets' for modeling and decision-making ”

  Text VariablesStatistics VariablesRelationship Graph Variables

  

• Text Variables

  Including communication, POI, device, social networking, etc., a total of 700+ variables

  Statistics Variables

  Including multiple platforms, credit amount, loan performance, collection, etc., a total of 1000+ variables

  Relationship Graph Variables

  Covering repayment details, overdue details and other post-loan performance information variables

• Credit Score

  Tailor-made, providing professional scoring for pre-loan audit, loan monitoring, and post-loan management

  General Credit ScoreCustomized Credit Score

  

• General Credit Score

  The general credit score made by highly versatile variables can be applied to classify customer group division and credit differentiation.

  Variable Extraction: Personal information, app collected information

  Application Scenario:Pre-loan evaluation, credit differentiation

  Connection Method: API/SDK

  Customized Credit Score

  Professional service, excellent effect