New ID_Check v2.6.11 — a new ID recognition engine improves OCR for Korean documents, PII masking is now set from the dashboard, and submissions can be searched by custom fields (cf1–cf3). See what's new →
New ID_Check v2.6.11 — a new ID recognition engine improves OCR for Korean documents, PII masking is now set from the dashboard, and submissions can be searched by custom fields (cf1–cf3). See what's new →
Learn about Verification data related settings including automatic English translation of submission names, partial data deletion, ID document PII masking, duplicate user detection, and submission rate limiting.
Verification data settings manage the quality and storage methods of Verification data collected in ID check projects. You can establish data management policies that meet business requirements through various options such as data conversion, data protection, duplicate management, etc.
Text from submitted IDs is changed to English for display and storage.
Automatic English Translation of Submission Names Settings
PrecautionsOCR result values are also changed to English, which may affect options such as government verification. (e.g., Korean name but attempting verification with English name)
In the above case, please request the sales team to create a new project, then reconfigure options for Korean targets before proceeding.
Translation may proceed with paraphrased English during the translation process.
Usage ScenariosWhen providing global services, IDs in various languages can be unified to English to facilitate data management and search.
When a submitted Submission is deleted, personal information is deleted and only de-identified data is maintained.
Partial Data Deletion Settings
PrecautionsPersonally identifiable information from capture devices is completely deleted, and only de-identified data such as date of birth/gender/age group/nationality in YYYYMM format is maintained for statistical purposes.
Partial Data Deletion UsageUsed when you want to delete Submissions for privacy protection law compliance but maintain de-identified data for statistical and analysis purposes. Deleted data cannot be recovered, so set carefully.
You can freely combine DI (Duplicate Information) for additional settings. If not collected after setting, DI is not generated.
Custom DI Settings
Default DIDefault DI is automatically generated based on name/date of birth/gender/nationality/portrait (face on ID). Custom DI allows more detailed duplicate detection by combining fields in addition to default DI.
DI Generation ConditionsDI value is generated only when name, date of birth, gender, nationality, and portrait, etc. are all provided. If a submitter’s identity has been verified through ARGOS Identity service, the existing DI value is maintained even when authenticated in a different project.
Custom DI UsageUsed when you want to set duplicate detection criteria suitable for project characteristics. For example, adding email addresses or phone numbers enables more accurate duplicate detection.
New in August 2026 — This masking option was previously configurable only from the internal ARGOS console. You can now control it directly from the dashboard.
Set, per number type, whether the numbers printed on Korean ID documents are collected and whether they are hidden on the ID document image. Masking results are displayed on the ID card image based on the selected options.Applicable to: Passport, National Id, Driver’s License, Resident Permit
Each number type applies to a different set of documents and offers a different set of options.
Number type
Applicable documents
Options
Resident Registration Number
Passport, National Id, Driver’s License, Resident Permit
Collect full number / Do not collect / Do not collect + mask
Document Number
Passport, Driver’s License
Collect full number / Do not collect / Do not collect + mask
Serial Number
Driver’s License
Collect full number / Do not collect
Serial Number has no masking option. For the serial number printed on a driver’s license you can only choose whether to collect it; it cannot be hidden on the ID document image.
Do not collect and Do not collect + mask both skip storing the number. The difference is whether the number remains visible on the ID document image.
Option
Data storage
ID document image
Collect full number
Extracts and stores the full number
Stays visible
Do not collect
Not stored
Stays visible
Do not collect + mask
Not stored
Hidden
The masked area differs per number type:
Resident Registration Number: hides the last 7 digits. (The first 6 digits, the date of birth portion, stay visible.)
Document Number: hides the whole passport number / driver’s license number area.
Masking cannot be applied while the number is being collected.Masking only works on top of Do not collect. You cannot store the number and hide it on the image at the same time.
Usage scenarioIf your service has no legal basis for storing resident registration numbers, choose Do not collect + mask to block both storage and image exposure at once.Note that some industries are legally required to collect the full number. Financial institutions, for example, must collect the full resident registration number under Korean credit information and tax law. Check the collection obligations for your industry in the fintech industry guide before changing this setting.
Controlling which PII fields are visible to each role (Owner, Leader, Member, Guest) on the dashboard screen is a separate feature — see System Operation. The masking on this page applies to the stored data and the ID document image itself.
Select the pipeline to use for duplicate checks. Both default method and custom DI pipelines can be selected, and the duplicate value from the first detected pipeline during detection is used.
Select the pipeline to perform duplicate checks. Both pipelines can be selected, and can be checked/unchecked with checkboxes.
Pipeline
Description
Default Method
Pipeline that detects duplicates based on default fields.
Custom DI
Pipeline that detects duplicates based on custom DI.
Pipeline Operation MethodWhen both default method and custom DI pipelines are selected, both pipelines run simultaneously. The duplicate value from the pipeline where duplicate is first found during detection is used.
The default method pipeline proceeds as a type of filter function when detecting duplicate users using DI, and checks for duplicates in the following order when searching the database:DB Search Order:
Exact Matching (Exact match)
Fuzzy Matching (Similar match)
Compare Face (Face comparison)
Fields Used in Each Filter Stage:
Filter Stage
Fields Used
Description
Exact Matching
Date of birth (birthDate), Gender, Nationality
Searches for users with exactly matching information.
Fuzzy Matching
Name
Searches for users with similar names. Allows typos or slight differences.
Compare Face
Portrait
Confirms if same person by comparing face images.
Duplicate Judgment Process:When passing each filter stage sequentially, it proceeds to the next stage. Users who pass all filters are judged as duplicate users.
User Submission ↓Exact Matching (birthDate, gender, nationality match?) ↓ PassFuzzy Matching (name similar?) ↓ PassCompare Face (face match?) ↓ PassJudged as duplicate user
Filter Pass ConditionsWhen a user matching conditions is found at each filter stage, it proceeds to the next stage. Only when all stages are passed is it judged as a duplicate user, so cases where only some information matches are not detected as duplicates.
Duplicate Detection AccuracySince checks are performed in the order of Exact Matching → Fuzzy Matching → Compare Face, duplicates are only judged when birthDate/gender/nationality exactly match, name is similar, and face also matches. This enables accurate duplicate detection while minimizing false positives.
Select the processing method for submissions detected as duplicates. (Radio button)
Processing Method
Description
Approved submission + Duplicate information display
Approves submissions detected as duplicates but displays duplicate information.
Reject submission if duplicate
Rejects submissions when detected as duplicates.
Duplicate Check Pipeline UsageWhen operating a one-person-one-account policy, you can activate the duplicate check pipeline to prevent creating multiple accounts with the same identity information. Selecting both default method and custom DI pipelines enables more accurate duplicate detection.
Sets the maximum number of verification attempts a user can make within the same period. Operates in Window Sliding method to effectively block excessive submission attempts by malicious users.
Submission rate limiting operates in Window Sliding method. Based on when the last submission came in, it goes back by the set time window (Window) and checks the number of submissions within that period.Operation Principle:
User attempts submission.
System goes back by the set time window (e.g., 1 hour) from the last submission point.
Checks the number of submissions within that time window.
If allowed count is exceeded, blocks authentication for the remaining time of the time window.
Example:
Setting: Maximum 5 submissions allowed within 1 hourTime axis: [---1 hour window---] [Current point]Submissions: [3 submissions] [2 submissions] ← Current attempt→ Total 5 submissions (within allowed range)→ Submission allowedTime axis: [---1 hour window---] [Current point]Submissions: [3 submissions] [3 submissions] ← Current attempt→ Total 6 submissions (exceeds allowed range)→ Blocked for remaining time of window
You can select criteria for detecting submission rate limiting. The following items can be combined:
Criteria
Description
Email
Limits based on number of submissions with the same email address.
User ID
Limits based on number of submissions with the same user ID.
IPv4 Address
Limits based on number of submissions from the same IPv4 address.
Restriction Scope CombinationMultiple criteria can be selected simultaneously. For example, if both email and IPv4 address are selected, blocking occurs if either criterion exceeds the allowed count.
You can effectively block abusers through the force block function when limits are exceeded.Block Period Settings:You can set an additional block period for users who exceed the limit count. During this period, the user cannot attempt authentication.Usage Scenarios:
Abuser Blocking: Block users who continuously attempt submissions for malicious purposes
Prevent Bad Attempts: Block repeated submission attempts for forgery or fraud purposes
System Protection: Prevent system load from excessive submissions
Effective Blocking Strategy
Set short time window (e.g., 1 hour) and low allowed count (e.g., 3) for quick blocking
Set force block period sufficiently (e.g., 24 hours) to prevent retries
Select email, user ID, and IPv4 address all together to block various bypass attempts
Using this function together with Proxy/VPN Detection function can more effectively prevent KYC forgery/alteration submissions quickly.
Checks for duplicates based on the following items. (Checkboxes)
Email
IP address
Local storage
Identity information: name, date of birth, gender, nationality
Resident registration number
Duplicate Approval Prevention Period UsageIf operating a one-person-one ‘approved’ account policy, be sure to set this function. If there is an approved submission with the same information within the set period, new submissions are rejected.
Duplicate Check Field PrecautionsWhen Identity info and Identity number are set, users submitting identical information are rejected.
Checks for duplicates based on the following items. (Checkboxes)
Email
IP address
Local storage
Duplicate Rejection Prevention Period PrecautionsExcessively strict settings may restrict legitimate user access, so settings must be made considering the balance between business goals and user experience. For example, it is good to set an appropriate period to allow retries when users accidentally enter incorrect information.
Duplicate Rejection Prevention Period UsageUsed to prevent malicious users from continuously resubmitting with rejected information. Setting the period to 0 days disables this function.