KYC parameters
In Bynn’s system, you can configure KYC (Know Your Customer) levels to match your business needs. Choose from default presets or fine-tune settings with customizable parameters to balance security, compliance, and user experience. Adjust key factors such as FRR (False Rejection Rate) and FAR (False Acceptance Rate) to optimize throughput while minimizing fraud risk. Whether you prioritize maximum security or seamless onboarding, Bynn gives you full control to fine-tune identity verification based on your industry, region, and risk tolerance.
KYC Level Settings
- Navigate to Settings > Product Settings (Identity Verification).
- Here, you will find KYC Level Settings, where you can create and edit KYC levels to tailor your customer verification process to your specific needs.
- You can either send all applicants to a single KYC level or use a risk-based approach, assigning levels based on factors such as country, general profile, and risk assessment.
Need help?
Our support team can assist you in setting up KYC levels for your business.
Default KYC Presets
By default, Bynn provides four preset KYC levels to help you get started:
Name | Description | Security | FRR (FAR) |
|---|---|---|---|
Boost Onboarding | Streamlined identity verification to onboard more users with minimal friction. Focus on growth and user experience while meeting compliance requirements. Ideal for businesses that prioritize customer conversion, reducing drop-off rates, and faster onboarding without compromising basic security checks. | Low | <0.1% (<5%) |
Enhanched Growth Compliance | Built to protect your business and users with additional fraud prevention tools while maintaining a seamless onboarding experience. Minimize risks without compromising growth. Recommended for businesses balancing moderate regulatory obligations with a focus on efficient user acquisition. | Balanced Medium | c:a 0.56% (<4%) |
Smart Secure KYC | Balance user conversion and security with biometric checks and enhanced fraud detection. Convert users faster while ensuring secure and compliant identity verification. Suitable for businesses scaling rapidly but needing to protect against basic fraud risks without slowing down onboarding. | Balanced High | c:a 0.7% (<2%) |
Fraud Shield | Maximum fraud protection and compliance for businesses operating in high-risk or highly regulated sectors. Advanced tools ensure your enterprise can onboard users securely and mitigate fraud at scale. Perfect for businesses that need to stay ahead of fraudsters, meet complex regulatory requirements, and secure large-scale operations. | High (risk of false rejections - but very secure) | < 2% (<0.5%) |
What is FRR (False Rejection Rate) & FAR (False Acceptance Rate)?
- False Rejection Rate (FRR): The percentage of legitimate applicants who are incorrectly rejected by the AI identity verification system. A high FRR can lead to poor user experience, as valid users may struggle to verify their identity.
- False Acceptance Rate (FAR): The percentage of unauthorized applicants who are mistakenly accepted as legitimate. A high FAR increases security risks by allowing fraudulent individuals to pass verification.
Balancing FRR and FAR is crucial in AI verification systems to ensure both high security and a seamless user experience.
Important
While we provide a baseline configuration, adjusting even one of hundreds of available parameters will impact both FRR and FAR. There is no universal “one-size-fits-all” setting—optimal accuracy requires ongoing tuning based on your specific risk tolerance, industry, and user base.
We recommend starting with our default presets, which serve as an excellent foundation for general e-commerce businesses. However, different industries and geographic regions may require adjustments based on fraud patterns and regulatory requirements. To achieve maximum throughput and minimal risk, we highly encourage gradual adjustments and continuous optimization as you scale.
Maximum Passthrough – Want to Onboard Every Applicant?
No problem – you’re in control. Configure the system to send "rejected" applicants for manual review or automatically accept them with a different risk category. Adjust the settings to fit your needs while maintaining security and compliance.
Parameters
| Parameter | Description |
|---|---|
| Data Processing Consent Link | Specify a custom URL for the data processing consent page. If left blank, the system will use the default link provided by the platform. |
| Data Processing Consent Text | Provide custom text for the data processing consent agreement. If not specified, the default consent text will be used. |
| WebSDK Return URL | Define the URL where applicants are redirected upon completing the verification process via the WebSDK. If left empty, a default 'Thank You' page will be displayed. You can also dynamically pass the return URL in the WebSDK for flexible routing. |
| Mobile Phone Verification Enforcement | Enforce that the verification process is completed on a mobile device. This enhances security by leveraging mobile-specific sensors, though it may exclude users without smartphones. |
| United States Residency Restrictions | Automatically disqualify applicants who indicate residency in the United States. This bypasses the verification process for USA residents. |
| Automatic Translation | Enable automatic translation of the KYC application into the applicant's preferred language for enhanced accessibility. |
| Data Retention Override | Enable a custom data retention period specifically for this level, overriding the default retention policy set at the account level. |
| Data Retention Time | Specify the custom duration for retaining data once the override is enabled. This setting determines how long data will be stored before deletion. |
| Name Source | Choose the source for the applicant's name: either manually provided by the applicant/API or automatically extracted from the applicant’s ID documents. |
| AI Decision Engine | Activate the AI-powered decision engine that automates the approval or rejection of applications, enhancing efficiency, accuracy, and consistency. |
| Decision Engine Type | Select the specific AI decision engine model to use for processing applications. This determines the logic and parameters applied during decision-making. |
| Decision Engine Uncertain Type | Define how the system should handle cases when the AI decision engine is uncertain about the outcome, including fallback procedures or additional review steps. |
| Custom Session Expiration | Specify a custom expiration time for verification sessions. By default, sessions expire after 24 hours if not completed. Adjust this period as needed. |
| Session Expiry Time Hours | Define the duration (in hours, between 1 and 8760) for which a verification session remains valid before it expires. |
| Capture ID Documents | Enable the collection of ID documents from applicants and trigger the verification process to authenticate the submitted documents. |
| Age Restrictions | Automatically reject applicants who do not meet the legal age requirement (typically 18 or 21 years old) based on their country or state of residency. |
| Minimum Residual Validity | Set the minimum remaining validity period required for ID documents to ensure they are current and acceptable for verification purposes. |
| Minimum Residual Validity Months | Define the minimum number of months that an ID document must remain valid to be considered acceptable for verification. |
| Enforce Live Capture | Force applicants to capture ID documents in real time using their device's camera. This minimizes the risk of using pre-edited or fraudulent images. |
| Live Capture Method | Select the mode for live document capture. Options may include direct camera capture or guided photo capture to ensure document authenticity. |
| Live Capture Fallback Method | Configure an alternative method to be used if live capture fails, ensuring that document submission can still be completed. |
| Document Types | Select the acceptable types of ID documents (e.g., passport, driver’s license, national ID) for verification. This limits submissions to supported document types. |
| Camera Capture Quality | Choose the quality level for camera captures. Higher quality improves fraud detection and forensic analysis but may require increased bandwidth and storage. |
| Liveness Check | Enable liveness detection (anti-spoofing) to verify that the applicant is physically present. This feature detects and blocks AI-generated images, deepfakes, or other fraudulent attempts. |
| Liveness Check Type | Select the liveness detection model to employ during the verification process. This defines the specific anti-spoofing method applied. |
| Record Audio and Video | Enable recording of audio and video during the verification session. This provides a comprehensive record for forensic analysis and helps detect fraudulent document submissions. |
| Capture Biometrics | Configure settings for capturing biometric data (e.g., facial recognition, fingerprints). This ensures compliance with regulations while improving security and fraud detection. |
| Capture Biometrics Type | Select the method for capturing and processing biometric data. Options may vary based on the security requirements and available technology. |
| Fraud Forensic Analysis | Activate AI-driven fraud forensic analysis to scrutinize documents for signs of forgery, manipulation, or tampering, enhancing overall verification security. |
| Synthetic Identity Protection | Automatically reject applications when biometric data matches but the provided personal information does not correspond with that on the submitted document, preventing synthetic identity fraud. |
| Automatic Image Quality Assessment | Automatically assess the quality of submitted images and flag or reject those that do not meet predefined standards, ensuring clarity for accurate verification. |
| Image Quality Handle | Define the process for managing low-quality images. Options may include prompting the applicant to resubmit or applying automated enhancements before processing. |
| AI-Generated Content Detection | Enable detection of AI-generated content (e.g., deepfakes) in images and videos. This advanced (beta) feature automatically rejects media that appears artificially generated. |
| Document Type Identification | Automatically verify the document type and country of origin using an extensive template database. Documents that cannot be identified are rejected. |
| Visual Zone Verification (VIZ) | Analyze the critical visual elements of an ID document. If the Visual Inspection Zone (VIZ) cannot be accurately processed, the document will be rejected. |
| Machine Readable Zone Verification (MRZ) | Validate the Machine Readable Zone (MRZ) of the ID document. Documents with unreadable or unprocessable MRZ data are automatically rejected. |
| Barcode Reading | Enable barcode reading to extract data from 1D or 2D barcodes. Documents with unreadable or inconsistent barcode data will be rejected. |
| NFC Verification | Utilize NFC verification to read embedded data in e-Passports, e-IDs, and e-DLs. If the NFC data cannot be read or verified, the document may be flagged or rejected. |
| NFC Handle | Define procedures for handling NFC verification failures. Options include prompting for a rescan, falling back to another method, or rejecting the application. |
| Lexical Analysis | Automatically process and standardize text from documents. Documents that fail to be analyzed, transliterated, or converted into a standardized format will be rejected. |
| Date Validation | Perform thorough checks on document dates, including expiry, issue, and format validation. Documents with inconsistent or invalid date formats are rejected. |
| Cross Validation | Conduct cross validation across multiple data sources (MRZ, VIZ, barcode, RFID) to ensure consistency. Documents with significant mismatches are rejected. |
| Data Presence Check | Automatically verify that all mandatory data fields are present on the document. Documents missing required data are rejected. |
| Deprecated Blanks Detection | Enable detection of outdated or deprecated document templates. Documents identified as no longer valid for use are automatically rejected. |
| Hologram Check | Activate hologram verification to ensure that the document includes a valid hologram. This advanced (beta) feature flags or rejects documents without proper holograms. |
| Hologram Handle | Define the action to take when hologram verification fails, such as prompting for resubmission, flagging for review, or automatic rejection. |
| Copy Detection | Enable detection of duplicate or non-original documents. Documents identified as copies (either soft or hard) are rejected to ensure authenticity. |
| Screenshot Check | Detect and reject documents submitted as screenshots or directly captured from digital devices, ensuring only original, physical document scans are accepted. |
| Textual Data Validation | Validate the formatting of textual data on documents (including font, spacing, and color). Documents failing these standards are rejected. |
| Barcode Format Check | Examine the format, type, and content of barcodes on documents. If the barcode is missing or does not meet required standards, the document is rejected. |
| Security Feature Check | Verify that all required security features (such as microprinting or watermarks) are present and meet specified criteria. Documents lacking these features are rejected. |
| Document Number Format | Ensure the document number is correctly formatted and matches expected patterns. Documents with an incorrect document number are rejected. |
| Personal Number Check | Validate the format and check digits of personal identification numbers on documents. Documents that do not pass validation are rejected. |
| IPI Presence Check | Perform an advanced check for Invisible Personal Information (IPI) within the document image. Documents failing this check are rejected. |
| LASINK™ Photo Check | Ensure the document's portrait is printed using LASINK™ technology. This advanced check rejects documents that do not incorporate the required secure printing method. |
| Biometric Portrait Comparison | Compare the portrait on the document with multiple biometric sources (e.g., main image, ghost image, NFC data, liveness selfie). Mismatches result in rejection. |
| Document Liveness | Enable dynamic liveness detection to ensure the document exhibits valid, live security features. Failure of this check results in rejection. |
| Fraud Intelligence | Utilize advanced AI and network data to assess fraud risk in real time, thereby enhancing the security and reliability of the verification process. |
| Network Document Fraud | Automatically reject documents that are flagged by the fraud intelligence network based on known fraudulent patterns. |
| Biometrics Mismatch | Detect and reject biometric data that does not match previously verified identities, preventing the reuse of biometric information across different individuals. |
| Risky Behaviour | Flag or reject applications when indicators of risky or fraudulent behavior are detected based on network activity or historical data. |
| Device Activities | Monitor device activity during verification. Devices with a history of suspicious or risky behavior may be flagged or rejected. |
| Device Activities Handle | Define the response for suspicious device activity, which may include manual review, additional verification steps, or outright rejection. |
| Phone Online Presence | Evaluate the online presence of the applicant’s phone number. Numbers lacking associated messaging apps or web service links may trigger additional scrutiny. |
| Phone Online Presence Handle | Set procedures for addressing phone numbers with limited online presence, which might include extra verification or manual review. |
| Phone PII Mismatch | Compare phone-linked data with the applicant’s provided identity information. Discrepancies may trigger a rejection or flag the application for further review. |
| Phone PII Mismatch Handle | Define the process for managing discrepancies between phone-associated personal information and the submitted identity data. |
| Phone Biometric Analysis | Perform biometric analysis on phone-linked images (such as social media profile pictures) and compare them with the ID document. Mismatches can lead to rejection or flagging. |
| Phone Biometric Mismatch Handle | Establish guidelines for handling cases where biometric data from phone sources does not match the ID documents, which may include additional checks or rejection. |
| Disposable Phone Detection | Detect the use of disposable or virtual phone numbers. Applications using such numbers may be flagged for further review or automatically rejected. |
| Disposable Phone Handle | Define the actions to take when a disposable phone number is detected, such as additional verification or outright rejection. |
| SIM Swap Detection | Enable detection of SIM swap attacks by identifying phone numbers with suspicious porting histories. Such cases can be flagged or rejected. |
| SIM Swap Handle | Specify the procedure for handling suspected SIM swap incidents, including additional verification steps or rejection. |
| Email Biometric Analysis | Perform biometric analysis on email-associated profile pictures and compare them with the ID document. Inconsistencies may trigger flagging or rejection. |
| Email Biometric Mismatch Handle | Set guidelines for managing cases where email biometric data does not match the provided identity information. |
| Disposable Email Detection | Detect disposable or temporary email addresses. Applications using such emails may be flagged for extra review or rejected outright. |
| Disposable Email Handle | Define the process for handling disposable email addresses, including additional verification measures or rejection. |
| IP Privacy Detection | Identify cases where the applicant’s IP address is masked via VPNs, proxies, or Tor networks. Such instances may trigger rejection or additional checks. |
| IP Privacy Handle | Set procedures for managing masked IP addresses, which may include manual review or further security checks. |
| IP Geolocation Intelligence | Compare the geolocation of the applicant’s IP address with the claimed country. Discrepancies can result in the verification being flagged or rejected. |
| IP Geolocation Handle | Define the response when IP geolocation does not match the applicant’s claimed country, including additional verification or rejection. |
| Behavioral Analysis | Monitor user interactions such as mouse movements, keystroke dynamics, and browsing patterns. Anomalies in behavior may trigger further verification or rejection. |
| Behavioral Analysis Handle | Establish procedures for addressing suspicious behavioral patterns detected during the verification process, which may include extra security measures or rejection. |
| AML Screening | Enable AML screening by cross-checking applicant data against global sanctions lists, politically exposed persons (PEP) databases, and adverse media sources. |
| Ongoing Monitoring Frequency | Set how frequently the system should perform AML re-screening on the applicant to capture any new risk indicators. |
| Matching Sensitivity | Adjust the strictness of the identity matching process. A higher sensitivity enforces stricter matching criteria, reducing false positives at the risk of false negatives. |
| Influential Role Match | Define how to handle matches with individuals in influential roles, such as Politically Exposed Persons (PEPs) or their close associates, which may require additional review. |
| Sanctioned Match | Specify the response when an applicant is matched with an entity on global sanctions lists, which may include automatic rejection or manual review. |
| Crime Match | Determine the process for handling cases where an applicant is linked to criminal activities as identified by matching against criminal databases. |
| Wanted Match | Define the procedure for managing matches with individuals on international wanted lists. Such matches may require immediate rejection or further investigation. |
| Military Officers Match | Set guidelines for handling matches with high-ranking military officers, considering the sensitivity and special processing these cases may require. |
| Debarred Individual Match | Specify how to handle cases where an applicant matches individuals barred from specific professions or activities, ensuring regulatory compliance. |
| Adverse Media Screening | Activate adverse media screening to search global media sources for negative news associated with an applicant. This advanced check helps identify potential risks not captured in standard databases. |
| Adverse Media Handle | Define the action to take when adverse media screening returns a match, such as manual review, additional verification, or rejection. |
- These presets are fully adjustable—you can modify requirements such as ID verification, proof of address, and biometric checks to ensure compliance and security.
- You can also create new KYC levels to fit your unique business needs.
- Each level has a unique identifier displayed next to it. Use this Identifier in your SDK or API requests to direct applicants through the appropriate KYC workflow.
Need help?
For further assistance, contact Bynn Support to optimize your KYC workflow! 🚀
Article
Ever had a legitimate customer blocked by your KYC system even though they were who they claimed? That’s an example of a false rejection. Or worse, imagine a fraudster slipping through as a verified user – a false acceptance.... read more
Updated about 1 month ago