A Complete Guide to Employment Verification

A Complete Guide to Employment Verification [2024]

Introduction

Building a strong and reliable workforce is a paramount objective for any organization, yet it is often fraught with challenges. Statistics in an Economic Times article on data published by AuthBridge reported that around 20% of the resumes received by corporate companies in India have discrepancies or false information. This alarming trend of misrepresentation on resumes encompasses various aspects, including work experience, educational qualifications, skill sets, and job responsibilities.

Doing detailed background checks, including employment verification, is crucial to avoid these risks and hire better employees. The Data Security Council of India (DSCI), under the Ministry of Electronics and Information Technology, explains that employment verification is a key part of this process. It involves checking if a candidate’s work experience and job details are true. This helps spot any lies, unexplained gaps in their job history, or fake job titles. Usually, this means contacting their past employers to check the role, title, duration of employment, and reasons for leaving. By verifying a candidate’s information, employers can make better hiring decisions and build a strong team.

What is Employment Verification?

Employment verification is a crucial component of the screening process that enables employers to validate the accuracy and authenticity of a candidate’s claimed work history. This rigorous process is designed to ensure that the individual possesses the requisite experience and qualifications to perform the intended job effectively.

At its core, employment verification involves confirming a candidate’s past employment details, such as job titles, responsibilities, employment duration, and reasons for leaving, directly with their former employers. This step helps uncover any potential discrepancies, falsified claims, or gaps in employment history that may have been omitted from the candidate’s resume or job application.

However, employment verification is not limited to merely verifying work experience; it often encompasses a comprehensive range of background checks. These additional checks may include verifying educational credentials, professional licenses or certifications, conducting criminal record searches, and validating the candidate’s identity through various means.

Key Insights from 25,00,000+ Employment Checks Conducted by AuthBridge

Discrepancy rate for employment verification has grown by 18% between FY 21-23. 

The rise in employment verification discrepancy is majorly from an increase in fake/forged experience certificates and wrong employment information. The inclusion of new verification measures like moonlighting, impersonation, and social media checks has also opened newer dimensions for the comprehensive screening of candidates contributing to this increase.

The Importance of Employment History Verification

Building Trust: Employment verification helps make sure that new hires are honest, especially when they’ll be handling sensitive company information. This helps build trust within the team.

Reducing Employee Turnover: When new hires fit well with company values, they’re less likely to leave due to bad behavior, which means lower employee turnover.

Checking Employment History: Verifying work history makes sure candidates aren’t lying about their experience and skills, ensuring they can do the job.

Verifying Job Titles: This makes sure that job titles match what the candidates did, preventing them from overstating their abilities.

Understanding Past Jobs: Knowing what a candidate did in their previous jobs helps determine if they’re a good fit for the new role.

Finding Out Why They Left: Understanding why candidates left their past jobs can help see if they’ll be a good fit and catch any potential issues early.

How to Verify Employment History

  1. Do It Yourself: Handling employment verification internally involves your HR team directly reaching out to the candidate’s previous employers. 
  • Contacting Past Employers: The HR team contacts each listed employer to verify job titles, dates of employment, and reasons for leaving.
  • Pros and Cons: This method is cost-effective but time-consuming and labor-intensive, requiring multiple calls and follow-ups.
  1. Use WorkAttest: WorkAttest, developed by AuthBridge, automates the employment verification process through a secure online platform.
  • Automation and Security: WorkAttest streamlines verifications by using a centralized, secure data repository. Employers upload ex-employee data, which verifiers can access instantly.
  • Benefits: This tool improves operational efficiency, reduces verification time, and minimizes fraud risk. It also offers comprehensive reporting and data analytics for better attrition management and hiring strategies.
  1. Partner with a Background Check Provider: Collaborating with a professional background check provider like AuthBridge can make the employment verification process more efficient.
  • Comprehensive Services: Providers verify employment history, education, criminal records, and more. AuthBridge uses advanced technology and extensive databases for accurate and fast verifications.
  • Compliance and Efficiency: Best providers ensure compliance and ensure quick turnaround times and legal adherence. For example, AuthBridge emphasizes legal compliance and efficiency in its verification process.

Types of Employment Verification

Verification Method

Initiation

Information Retrieval

Verification and Report Generation

Employment Check via HR Process

AuthBridge sends an email to the HR department or reporting manager of the previous employer to initiate the verification process.

AuthBridge utilizes its database to locate the HR email of the candidate’s former employer.

The HR department or reporting manager provides essential details such as the candidate’s employment dates, job title, and salary information.

Employment Check via UAN

AuthBridge employs a secure and encrypted API to facilitate the verification process.

AuthBridge conducts a thorough comparison between the candidate’s provided information and the data retrieved from the EPFO database.

Multiple checks are performed, including name, company name matching, date of joining, and date of exit. A comprehensive report is shared with the client.

Employment Check via Form 16

The candidate provides their Form 16, which is a certificate issued by their employer that shows their salary and tax deductions for a particular year.

AuthBridge verifies that form 16 by cross-referencing it with the ITR website API, ensuring accurate and reliable information.

Validate the name of the employer and thoroughly examine the TDS deductions for a specific assessment year. A comprehensive report is shared with the client.

Employment Check via Form 26AS

Obtain the necessary credentials, including the PAN card number and other relevant information, to access the user’s ITR and Form 26AS.

Utilize AuthBridge’s API to securely retrieve employment-related information from the user’s ITR and Form 26AS.

Analyze the retrieved data to authenticate the user’s employment details. Cross-reference reported income sources, employment status, and previous employment history.

Results that you can Expect from Employment Verification

Employment Check via HR Process:

  • What It Includes: Verification of the candidate’s employment dates, job title, and salary.
  • Additional Insights: Feedback on the candidate’s code of conduct, exit formalities, and reasons for leaving.

Employment Check via UAN:

  • Key Elements: Report includes UAN number, assessment year, employee name, organization name, tenure, and PAN number.
  • Verification Method: Cross-references information with the EPFO database.

Employment Check via Form 16:

  • Verification Process: Validates employer’s name and examines TDS deductions for a specific assessment year.
  • Report Details: Form 16 certificate number, company name, TAN and PAN of the employer, assessment year, and TDS amount deducted.

Employment Check via Form 26AS:

Report Content: Organization name during the assessment year, status of TDS booking, candidate’s name, number, email address, PAN number, and organization name.

How long does an Employment Verification Take?

Employment Verification via Worknumber is instant, whereas, in the case of managed checks, it can range from 2-3 days, depending on the type of check. 

How far back do Employment Verifications Go?

The number of years of employment history to be verified depends on the job’s nature:

  • Entry-Level Positions: Typically, verifying the previous three years of employment is adequate.
  • Senior Positions: Verification of a longer period is required to ensure extensive experience and reliability.

Role-Specific Responsibilities: The length of experience verification also depends on the responsibilities entailed in the role.

Questions to Consider Before Choosing a Background Check Provider Like AuthBridge

  1. What percentage of Employment Verifications are you unable to verify?
  2.   At AuthBridge, we pride ourselves on our comprehensive verification processes. However, there are instances where we encounter challenges in verifying employment information. The percentage of employment verifications we are unable to verify is the lowest in the industry. This is because we utilize a combination of advanced technology and an extensive network of industry connections to ensure the highest accuracy and completion rates.   
  3. What is included in your methodologies of Employment Verification?
  4.   Our employment verification methodology is multifaceted and designed to provide a comprehensive overview of a candidate’s employment history.    Key components include:  
    • Direct Employer Verification: We contact previous employers directly to verify the candidate’s tenure, job title, responsibilities, and reasons for leaving.
    • Database Checks: We leverage extensive proprietary databases and public records to cross-reference information.
    • Document Validation: We authenticate documents such as offer letters, pay slips, and experience certificates to ensure their legitimacy.
    • Advanced Technology: Our processes are powered by AI and machine learning algorithms to detect discrepancies and ensure data integrity.
    • Global Reach: Our international verification capabilities allow us to verify employment history across different countries, ensuring a global perspective.
     
  5. Do you provide continuous screening in case I want to check for Moonlighting?
  Yes, AuthBridge offers continuous screening services to monitor employees on an ongoing basis. This is particularly useful for detecting instances of moonlighting, where an employee might be engaged in secondary employment without the primary employer’s knowledge.

Get Started with AuthBridge

Here’s how you can supercharge your employee verification process with AuthBridge.

Why Choose AuthBridge?

  • Comprehensive Coverage: Our verification services cover all critical aspects, including employment history, education, criminal records, and more.
  • Advanced Technology: Leveraging AI and machine learning, we deliver accurate and efficient verifications.
  • Global Reach: Our international capabilities ensure seamless verifications across different regions.
  • Real-time Reporting: Stay informed with real-time updates and detailed reports.
  • Continuous Screening: Maintain workforce integrity with ongoing monitoring services.

Ready to get started? Contact us today to begin your journey towards a secure and reliable workforce with AuthBridge. Visit our Employee Background Verification & Screening page for more information.

Additional Information on International Processes

  • International Employment Verification in United States – e Verify

Employment verification is a crucial process for employers worldwide, ensuring that prospective employees are eligible to work. One prominent system used in the United States for this purpose is E-Verify. This web-based system, operated by the U.S. government, checks the employment eligibility of new hires by comparing information from Form I-9 against records from the Social Security Administration (SSA) and the Department of Homeland Security (DHS).

E-Verify enrollment is primarily voluntary, although federal contractors and subcontractors must participate. Employers use E-Verify to confirm that their employees are legally authorized to work in the U.S. The system cross-references the information provided by the employee on Form I-9 with records from the SSA and DHS.

Process

  1. Form I-9 Completion: The process begins with the employee completing Form I-9, which collects information about their identity and work eligibility.
  2. Document Review: The employer reviews the supporting documents provided by the employee to ensure they are genuine and related to the employee.
  3. Information Submission: Once the employer is satisfied with the documents, they complete section 2 of Form I-9 and submit the information to E-Verify.
  4. Verification: E-Verify checks the information against SSA and DHS records to confirm the employee’s eligibility to work in the U.S.

Result: The system provides immediate results indicating whether the employee is eligible to work, or if further action is needed.

Laws in International Employment Verification

United States

The Immigration Reform and Control Act (IRCA) of 1986 mandates that employers verify the identity and employment eligibility of all new hires. E-Verify extends this requirement for federal contractors and subcontractors.

European Union

Employment verification in the EU must comply with the General Data Protection Regulation (GDPR), ensuring the protection of personal data. Employers are required to verify work permits or visas while adhering to strict data protection rules.

United Kingdom

The Data Protection Act 2018, aligned with GDPR, governs how employers handle personal information during employment verification. UK employers must also verify the legal right to work, a requirement emphasized post-Brexit.

Canada

The Personal Information Protection and Electronic Documents Act (PIPEDA) regulates the collection, use, and disclosure of personal data during employment verification. Employers must ensure employees have the legal right to work through permits or visas.

Australia

Australia’s Privacy Act 1988 governs the handling of personal information during employment verification. Employers must verify employees’ work rights using the Visa Entitlement Verification Online (VEVO) system.

FAQ

This varies based on the position you’re hiring for. Typically, verifying the last 7-10 years of employment history is recommended to ensure a comprehensive check of a candidate’s professional background.

An employer can usually release Job title, Employment dates, Salary information (if authorized), Job responsibilities, Reason for leaving

Yes, HR departments can verify your work history as part of the employment verification process.

Employment verification confirms a candidate’s job history, titles, and employment dates with previous employers. Whereas, Reference verification gathers insights about a candidate’s work performance, skills, and character from former colleagues or supervisors.

A Proof of Employment Letter, also known as an Employment Verification Letter, is an official document provided by an employer that confirms an individual’s current or past employment status. This letter is often required for various purposes such as applying for a loan, renting an apartment, obtaining a visa, or as part of the onboarding process for a new job.

Face-match Tech: Working, Applications, & Benefits

Introduction

Face-match technology, also known as facial recognition technology, has become increasingly prevalent in our digital world. It uses biometrics to map facial features from a photograph or video and compares this information with a database to find a match. This technology is being adopted across various sectors due to its efficiency and security benefits.

How Face-match Works?

Face-match technology operates by analysing and comparing the unique facial features of an individual. The process involves several sophisticated steps that leverage advanced algorithms and data processing techniques to ensure accuracy and efficiency.

Facial Recognition Algorithms

Facial recognition algorithms form the core of face-match technology. These algorithms perform a series of steps to identify and verify individuals:

  1. Detection: The first step involves detecting a face in an image or video. This is achieved using techniques like Haar cascades or deep learning models such as Convolutional Neural Networks (CNNs). The system identifies facial landmarks like the eyes, nose, and mouth.
  2. Alignment: Once detected, the face is aligned to a standard orientation. This step ensures that the facial features are in the correct position for accurate analysis, compensating for variations in head pose, lighting, and facial expressions.
  3. Feature Extraction: In this phase, unique features of the face are extracted. These features could include the distance between the eyes, the shape of the cheekbones, and the contour of the lips. Modern systems use deep learning techniques to extract features, converting the face into a mathematical representation known as a faceprint.

Matching: The extracted faceprint is then compared against a database of known faces. Matching algorithms calculate the similarity between the input faceprint and those stored in the database, determining if there is a match.

Data Handling and Processing

Efficient data handling and processing are crucial for the performance of face-match technology. Here’s how data is managed:

  1. Data Collection: Facial data is collected from various sources, including photographs, video feeds, and live camera inputs. This data is often preprocessed to enhance quality and ensure consistency.
  2. Database Management: The facial data is stored in databases designed for quick retrieval and matching. These databases use indexing techniques to speed up the search process.
  3. Real-time Processing: For applications like security and surveillance, real-time processing is essential. Advanced systems can process and match faces in real time, providing immediate feedback and alerts.

Table: Key Steps in the Face-match Process

Step

Description

Techniques Used

Detection

Identifying a face in an image or video

Haar cascades, CNNs

Alignment

Standardising the orientation of the face

Geometric transformations, landmark alignment

Feature Extraction

Converting facial features into a mathematical representation

Deep learning models, feature vectors

Matching

Comparing the input faceprint with the database

Similarity algorithms, neural networks

Applications of Face-match Online

Face-match technology has found a myriad of applications across various sectors due to its capability to quickly and accurately identify individuals. These applications range from enhancing security measures to streamlining user authentication processes.

Security and Surveillance

One of the most prominent applications of face-match technology is in security and surveillance. Governments and private organisations deploy facial recognition systems in public spaces such as airports, stadiums, and malls to monitor and identify individuals in real time. This technology helps in:

  • Crime Prevention: By identifying known criminals and alerting security personnel in real time, facial recognition systems can prevent crimes before they occur.

Missing Persons: Authorities can use face-match technology to locate missing persons by comparing live camera feeds with databases of missing individuals.

User Authentication

face-match technology is increasingly being used for user authentication, particularly in online services and mobile applications. This method provides a convenient and secure way for users to access their accounts without needing passwords.

  • Banking: Financial institutions use facial recognition to verify the identity of users during online transactions, reducing the risk of fraud.
  • Mobile Devices: Smartphones and tablets incorporate face-match technology to unlock devices and authorise payments.

Supporting Data: According to Juniper Research, the number of mobile devices using facial recognition for authentication is expected to exceed 800 million by 2024, highlighting the growing reliance on this technology.

Social Media and Online Verification

Social media platforms and online services leverage face-match technology to enhance user experiences and ensure the authenticity of user identities.

  • Tagging Photos: Platforms like Facebook use facial recognition to suggest tags for people in photos, making it easier to organise and share images.
  • Online Verification: Companies use face-match technology to verify the identities of users during the sign-up process, ensuring that users are who they claim to be.

Example: Dating apps like Tinder and Bumble use facial recognition to verify profile pictures, ensuring that users’ photos are genuine and reducing the risk of catfishing.

Benefits of Using Face-match Online

Face-match technology offers a wide range of benefits, making it an invaluable tool across various industries. These advantages stem from the technology’s ability to provide accurate, efficient, and secure identification and authentication solutions.

Accuracy and Efficiency

face-match technology is renowned for its high levels of accuracy and efficiency, which are critical in applications where precise identification is necessary.

High Precision

Facial recognition systems achieve remarkable precision due to the advanced algorithms and deep learning models employed. These systems can accurately identify individuals even in challenging conditions, such as poor lighting or occluded faces.

  • Algorithmic Advancements: The use of Convolutional Neural Networks (CNNs) and other deep learning techniques has significantly improved the accuracy of facial recognition algorithms. These models can learn and recognise intricate facial features, making them highly reliable.
  • Case Study: In a study conducted by the National Institute of Standards and Technology (NIST), the best facial recognition algorithms demonstrated error rates of less than 0.1% in controlled environments, highlighting their high precision.

Rapid Processing

The speed at which facial recognition systems can process and match faces is another significant benefit. This rapid processing capability is essential for real-time applications where immediate responses are necessary.

  • Real-Time Recognition: Modern facial recognition systems can analyse and match faces in real time, providing instant feedback. This feature is particularly useful in security and surveillance applications, where quick identification is crucial.
  • Example: During large-scale events, such as sports games or concerts, facial recognition systems can quickly scan and identify attendees, ensuring safety and security without causing delays.

Enhanced Security and Safety

face-match technology significantly enhances security and safety measures, offering robust solutions for various applications.

Fraud Prevention

In the financial sector, face-match technology is employed to prevent fraud and verify user identities during transactions. This method reduces the risk of unauthorised access and fraudulent activities.

  • Banking Security: Financial institutions use facial recognition for identity verification during online banking transactions. By ensuring that the person conducting the transaction is the account holder, banks can minimise the risk of fraud.
  • Example: HSBC uses facial recognition technology in its mobile banking app to authenticate users, providing a secure and convenient way to access accounts.

Public Safety

In public spaces, face-match technology is used to enhance safety by identifying potential threats and ensuring the well-being of citizens.

  • Surveillance Systems: Cities and law enforcement agencies deploy facial recognition systems in public areas to monitor and identify individuals. These systems help in detecting and preventing criminal activities, ensuring public safety.
  • Example: The use of facial recognition technology at airports enhances security by identifying travellers on watchlists and verifying identities during boarding processes.

Table: Benefits of Using face-match Technology

Benefit

Description

High Precision

Advanced algorithms and deep learning models ensure accurate identification

Rapid Processing

Real-time face-matching provides immediate feedback

Fraud Prevention

Verifies user identities during financial transactions to reduce fraud risk

Public Safety

Monitors public spaces and identifies threats for enhanced security

Supporting Data

The growing reliance on face-match technology is reflected in market trends and projections. According to Grand View Research, the global facial recognition market is expected to reach USD 12.92 billion by 2028, driven by increasing demand for enhanced security and surveillance systems.

Real-Life Example: In India, the government has implemented facial recognition technology in several airports, such as Rajiv Gandhi International Airport in Hyderabad, to streamline passenger identification and enhance security measures. This implementation has resulted in faster boarding processes and improved overall safety for travellers.

Challenges and Limitations

Despite its numerous benefits, face-match technology also presents several challenges and limitations. These issues must be addressed to ensure the technology’s effectiveness and public acceptance.

Privacy Concerns

One of the most significant challenges associated with face-match technology is privacy. The collection, storage, and use of biometric data raise serious concerns about individual privacy and data security.

Data Collection and Consent

The process of collecting facial data often occurs without explicit consent from individuals, raising ethical and legal concerns.

  • Lack of Transparency: Many facial recognition systems operate without informing individuals that their data is being collected and analysed. This lack of transparency can lead to mistrust and opposition.
  • Example: In 2019, San Francisco became the first major U.S. city to ban the use of facial recognition technology by city agencies, citing privacy and civil liberties concerns.

Data Security

The storage and protection of biometric data are critical. Unauthorised access to this data can lead to identity theft and other malicious activities.

  • Risk of Breaches: Biometric data, once compromised, cannot be changed like a password. This makes data breaches involving facial recognition data particularly concerning.
  • Supporting Data: According to a report by the Brookings Institution, the risk of biometric data breaches increases as more organizations adopt facial recognition technology, highlighting the need for robust security measures.

Technical Issues

Technical limitations also pose challenges to the widespread adoption and effectiveness of face-match technology.

Accuracy in Uncontrolled Environments

The accuracy of facial recognition systems can be affected by various factors such as lighting conditions, facial expressions, and occlusions (e.g., glasses, masks).

  • Environmental Factors: Poor lighting or extreme angles can reduce the accuracy of face-match technology. Systems must be trained to handle diverse conditions to maintain reliability.
  • Example: During the COVID-19 pandemic, the widespread use of face masks presented a significant challenge for facial recognition systems, which struggled to identify masked individuals accurately.

Bias and Discrimination

Facial recognition algorithms can exhibit biases, leading to disparities in accuracy across different demographic groups.

  • Algorithmic Bias: Studies have shown that facial recognition systems often perform better on lighter-skinned individuals compared to those with darker skin tones. This bias can result in higher rates of false positives or false negatives for certain groups.
  • Supporting Data: A study by the National Institute of Standards and Technology (NIST) found that facial recognition algorithms have higher error rates for women and people of color compared to white men.

Legal and Ethical Considerations

The use of face-match technology raises several legal and ethical questions that need to be addressed to ensure responsible deployment.

Regulatory Compliance

Regulations surrounding the use of facial recognition technology vary widely across different regions and countries.

  • Compliance Requirements: Organisations using face-match technology must navigate a complex landscape of privacy laws and regulations to ensure compliance.
  • Example: The European Union’s General Data Protection Regulation (GDPR) imposes strict guidelines on the processing of biometric data, requiring explicit consent and robust data protection measures.

Ethical Use

Ethical considerations include ensuring that facial recognition technology is used fairly and justly, without infringing on individuals’ rights.

  • Fair Use: It is essential to implement guidelines that prevent the misuse of facial recognition technology, such as unwarranted surveillance or discrimination.

Supporting Data: The American Civil Liberties Union (ACLU) has highlighted several instances where facial recognition technology has been misused, advocating for stricter regulations and oversight.

Future of face-match Technology

The future of face-match technology looks promising, with ongoing advancements and potential new applications on the horizon.

Technological Advancements

Continued research and development are expected to enhance the capabilities and accuracy of facial recognition systems.

  • Improved Algorithms: Advances in artificial intelligence and machine learning will lead to more sophisticated algorithms capable of handling diverse conditions and improving accuracy.
  • Real-Life Example: Researchers at the Massachusetts Institute of Technology (MIT) are working on developing facial recognition systems that can better handle variations in lighting and facial expressions, aiming to reduce error rates further.

Emerging Applications

New applications for face-match technology are continually emerging, expanding its use beyond traditional sectors.

  • Healthcare: Facial recognition can be used in healthcare settings to monitor patients, verify identities, and even diagnose certain medical conditions based on facial features.
  • Retail: In the retail industry, facial recognition can enhance customer experiences by personalizing services and improving security measures.

Example: In China, some hospitals use facial recognition to streamline patient check-ins and ensure the correct administration of treatments, demonstrating the technology’s potential in healthcare.

AuthBridge's Face Verification

AuthBridge’s face verification service is a sophisticated solution designed to authenticate identities quickly and accurately. By leveraging advanced biometric technologies, it ensures the verification process is both reliable and efficient. Here’s a comprehensive look into the steps involved, the processes, and why one should trust AuthBridge for face verification.

Steps Involved in Face Verification

  1. Capture and Enrollment
    • Initial Capture: The first step involves capturing the individual’s face through a camera, either from a live feed or a pre-existing photograph.
    • Enrollment: The captured face is then enrolled into the system by extracting unique facial features and converting them into a digital format known as a faceprint.
  2. Face Matching
    • Real-Time Verification: During the verification process, the system captures a new image of the face and generates a faceprint.
    • Comparison: The newly generated faceprint is compared against the enrolled faceprints in the database to find a match.
    • Algorithmic Matching: Advanced algorithms calculate the similarity between the faceprints to verify the identity.
  3. Liveness Detection
    • Anti-Spoofing Measures: To ensure the face being verified is live and not a photograph or video, liveness detection techniques are employed. These can include blinking detection, texture analysis, and motion analysis.
    • 3D Face Modelling: Some systems use 3D modelling to distinguish between a live person and a static image.
  4. Result Generation
    • Instant Results: The system provides real-time verification results, indicating whether the face matched successfully or not.
    • Report Generation: Detailed reports are generated, documenting the verification process and outcomes.

Processes Involved in Face Verification

  1. Image Preprocessing
    • Enhancement: The captured images are enhanced to improve quality and clarity.
    • Normalisation: The images are normalised to standardise the facial features, ensuring consistent data for accurate comparison.
  2. Feature Extraction
    • Key Points Identification: Unique facial features such as the distance between eyes, nose shape, and jawline are identified.
    • Faceprint Creation: These features are used to create a digital representation or faceprint.
  3. Database Management
    • Storage: The faceprints are securely stored in a database.
    • Indexing: Efficient indexing techniques are employed to facilitate quick retrieval during the matching process.
  4. Algorithmic Analysis
    • Similarity Scoring: The system uses sophisticated algorithms to score the similarity between the captured faceprint and the stored faceprints.
    • Decision Making: Based on the similarity score, the system decides on the verification status.

Why Trust AuthBridge for Face Verification?

  1. Advanced Technology
    • AuthBridge utilises state-of-the-art biometric technology and AI-driven algorithms to ensure high accuracy and reliability in face verification.
  2. Security and Compliance
    • Data Security: AuthBridge adheres to stringent data security protocols, ensuring that biometric data is protected against unauthorised access and breaches.
    • Regulatory Compliance: The service complies with relevant regulations and standards, including GDPR, ensuring ethical and legal use of biometric data.
  3. Proven Track Record
    • With years of experience in identity verification and background screening, AuthBridge has built a strong reputation for delivering reliable and efficient solutions.
  4. Comprehensive Solutions
    • AuthBridge offers a wide range of verification services beyond face verification, including background checks, document verification, and digital KYC, providing a holistic approach to identity management.
  5. Superior Customer Support
    • AuthBridge provides robust customer support, assisting clients with implementation, troubleshooting, and any other needs, ensuring smooth operation and satisfaction.

Additional Features from AuthBridge's Face Verification Page

  1. Scalability
    • AuthBridge’s face verification system is designed to scale, accommodating the needs of businesses of all sizes, from small enterprises to large corporations.
  2. Ease of Integration
    • The face verification system can be easily integrated into existing workflows and systems, thanks to its API-first approach, which ensures seamless connectivity and functionality.
  3. Multi-Device Compatibility
    • The service is compatible with various devices and platforms, including smartphones, tablets, and desktops, ensuring flexibility and convenience for users.
  4. Customisable Solutions
    • AuthBridge offers customisable face verification solutions tailored to meet the specific needs and requirements of different industries and use cases.

Conclusion

face-match technology, with its numerous applications and benefits, is revolutionising various sectors by providing accurate, efficient, and secure identification solutions. However, it also presents challenges and limitations that must be addressed to ensure its ethical and effective use. As advancements continue and new applications emerge, the potential for face-match technology will expand, offering even more innovative solutions in the future.

FAQs about Face Match Technology

Face match technology, also known as facial recognition technology, uses biometrics to map facial features from a photograph or video and compares this information with a database to find a match. It is used for identification and authentication purposes across various industries.

Face match technology works by detecting a face in an image or video, aligning it to a standard orientation, extracting unique facial features to create a faceprint, and then matching this faceprint against a database of known faces.

Face match technology is used in security and surveillance, user authentication, social media, and online verification. It helps prevent crime, verify identities, and enhance user experiences.

Face match technology is used in security and surveillance, user authentication, social media, and online verification. It helps prevent crime, verify identities, and enhance user experiences.

Privacy concerns include the lack of transparency in data collection, the potential for data breaches, and ethical issues related to consent and misuse of biometric data.

Technical challenges include maintaining accuracy in uncontrolled environments, such as poor lighting or occlusions, and addressing algorithmic biases that may affect certain demographic groups.

Face match technology is subject to various regulations that differ by region and country. For example, the European Union’s General Data Protection Regulation (GDPR) imposes strict guidelines on the processing of biometric data.

The future of face match technology looks promising with ongoing advancements in artificial intelligence and machine learning. Emerging applications include healthcare and retail, expanding the technology’s use beyond traditional sectors.

When implemented with robust data protection measures and ethical guidelines, face match technology can be safe and effective. However, it is essential to address privacy concerns and technical limitations.

Facial recognition systems have faced challenges with the widespread use of masks. However, advancements in technology are improving the accuracy of face match systems in identifying masked individuals.

Moonlighting in India

Moonlighting in India: Meaning, Legal Implications, Impact, and Verification Methods

Introduction to Moonlighting:

Moonlighting refers to the practice of holding a secondary job or responsibilities, typically unknown to one’s primary employer, often performed during off-hours like nights or weekends. This term gained popularity as employees started to seek additional employment beyond their regular day jobs to increase their income.

Why is Moonlighting not a good thing for employers?

Moonlighting presents several challenges for employers, often making them wary of this practice for various reasons:

  1. Decreased Productivity: Employers are concerned that employees who work multiple jobs may not perform optimally in their primary roles. Fatigue from balancing more than one job can lead to reduced energy and focus, which can adversely affect productivity and the quality of work.
  1. Conflict of Interest: There’s a risk that moonlighting could lead to situations where an employee’s secondary job conflicts with the interests of their primary employer. This could be direct, such as working for a competitor, or indirect, where the employee may inadvertently share sensitive information or insights that could benefit their secondary employer.
  1. Divided Loyalties: Employers might worry that employees who moonlight may not be fully committed or loyal to their primary job. This divided attention can lead to prioritization issues, where employees may favor their secondary employment over their main job responsibilities.
  1. Impact on Team Dynamics: If an employee is regularly tired or less engaged due to their commitments elsewhere, it can affect not only their own performance but also the morale and productivity of the entire team. This can create additional strain on colleagues who may have to compensate for the decrease in productivity.
  1. Availability Issues: Moonlighting can lead to scheduling conflicts, especially if the secondary job requires similar working hours or if unexpected demands arise from the other role. This can make it difficult for employers to rely on the employee for overtime or to cover shifts, which is particularly problematic in roles that require a high degree of flexibility.
  1. Legal and Ethical Concerns: There can be legal implications if the moonlighting activity violates non-compete clauses or confidentiality agreements. Ethically, employers may question whether an employee can impartially handle responsibilities if they are engaged in similar work elsewhere.
  1. Resource Drain: When employees are overstretched, they might use the resources from their primary job to support activities for their secondary job, whether that’s time, materials, or intellectual property. This can lead to losses and ethical breaches for the primary employer.

Legality of Moonlighting in India:

Legal Position of Moonlighting in India As previously stated, there is no explicit law in India that addresses moonlighting. However, it might be subject to legal repercussions under many statutes, including the Employment Contract Act, the Shops and Establishments Act, and the Industrial Disputes Act.  The Industrial Employment (Standing Orders) Act, of 1946 permits dual employment. Whereas under the Factories Act, of 1948, dual employment is prohibited. Under the Factories Act of 1948, an employer cannot require or let an adult employee work in the factory on days when they have already worked in another workplace. The prohibition provided by the Occupational Safety, Health, and Working Conditions (OSH) Code is restricted to simultaneous employment in a mine or factory and is largely equivalent to the one outlined in the Factories Act.

Consequences of Going Against Company Clause of Moonlighting: The consequences of going against a company clause prohibiting moonlighting can vary depending on the specific terms of the contract and the laws applicable in the jurisdiction where the employer is based. However, some common consequences include:

Disciplinary action: The employer may take disciplinary action against the employee, which may include a warning, suspension, or termination of the contract.

Legal action: If the breach of contract happens, the employer may choose to take legal action against the employee.

Damages: If the employer can demonstrate that the employee’s moonlighting activities have caused harm to the company, they may be able to claim damages.

Reputation damage: Going against a company clause can damage the employee’s reputation and may have negative consequences for their future employment prospects.

It is important to note that the specific consequences of going against a company clause prohibiting moonlighting will depend on the laws and regulations applicable in the jurisdiction where the employer is based, and the terms of the employment contract. An employee should seek legal advice before engaging in the concept of moonlighting activities if their employment contract contains a clause prohibiting such activities.

Moonlighting Policy for Employees:

Developing a Moonlighting Policy for Employees in India:

The topic of moonlighting has recently come under the spotlight in India, especially among leading corporations. There remains a significant debate around the ethical and legal dimensions of moonlighting, leading to varied stances among companies.

Role of HR in Moonlighting Policies:

It is primarily up to each company’s Human Resources department to establish a clear policy regarding moonlighting. This results in diverse policies across the corporate spectrum. Some companies have already implemented specific guidelines, while others are in the process of defining their stance.

Common Trends in Moonlighting Policies:

Most businesses tend to restrict their employees from engaging in work with competing organizations. This is a widespread measure to prevent conflicts of interest. Moreover, companies that haven’t yet formalized a separate moonlighting policy often address the issue by incorporating a clause against dual employment directly into their employment contracts.

How to Find Out if an Employee Is Moonlighting?

Companies can know if an employee is moonlighting and working for its competitors using their Universal Account Number (UAN) of the Employees’ Provident Fund (EPF). Companies can access an employee’s UAN number to get to know if two PF contributions are being made by different companies. When two PF contributions are being made simultaneously to a UAN, it is a clear indication of moonlighting by the employees.

Wipro fired 300 employees for moonlighting by tracking the EPF accounts maintained under the UANs. However, it isn’t easy to find moonlighting by an employee when he/she takes up additional work as a consultant, freelancer or part-time since an employer does not make the PF contribution for such work.

However, companies may start deploying new-age technology to track devices given to employees solely for office work and get to know when an employee uses it to do another company’s work. They may also hire a third-party agency for background checks to find out about moonlighting by an employee.

Detecting Employee Moonlighting

Businesses can ascertain whether their employees are engaged in moonlighting, especially with competitors, by monitoring their Universal Account Number (UAN) associated with the Employees’ Provident Fund (EPF). By examining an employee’s UAN, companies can detect dual PF contributions from separate employers, which is a clear sign of moonlighting.

Instances of Monitoring:

For instance, Wipro terminated 300 employees who were found moonlighting by monitoring the EPF accounts linked to their UANs. Detecting moonlighting becomes challenging when employees engage in freelance, consultancy, or part-time roles that do not require PF contributions by the employer.

Preventive Measures by AuthBridge:

AuthBridge leverages AI technology to effectively address and manage dual employment dilemmas, crafting a strategic blend of tactics for our clients and their HR teams. Our platform offers seamless workflows and minimizes data loss, enhancing the speed and efficiency of employment verification processes.

Our Dual Employment Verification Approach:

Our method involves using the UAN to conduct non-invasive employment verification, ensuring accurate results quickly and efficiently. AuthBridge’s system is designed to be data-centric and precise. Upon obtaining an employee’s UAN, we commence verification to confirm there is no concurrent employment during the client’s tenure. If dual employment is detected, the situation is immediately flagged.

Details Verified in Our UAN Checks Include:

  • Employee’s Name
  • Father’s/Husband’s Name
  • Employing Organization
  • Date of Joining
  • Date of Exit

Technological Advantages with AuthBridge:

  • Streamlined integrations through simple dashboards and APIs
  • Real-time background checks that optimize time efficiency
  • Customization of workflows to suit specific client and industry needs
  • Cost-effective solutions driven by a robust database
  • Elimination of manual processes
  • Secure digital data handling compliant with industry standards
  • Detailed and swift reporting to facilitate quicker hiring decisions

AuthBridge’s CEO on Moonlighting:

“A person can have multiple employees crediting PF into the same PF account. Many companies don’t run dual-employment verification for their employees. They will conduct a basic background screening,” said Ajay Trehan, founder and CEO of AuthBridge.“The only logical explanation is she must have been running a mini BPO setup at her home with multiple terminals and enrolled people to work on a project basis. We only run a check on PF credentials for dual employment.“

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moonlighting in india: AuthBridge CEO, Ajay Trehan words on the current insights and industry trends related to dual employment

Recent Developments in Corporate Moonlighting Policies

Wipro’s Stance:

Wipro’s CEO, Rishad Premji, recently labeled moonlighting as unethical, equating it to cheating. This strict viewpoint led to the termination of 300 employees found working for competitors, highlighting the company’s zero-tolerance policy against moonlighting.

IBM’s Approach:

IBM has also issued warnings to its workforce regarding moonlighting. The company has made it clear that such practices are not acceptable, reinforcing the policy to ensure that employees dedicate their professional energies solely to IBM.

TCS’s Approach:

Tata Consultancy Services (TCS) has voiced concerns over moonlighting, declaring it a matter of ethics and in direct contradiction with the company’s values and culture. TCS emphasizes integrity and full-time commitment from its employees, discouraging any form of dual employment.

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