Javelin’s 2020 identity fraud survey found that the total cost of identity fraud in 2019 was approximately $ 16.9 billion. These costs include data breaches, fines from data protection regulations like CCPA and GDPR, and lost or damaged resources. Due to these imminent risks, authenticating user identities is critical to your security infrastructure.
Basically, users register themselves. Self-registration is a form of proof of identity that in most cases records telephone number and e-mail. This is not enough as it reveals minute details about the user. For this reason, it is critical to go beyond self-registration and take advantage of intelligent and automated identity verification to identify users who need access to your system and network.
What is identity proofing?
Identity proofing is a process used to verify the identity of a user. Do not mix this with normal authentication which is based on the combination of username and password. Identity precedes the time when users secure their credentials to sign in to an application along with normal authentication process.
To better explain spoofing, the two definitions of the National Institute of Standards and Technology (NIST) are sufficient. In accordance with the NIST Digital Identity Framework;
Claimed Identity: Data related to the identity provided by users when registering into an IAM system. In other words, who they claim to be.
Actual identity: Data proving the validity of the user’s identity. This is who they really are.
Identity proofing has one main purpose: To ensure that the purported identity is synchronized with the actual identity of the users, so it acts as the first layer of defense against the intrusion of the identity perimeter.
So the question is, why automate Identity proofing? What are the shortcomings of the manual process?
Risk of compromise by ignorant staff
There have been several cases of compliance staff responsible for checking ID documents and getting their hands dirty in the event of identity theft. The manual process is flawed. Once customers discover that their sensitive information is being used for questionable activity, they will no longer believe your company’s reputation.
Building a human workforce costs you more than automation. For a human workforce, you have to pay wages, buy computers, pay rent, and make other miscellaneous expenses. For example, it could cost you $45 / hour to compensate the compliance team. That’s roughly $225,000 a year for a team of 1,000. Marketwatch has also cited the average cost of renting a space per employee, which is roughly $14,800 a year in New York. If you choose an automated solution, you can reduce all of these costs by 70%.
Snail-speed processing
Cost aside, it will take a long time to properly engage the compliance team with a manual process. You can lose potential customers who need your services on the spot, or your reputation can be damaged by mishandling by untrained personnel. they are still using manual KYC, which can take days or even weeks. If your customers have to wait for days, they better go where the process is automated.
Human error
People get tired and this tiredness can lead to mistakes. This is a major challenge when using manual ID checks. On the other hand, machines don’t get tired or bored; and they cannot lose focus. In addition, errors can occur when an organization lacks a trained and competent compliance team.
Difficulty in scaling
Manual ID checks become difficult to scale as you enter new markets when you had to outsource a new team familiar with local regulations. On the other hand, automated verifications enable companies to acquire new customers in real time.
What are the benefits of intelligent and automated identity proofing?
- The automated proof of identity simplifies the onboarding process and enables companies to increase their customer retention rate. With a digital solution, you can verify the identity of users in minutes.
- You can scale without hiring or outsourcing a large compliance team. Automation enables easy access to new markets.
- Secure storage of sensitive data provided by users.
- Documents are verified using innovative and advanced technologies such as OCR, machine learning and MRZ recognition.
What KYC solution providers check-in documents and how?
For an identity document to be verified successfully, the chosen platform will verify the correct colors, document edges, brightness and tilt. Then it automatically classifies the document by:
- type
- issuing country
- revision
For an identity document to be verified successfully, the chosen platform will verify the correct colors, document edges, brightness and tilt. Then it automatically classifies the document by:
Next, it verifies the visual authenticity. It looks out for the security features. Are the characters correct or is the document a duplicate? Is it aligned with the guidelines of the template document? Is there a photo above? Next, the Machine Readable Zone (MRZ) code matches the document type, which is then categorized into rule-based values. These decoded values are matched for validity against data generated by the visual appearance of the document.
The system then scans for portrait photos, extracts additional features such as photo, signature, barcode and QR code from the provided document and also checks the expiration date.
Use the data from the document to check the user’s profile and mark any discrepancies. The system then prompts the user to provide selfie photos along with the document to be reviewed. The selfie photo is compared with the portrait in the document. This is to verify that the images are from the same person.
How can companies automate identity proofing?
If you’ve decided to automate your identity verification process, here’s what you need to know:
1. Identity document capture
The right solution enables organizations to incorporate automatic file capture into their applications. The right tool will also guide the user through the entire verification process.
2. Biometric capture
Biometric tools allow users to pose for a selfie. A face recognition video can also be requested to link the identity of the owner to the documents.
3. Automated and hybrid analysis
Deep Scan carries out a real-time analysis of the transmitted files as well as a biometric recording and a comparison of data sets. If there is any difficulty verifying the identification, a fraud professional will intervene for manual verification.
4. Real-time results
After completing the analysis, the user receives a real-time result on the validity, authenticity and consistency of the analyzed documents.
Artificial intelligence in the field of automated proof of identity has shown better results than human verification. Machines are not boring, biased, or prone to common human error mistakes. I firmly believe that companies will get better results with authentication automation than with manual processes.
