Identity Authentication – Fueling Innovation to the Customer Verification
In today’s world identity verification has become crucial as well as challenging for every industry. Criminals are coming up with advanced methods to forge documents to bypass the verification process. This makes illegitimate onboarding a lot easier for them. Consequently, industries face various consequences like identity theft, data breaches, customer dropoff, and reputational damages.
Industries require adequate mechanisms to accurately verify customers and prevent these risks. The AI-powered ID verification solutions are helping industries overcome these threats by providing robust and seamless customer onboarding. These digital solutions are replacing human efforts by automating the process. It’s easy to integrate, consumes less operational cost, and provides multiple layers of customer identification. The blog covers how AI and ML technologies are taking over verification methods.
Digital Identity Verification Services – Replacing Human Efforts
Online identity authentication is the game-changer for industries in this ever-evolving world. Traditional verification is outdated because criminals are equipped with advanced methods and easily bypass them. Fraudsters are using identity theft to reap both financial and personal benefits. According to Juniper Research, the loss is predicted to rise up to $44 billion by 2024. Shufti Pro Funding indicates that the industries’ need for robust verification is increasing.
The AI and ML-driven solutions provide frictionless onboarding along with fraud prevention. Industries can verify customers without having to call them for face-to-face interaction. The digital solution uses technologies like OCR, biometrics, and machine learning. They not only automate the process but also identify customers in real-time. These solutions are not prone to human errors which makes them more reliable. Below are some of the must-have mechanisms AI and ML provide to industries.
Combine Human Efforts with Machine Learning
Digital customer verification solutions are enabling businesses to analyze huge datasets in minimal time. Incorporating Machine Learning (ML) into the businesses’ verification process has automated and paced up the onboarding process. ML is capable of self-learning which makes it superior to human intelligence. However, machines can face errors too sometimes, therefore, combining them with human efforts can minimize any chances of shortcomings. Businesses can then onboard legitimate customers without having to worry about loopholes.
Traditional verification methods involve various consequences like inaccurate entries, loss of data, or stolen records. This exposes businesses to criminal threats such as identity theft. Furthermore, customers can not easily access their data due to paper-based records. Customers nowadays are the most concerned regarding data transparency and if they see any related threat, businesses will ace drop-off. However, AI and ML technologies streamline these concerns by providing easy-to-access databases.
Customers can record their data by scanning their documents, facial features, and fingerprints. When they come back to the platform, the system offers auto-fill options so that legit customers can escape the hassle. These technological shifts are proving to be reliable options to retain customers’ trust and privacy of their information.
In this technologically evolved world, businesses can not simply rely on just identity and document verification. As per Shufti Pro News, criminal is way more advanced and easily fakes these attributes. This makes it tough for the verification processes to draw a line between legal entities and importers. Therefore, to ensure that criminals are not onboarding the platform, businesses need to incorporate robust identity verification services.
These technologies provide multi-layer identification that identifies customers by not only validating their documents but also analyzing distinct traits. For instance, facial features, iris/retina scan, DNA analysis, fingerprint, voice recognition, and liveness detection. Criminals can forge documents but it is impossible to replicate these features.
Cross-Verification Across Databases
Criminals no more stay connected to one industry for their malicious activities, to move across them to escape the regulatory checks. This makes it difficult for businesses to identify their identities and backgrounds. However, AI and ML-driven technologies are helping industries to access global databases and cross-verify customers prior to their onboarding. This way businesses can not only attract and onboard legit customers but also keep track of their activities.
Integration as per Requirements
Not every industry has the same requirements and they also vary from one region to another. Therefore, incorporating the same technologies can fall inadequate in identity theft protection. Businesses should line out their requirements and the data they need before integrating AI and ML-driven solutions. For instance, the finance sector focuses more on the transaction, whereas e-commerce has “address verification” as one of its top priorities.
Criminals are using advanced technologies to fake identities and illegitimately onboard platforms which is increasing the need for more effective solutions. Fortunately, AI and ML technologies are offering such services and streamlining the identity verification process. With its multi-layer identification and data transparency, businesses can address all the loopholes while leaving no room for criminals. Online ID verification is readily replacing human efforts while uplifting the businesses’ operations.