Addressing 5 Challenges of Digital Privacy in Identity Verification

The continuous user shift towards online platforms is putting pressure on businesses to facilitate consumers with convenience and speed. They have to allocate additional resources to enhance the digital user experience. Similarly, online identity verification during account sign-in and new customer onboarding is well-equipped with advanced innovative technologies to provide the right balance of ease and fraud prevention.

Below are 5 key challenges of Privacy in Identity Verification that deserves attention in 2021 and beyond;

A rise in Systematic Fraud

Cloud computing has given particularly instant resources to the corporate sector. This has helped companies to innovate and quickly launch new services or products. Unfortunately, the same strategies are utilized by fraudsters also. They can incorporate massive computer power to disrupt digital platforms. Doing so is not difficult today, this can be done at minimum cost with the best efficiency. Failing to protect customer data can have real consequences.

In the recent Congress hearing on Digital Privacy held on 16 July 2021, Shufti Pro’s CEO Victor Fredung said that fake IDs and identity thieves can be detected with 99% accuracy through AI-powered solutions. Thus, businesses can secure their channels with the best possible perfection.

Meeting Customer Expectations

Although we live in an era where data breaches are frequent, some businesses believe that they have adopted the right approach to security and fraud prevention. Nevertheless, they should work on improving the existing security policies and models. Meeting customer expectations is the topmost priority of every industry and business. For this, they might have to rely on external data or services, especially if they are operating at an international level.

Universal Accessibility of Machine Learning

With the emergence of AI and ML, many businesses are transforming from traditional rule-based systems to machine learning models for decision-making. Many machine learning models are provided by third parties, identity verification solution is an associate example. The IDV solution is integrated into the digital systems (website and mobile apps) via restful APIs. While, many companies are building, testing and running their in-house models.

This gives them full control over management. But they have to standardize and normalize the existing database. Then creating model features from it and provision of that data in high-quality with the least delayed service. In general, the normalization and model feature representation is essential for consistency and data feeding respectively. Names or addresses can’t be a model feature, but the financial value of payment can be. A model feature can be;

• Binary (0 or 1)
• Categorical response (high, medium or low)
• Numeric range

Ever-changing Regulatory Landscape

Addition and strictness in data sharing, security and privacy intended government regulations has increased the complexity level for many businesses. In the European Union, the Payment Service Directive (PSD2) monitors how banks and other financial organizations share customer data for payment purposes. Furthermore, GDPR (General Data Protection Regulation) obligates stringent control over data collection and usage. In the United States, the California Consumer Privacy Act (CCPA) protects the privacy rights of California residents. This law includes penalties for non-compliance.

Increasing Cross-Border Commerce

Businesses in the e-commerce sector, and online service providers, usually look for international marketplaces and customers. The intention is to increase revenue and potential. International expansion can be easy for e-commerce businesses because they do not have to arrange huge capital as in brick-and-mortar stores. According to Statista, worldwide retail online shopping revenue will be USD 5.424 billion that was the only USD 2.982 billion in 2018. This should be in the view that moving to new marketplaces can increase the possible risk for frauds and difficulty to provide consistent and frictionless services.

For many businesses, financial in particular online identity verification is;

• The initial step of a strong relationship with customers
• A critical part of maintaining trust and loyalty

Ecommerce businesses can verify their identity while accounts sign up or check out. Address verification has helped them in countering credit card fraud.

They have to maintain a balance between fraud prevention and customer convenience. Customer trust is very delicate, thus can be easily lost. They have to protect user accounts and their data while giving them convenience at the time.

Concluding the Above

The current identity verification solutions are powered by AI and ML, giving the best security against unauthorized access and fake data. It requires minimal user side effort, they just have to upload ID images and selfies. It will check the document authenticity and extract data. Further, the solution will perform facial recognition on it. Businesses can confidently make their channel secure by using identity verification solutions