Identity Verification in the Age of AI: Opportunities and Challenges


Digitization has made our lives more convenient than ever before. Whether you want to open a bank account or shop for a pair of shoes, you can do it from your phone while you sit in your favorite armchair. 

On the flip side, the risk of fraud has risen exponentially. Businesses rarely see their customers face-to-face and have to rely on the information provided to them to know who they are dealing with. 

Identity theft cases have tripled over the last decade with a person now being defrauded every 22 seconds. Hence the need for identity verification. In today’s age, Artificial Intelligence (AI) and identity verification are closely linked and like anything else, there has been a positive and a negative effect.

What is Identity Verification?

Falling prey to impersonators affects a company’s profit margins as well as relationships with actual customers. Identity verification is the only way to combat this. Simply put, this refers to verifying that the customer is who he/ she claims to be. Identity verification is a critical component of Know Your Customer (KYC) processes and due diligence for Anti-Money Laundering (AML) regulations. 

To verify a person’s identity, businesses collect documentary evidence and personal information such as the customer’s full name, age, date of birth, address and so on. This is then compared to data sourced from trustworthy databases to ensure they match. 

Speed and scalability are the biggest challenges for identity verification. While customers understand the need for verification, they still expect a seamless checkout process. With the right tools, businesses can compare data submitted by customers with information from third-party databases and obtain verified results in seconds. This minimizes the need for two-factor authentication and OTP and thus smoothens the checkout process. 

Identity Verification Standards and Regulations

Identity verification is most critical for banking, travel and border control, e-commerce and healthcare industries. Here it is no longer optional but a basic requirement. Identity verification in such cases is governed by regulations that allow businesses to source and save customer records. This includes:

  • General Data Protection Regulation (GDPR)
  • Know Your Customer (KYC) regulations
  • United Nations Security Council Resolutions
  • International Civil Aviation Organization (ICAO) standards
  • 3rd, 4th, 5th, & 6th EU Money Laundering Directive
  • Electronic Signatures in Global and National Commerce Act (ESIGN) 
  • Anti-Money Laundering Act (AMLA) and Counter-Terrorist Financing (CTF) regulations
  • Electronic Identification, Authentication, and Trust Services (eIDAS) regulation
  • The Financial Action Task Force (FATF)
  • Payment Card Industry Data Security Standard (PCI DSS)
  • Financial Crimes Enforcement Network (FinCEN)
  • Consumer Privacy Act (CCPA) and Personal Information Protection and Electronic Documents Act (PIPEDA) under the Consumer Privacy Act
  • Bank Secrecy Act (BSA) and Office of Foreign Assets Control (OFAC) under FinCEN
  • Financial Conduct Authority (FCA)
  • Office for Professional Body Anti-Money Laundering Supervision (OPBAS)
  • Markets in Financial Instruments (MiFID-II) Directive
  • The Customer Identification Program (CIP) of the USA Patriot Act
  • The UK Bribery Act
  • The UK Modern Slavery Act
  • Australian Transaction Reports and Analysis Center (AUSTRAC)

AI and Identity Verification

AI has simplified and streamlined identity verification processes. Companies using AI-based fraud detection tools have been able to reduce chargeback rates by 30%. Rather than manually checking each customer’s information, verification can be automated.  AI identity verification tools can analyze large data sets and keep online identities secure through:

Automated document verification

Rather than manually check documents, identity verification tools with AI can automate document scanning, data extraction and comparison against third-party databases. This makes the process much quicker and eliminates the risk of bias and human error. In addition, AI can identify inconsistencies and anomalies while scrutinizing documents to detect forgeries.

Facial recognition

The use of fingerprints, facial features, voiceprints, iris patterns, and other biometrics for identity verification is steadily increasing. AI can compare selfies submitted during the onboarding process with static images on photo identification documents like a driving license to confirm that they are photographs of the same person. These solutions are not only quicker but also overcome challenges such as variations in poses and lighting conditions to deliver more reliable results. Advanced AI technology also allows businesses to conduct ‘liveness tests’ while onboarding new customers remotely. 

Pattern analysis

At its core, AI is all about recognizing patterns. By analyzing data linked to past customer interactions, AI can recognize patterns created by customers in their past interactions and flag any activity that does not concur with this pattern. This use of AI is helpful for the verification of onboarded customers before completing transactions. For example, AI may flag a customer’s order if it is placed from a geographic location other than the one normally used. 

The Future of AI and Identity Verification

Advancements in AI are inextricably linked to improvements in identity verification. Its ability to continually learn and adapt to changing data sets makes it a steady shield against fraudsters. Further, AI can be leveraged to detect deepfakes and synthetic identities. Sophisticated AI models integrated with technology like blockchain can improve accuracy and data security. It also aids in digital identity transparency.

At the same time, the age of AI also shines a light on challenges connected to regulatory compliance, privacy and ethics. For example, biometric data and sensitive personal information can be misused if the database is not sufficiently secure. Algorithm developers must ensure that biases are not baked into training models to prevent discrimination in real-world applications. Ensuring that these systems are transparent and respect user privacy has become a common topic for debate amongst privacy advocates and technologists. 

A Final Word

Where criminals would once wear masks to rob a bank, today they use false identities and pretend to be someone else. Q2 of 2023 saw 6% of all verification attempts being detected as fraudulent. Embracing AI-driven identity verification technology is proving vital for businesses to protect themselves and their customers from such fraud. 

Businesses using AI technology for identity verification have been able to make their processes more user-friendly, thereby earning their customer’s loyalty while simultaneously staying ahead of fraudsters and emerging threats. 

The post Identity Verification in the Age of AI: Opportunities and Challenges appeared first on Datafloq.

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