Sagar Gupta on Why Continuous Identity Verification Could Transform Digital Security

In conversation with David Soffer, technology executive and inventor Sagar Gupta discusses the limitations of passwords, the financial risks of compromised digital sessions, and his German-registered invention for continuous identity verification.

As financial institutions and businesses become more dependent on cloud platforms, remote access and digital transactions, identity security is becoming increasingly important.

Technology executive and inventor Sagar Gupta has developed a system designed to verify a user’s identity continuously rather than relying only on a password, one-time code or biometric check at login.

His invention, “Device for Continuous Identity Verification Using Multi-Modal Biometrics and Behavioral Signals,” is protected under German Utility Model Registration No. 20 2026 100 678, registered on March 6, 2026.

In this interview with David Soffer, Gupta explains how continuous authentication could help businesses reduce fraud and strengthen digital trust.

David Soffer: What problem does your invention address?

Sagar Gupta: Most digital systems verify a person only at the beginning of a session.

A user enters a password, approves a one-time code or completes a biometric scan. Once access is granted, the system often continues trusting the session until the user logs out.

However, a legitimate user may leave a device unattended. An attacker may steal an active session token, or malware may take control after authentication.

The login may have been genuine, but the person currently controlling the session may no longer be authorised.

My invention addresses this gap by evaluating identity throughout the session.

David Soffer: How does continuous identity verification work?

Sagar Gupta: The system can analyse several authorised signals, including typing rhythm, mouse movements, touchscreen behaviour, device information, network context and application-navigation patterns.

Where legally and ethically appropriate, biometric characteristics such as facial or voice signals may also be included.

These indicators are evaluated together to create an identity-confidence score.

When behaviour remains consistent, the system can continue operating without interrupting the user. When significant differences appear, it may request additional authentication, restrict a sensitive action or alert the security team.

David Soffer: Why is a multi-modal approach necessary?

Sagar Gupta: No single signal is completely reliable.

Typing behaviour can change because of stress or fatigue. Facial recognition may be affected by lighting. A person’s location may change because they are travelling, and an authorised employee may start using a new device.

A multi-modal approach examines several indicators together.

A new location may not be suspicious when the device, typing behaviour and activity remain familiar. However, unusual typing, unfamiliar navigation and an attempt to change banking details could justify stronger verification.

The combined pattern is more meaningful than any single signal.

David Soffer: How could this technology help financial organisations?

Sagar Gupta: Financial services are an important potential application because compromised access can lead directly to fraud.

A bank or business could apply stronger identity checks before a user changes payment instructions, adds a beneficiary, transfers a large amount, modifies account information, exports sensitive financial data or approves a high-value transaction.

Instead of treating every action equally, the system could require a higher level of identity confidence for activities carrying greater financial risk.

David Soffer: Does this replace multifactor authentication?

Sagar Gupta: No. Continuous verification is designed to complement multifactor authentication.

Multifactor authentication strengthens the login process by requiring more than one form of evidence. However, it usually confirms identity at a particular moment.

Continuous verification operates after login and helps determine whether the established trust should be maintained.

Multifactor authentication can establish initial trust, while behavioural, biometric and contextual signals help protect the remainder of the session.

David Soffer: What role does artificial intelligence play?

Sagar Gupta: Artificial intelligence can identify patterns that fixed security rules may miss.

A basic system may automatically treat access from another country as suspicious, even when an executive is travelling legitimately. It may also flag a change in typing speed even though normal behaviour varies.

An intelligent system can evaluate the overall context, historical patterns and sensitivity of the action.

This allows security controls to become more adaptive and proportionate.

David Soffer: Are there privacy concerns?

Sagar Gupta: Privacy must be built into the system from the beginning.

Continuous identity verification should not become unlimited employee or customer surveillance.

Organisations should collect only the information necessary for security, clearly explain how it is used and apply encryption, limited retention and strict access controls.

Where possible, systems should use protected biometric templates or calculated confidence values rather than storing unnecessary raw biometric information.

The objective is to protect the person’s identity, not invade their privacy.

David Soffer: What inspired you to develop this invention?

Sagar Gupta: My work in enterprise applications, ERP systems, cloud infrastructure and cybersecurity repeatedly showed me that a valid account is not always the same as a verified human identity.

An account may have the correct password, trusted device and active session token, yet those technical indicators do not always prove that the authorised person remains in control.

I wanted to explore a system where trust could change dynamically according to behaviour, device context and transaction risk.

David Soffer: What is your long-term vision?

Sagar Gupta: I believe digital identity will become continuous, adaptive and risk-based.

A successful login should begin the trust relationship, not permanently settle it.

When identity confidence remains high, security should operate quietly in the background. When risk increases, the system should respond intelligently.

The long-term goal is to create persistent digital trust across financial platforms, enterprise applications, cloud systems and, eventually, AI agents acting on behalf of human users.

About Sagar Gupta

Sagar Gupta is a technology executive, inventor and enterprise-transformation leader with more than two decades of experience in enterprise applications, ERP modernisation, artificial intelligence, cloud infrastructure and cybersecurity. He is the inventor associated with German Utility Model Registration No. 20 2026 100 678.