Cybersecurity threats are evolving faster than the defenses built to stop them. Account takeovers, phishing attacks, and Remote Access Trojans continue to exploit the most persistent vulnerability in digital security: static authentication. Passwords and OTPs, despite their widespread use, remain fundamentally easy to compromise, leaving individuals and institutions exposed at scale. As regulators like the RBI push for stronger multi-factor authentication and enterprises scramble to protect high-value transactions, a new wave of behavioral biometric solutions is emerging to fill the gap.
Analytics Insights spoke with JP Mishra, CEO and Founder of Deep Algorithms, to understand how AI-powered behavioral intelligence is shifting cybersecurity from reactive defense to continuous, frictionless, real-time protection. Excerpts from the interview:
What core problem in cybersecurity led to the creation of Deep Algorithm and why was existing technology insufficient to solve it?
The fundamental concern that led to the inception of Deep Algorithms is to stop fraud that happens when people use static authentication methods like passwords and one-time passwords (OTPs). This is the main reason for account takeover. Most of the system depends on "what the user knows," which is easy to hack with a Remote Access Trojan or phishing. To solve this, we have developed a unique solution which recognizes the user based on how they interact with the device i.e. his biometric behavior like typing pattern, mouse movement, swiping cadence, tapping etc. This is dynamic and legacy systems were not designed to address.
How does Deep Algorithm differentiate itself in fraud detection compared to traditional rule-based or OTP-driven security systems?
Traditional rule-based security relies on rules that have already been set, but our behavior-based biometric security is dynamic and powered by an AI-based real-time risk engine that keeps learning how the user behaves and adjusts to it. This enables real-time proactive fraud detection while operating passively, ensuring a seamless user experience and enhanced security.
What role does behavioral intelligence or user pattern analysis play in your technology stack, and how does it improve accuracy?
Behavioral intelligence is the core design concept of our platform. We analyze the human interactions such as typing rhythms, touch patterns, swipe cadence, navigation flow and device usage behavior to create a unique profile for that user. This way we continuously authenticate users in the background and provide feedback to our AI models to keep learning the dynamic user behavior and keep improving accuracy in identifying anomalies and reducing fraud without adding friction to genuine users.
Can you walk us through a real-world use case where Deep Algorithm successfully prevented or mitigated a high-risk cyber threat?
In one deployment of adapID AI at a leading bank, an attacker with valid credentials attempted to log in to the system. The adapID AI immediately recognized the abnormal user behavior, flagged the session and triggered further step-up authentication and prevented a high-value transaction. This shows the effectiveness of behavior biometric authentication beyond the traditional static credential.
What industries or sectors are currently seeing the highest demand for your solutions, and why?
Our solutions are in great demand across banking, the digital payments ecosystem, and fintech, as these sectors face a high risk of fraud. The RBI's requirement for a required MFA other than OTP has also led to significant demand. Other industries, such as healthcare, insurance, and brokerage firms, are also adopting next-generation authentication using behavioral biometrics to protect their systems from digital fraud.
What is your long-term vision for Deep Algorithm in shaping the future of cybersecurity and digital identity protection?
Our vision is to secure the digital world and move towards a passwordless, frictionless ecosystem. We are aiming to make behavioral biometrics the core layer of digital identity, which will strengthen an organization's digital security proactively and in real time. We can see that Deep Algorithms is helping reshape cybersecurity from reactive defense to an intelligent, AI-based proactive security system.