In 2024, the global average cost of a data breach reached $4.88 million, marking a 10% increase over the previous year. Additionally, cybercrime costs worldwide are projected to grow by 15% annually, potentially reaching $10.5 trillion by 2025. These escalating figures underscore the critical need for innovative cybersecurity measures to protect sensitive financial information and corporate infrastructure.
Throughout the past years, security in financial technology has been sporadic, with individual engineering teams handling the deployment of security controls for microservices. This approach created loopholes in authentication, logging, and API security, thereby exposing organizations to a myriad of threats. To counter this, a cybersecurity expert, Srajan Gupta, saw the necessity of a unified framework. It therefore led the development of Prebuilt Security Packages, a security model that is standardized to remove inconsistencies by combining authentication, API security, structured logging, and compliance enforcement into microservices. With a background in Zero Trust security, AI-powered incident response, and microservices security, his efforts have revolutionized the way organizations handle security in the digital age to be more proactive, smart, and scalable.
This innovation enabled teams to concentrate on development without sacrificing protection by shifting security from a manual process to an integrated, unified one. Because best practices were applied automatically, vulnerability remediation time was reduced by 40 percent, and security incidents were cut by 60 percent. With security modules preconfigured and built into CI/CD pipelines, the security validation process was automated, thereby preventing vulnerabilities from entering production.
Looking at the significance of this transformation, Srajan shared, “Our data is not secure just because we have a policyātrue security comes from building paved paths that developers actually use.” ā Srajan Gupta. Response times to incidents reduced by half with security enforcement standardization, as centralized monitoring and structured logging facilitated simpler threat detection and mitigation. Developers were freed from manually deploying security controls, thus avoiding human error and simplifying deployment processes.
With the advancement of cyber threats, conventional incident response measures have proven to be inefficient. Security experts have been faced with an inundating number of alerts, most of which were false positives, leading to lost time and late responses to legitimate threats. In addressing this problem, this cybersecurity professional has developed an AI-based anomaly detection and automated incident response system. By using machine learning to process security logs in real-time, the system efficiently identifies and prioritizes legitimate threats while at the same time eliminating false positives.
The addition of Security Orchestration, Automation, and Response (SOAR) functionality enabled real-time containment measures, such as isolation of the affected devices and revocation of unauthorized access based on risk analysis. The results were astoundingāmanual security investigations decreased by 80 percent, false positives decreased by 40 percent, and incident response times decreased from four hours to less than 30 minutes.
After considering the role of automation in the security domain, he said, “AI-powered security isn’t about replacing analystsāit’s about empowering them to work on actual threats. By automating mundane tasks and removing noise, we enabled our teams to move from reactive firefighting to proactive threat hunting.” Besides internal security operations, this innovation paved the way for enhanced cybersecurity through automation in various industries. They were well documented to have made a difference, and made their way to several AI Security Automation discussions and industry meetings.
Srajan Gupta’s cybersecurity innovations extend far beyond the business communityāthey actively safeguard the everyday digital existence of people. Today, where financial fraud, identity theft, and data breaches are increasingly common, his AI-driven security automation ensures that online transactions, personal data, and cloud services are protected from new threats.
For the general user, this translates into a more secure experience where unauthorized access and fraudulent transactions are rapidly identified and fixed in real time. With security automation in banking organizations, Srajan’s solutions significantly minimize risk for online banking, digital wallet, and e-commerce site users. AI-powered anomaly detection prevents unauthorized credit card transactions and notifies users before any harm could be inflicted, thereby providing an additional layer of security.
In addition to financial applications, his security models also benefit medical practitioners by providing the security and confidentiality of electronic medical records. Additionally, automated security controls protect patient information from cyber attacks while maintaining privacy legislation compliance. Also, companies of various sizes, ranging from small startups to enterprise firms, encounter lower operation risks. With security included in development pipelines, Srajan’s innovation enables organizations to develop secure apps from the beginning, thereby avoiding expensive breaches and regulatory penalties.
His leadership and experience in deploying Zero Trust security, AI-powered threat detection, and scalable automation have transformed the way organizations approach cybersecurity. He has proven objectively that security does not have to be a compromise between safety and efficiency, but can be an innovation enabler. By embedding security in all infrastructure layers, automating mundane tasks, and leveraging intelligence-based risk assessment, he continues to raise the bar in proactive cybersecurity by setting new standards for the industry.
