Hello everyone. My name is Vanka Krishna Ramesh, mark. Today I would like to present you with digital identity. With ai. AI powered digital identity solutions are fundamentally reshaping how verification occurs across financial, healthcare, and government sectors. These intelligence systems not only strengthen security through advanced biometric authentication. But also eliminate friction in user journey while enabling personalized digital experience that were previously impossible. Example, how users are opening a bank account online in two minutes with facial and fingerprint verification, digital identity, powering global prosperity, the economic promise. Potential economic value unlocked by 2030 through global digital identity implementation, 75% UN SDGs. Percentage of substantial development goals supported by digital identity systems, 6.2 billion apps are projected to use digital identity applications. We are up from 1 billion in 2020. Example. India's other system saved 11 billion by reducing identity fraud in welfare distribution. Core AI technologies, facial recognition, AI systems, map distinctive facial features into mathematical representations, enabling secure identification with sophisticated anti spoofing mechanisms. Examples, airport eGates fingerprint analysis. Deep learning algorithms detect and compare microscopic bridge patterns and minute points achieving near perfection verification accuracy. Example, smartphone unlock. Voice identification, sophisticated neural network analyze or a hundred al characteristics, including pitch, tune and to create unique voice signatures for authentication. Example, banking via phone assistant behavioral analytics. ML algorithms continuously monitor typing patterns, navigation habits, and devise interaction styles to provide seamless background authentication. Example would be continuous verification during app use. We can take an example. AI flagged a credit card fraud attempt by spotting unusual geolocation and behavior. This is possible by using AI technologies, fraud prevention system. Real time detection. Advanced AI algorithms continuously monitor transactions instantly identifying and flagging suspicious anomalies before fraud occur. Pattern recognition, sophisticated machine learning models analyze historical data to identify complex fraud patterns, invisible to traditional systems. Multi-factor authentication. Robust security frameworks integrate biometric, behavioral and knowledge based verification methods for comprehensive protection, adaptive security, self evolving protection mechanisms automatically adjust to emerging threats through continuous learning and feedback loops. Example, a FinTech app, allowing password, let's log in and instant transfer via face id. Industry applications, financial services, advanced biometric verification enables secure account and frictionless payments, reducing fraud rates by 90% while boosting customer trust, streamlined customer onboarding, completed in minutes instead of days. OneTouch transaction approval, eliminating password frustration healthcare. Precise patient identification, safeguards, medical recognition, integrity prevents treatment, errors and protections to health. Information from unauthorized access, HIPAA compliance, health data access with multifactor security, automated insurance verification, reducing administrative burden, travel and border control. AI powered contactless verification, accelerate security process by 60% while significantly enhancing threat detection and passenger experience. Average wait times reduced from hours to minutes. Advanced risk assessment capabilities for proactive security, touchless face scans at airport customs, reducing wait times from two hours to 15 minutes. User experience benefits faster transactions. AI powered verification slashes, processing time from minutes to seconds, eliminating unnecessary, waiting and boosting customer satisfaction. Cross platform compatibility. The unified digital identity functions effortlessly across multiple services and platforms, creating a cohesive ecosystem. Experience reduction, friction. Seamless passwordless authentication eliminates the frustration of remembering complex credentials and the hassles of constant resets, excuse me, personalized experience, secured verified identity, enabled tailored services and recommendations while maintaining robust user privacy controls and data protection. Example, a user logs into their insurance, banking and travel app with a single id. Privacy challenges data minimization. All systems must collect only essential information for verification or collection. Not only increases privacy vulnerabilities, but also amplifies regulatory compliance risks and erodes user trust. Consent management users require granular control or how their identity data is shade and stored. Implementing transparent user-friendly consent mechanisms is crucial for building trust and maintaining regulatory compliance. Surveillance concerns, biometric identification systems, risk enabling unwanted mass surveillance. Robust ethical frameworks and technical safeguards must be implemented to prevent identification technologies from facilitating privacy intrusions or civil liberties violation. Example, transparent consent prompt before collecting voice data. Inclusivity considerations, universal access. Ensure equitable identity verification for all demographics regardless of age, economic status, or technical proficiency. Cultural adoption. Designing systems that represent cultural sensitivities around biometrics personal data and identify representation, access global communities, accessibility features, implementing diverse verification alternatives for people with visual, auditory, or our motor impairments to prevent exclusion technology options. Providing multiple identity verification pathways for users with limited connectivity. Older devices are restricted access to advanced technologies. Example, using voice instead of face fingerprint for visually impaired users. We can take numerous examples for this. We can consider all the multifactor authentication options as part of these technology options. Regulatory landscape data protection regulation, G-D-P-R-C-C-P-A and similar frameworks establish strict requirements for data minimization, user concern and security measures in identity management systems, digital identity frameworks, EI DS in EU and DI A CC in Canada. Provide comprehensive technical standards and trust frameworks, ensuring secure interoperable digital identification across sectors. Ethical AI guidelines, emerging regulatory standard. Emerging regulatory standards addresses algorithmic bias, decision transparency, and corporate accountability in AI identity systems. While prompting fairness and human oversight, crossroad interoperability. International collaboration initiatives seek to harmonize identity verification protocols. Enabling secure cross border transactions while respecting al so and privacy requirements. Example, G R's requirement for explicit consent in biometric use implementation roadmap. Conduct comprehensive audit. Of existing identity systems and define specific business and technical requirements, infrastructure. Develop secure technical foundation with encrypted data storage and robust API integrations pilot program. Deploy to sector user groups with detailed feedback. Collection to validate performance and usability. Scale deployment, expand implementation across organizations with real time monitoring and iterative enhancements. Example, pilot project. Pilot project for digital ID in university. Our local government service. The future of digital identity, the digital identity landscape is evolving towards self-sovereign, decentralized systems secured by quantum resistant encryption. These advanced frameworks will deliver unparalleled protection against emerging threats, while empowering individuals with complete control or their personal information. The convergence of blockchain verification and international standards will enable seamless crossroad integrity verification without compromising fundamental privacy rights. Example, decentralized ID on blockchain with user control data wallets. Are you ready to lead the identity renovation revolution? Assess your current identity systems and consider AI integration. I would like to give an example of overall system where we can implement ai. It could be a network security or an application security. Our data privacy, our data security. We can implement ai. Let's take one, one example at each instance, for example, network security. If we implement AI in network security, we can save a lot of our team's time and effort in, in figuring out what exactly the fraudulent activity are. We can reduce the numerous false positives and increase, increase our team performance and try to. Increase our effectiveness, the way in which the team is performing. The tasks are increase our productivity. By implementing ai, like for example, if we are collecting all the logs and we are storing them in a system that we are getting from sim, if we integrate ai, it would be much easier for AI to go and review the data and tag it along with the most recent activity and figure out whether any unwanted activity or unauthorized activities are happening. Which which a normal network resource can do. But that takes a lot of time. But whereas AI can do it much faster with less resources when coming to the development, we can use AI to write more code in less time and help to validate our, test our systems proactively. And for any. Leaks in the code or any memory management or any password leaks that are happening through code, we can use AI to, to make our code more secure and coming to the data security we can implement AI to, to figure out what exactly would be the best. Applicable solution for our environment and we can try to test multiple solutions that AI provides and choose the best one that suits our budget and the resource that we have to manage that solution. That's all. Thank you. I will, I would like to thank everyone who is present here to watch my presentation. Thank you. Have a good day.