From Fintech to Mobility: How AI is Reinforcing Trust in Smart Cities
AI establishes digital trust foundations, securing Internet of Vehicles networks through integrated advanced technologies for safe, efficient urban mobility.
Artificial Intelligence (AI) is no longer just a support technology it has become the foundation of digital trust. Its application can be seen in the financial systems as well as in the new sphere of smart mobility. With the pace of smart city development in the world, AI is taking the center stage in the quest to guarantee security, privacy and confidence of the citizens.
Indian-origin technologist Pushpalika Chatterjee is a FinTech leader and independent AI researcher working in the United States. She has contributed to this debate through recent research published in a peer-reviewed Springer journal, internationally recognized in computer science. The study proposes an AI-based blockchain framework for the Internet of Vehicles (IoV), showing how federated learning, deep learning, and blockchain can together protect urban mobility networks.
AI as the Foundation of Mobility Trust
In smart cities, vehicles are no longer isolated. They function as intelligent nodes, sharing real-time data on speed, congestion, and safety. This improves efficiency but also creates risks. Malicious actors could inject false congestion alerts, misdirect emergency services, or disrupt entire networks through coordinated cyberattacks.
AI addresses this challenge by serving as the intelligence layer in IoV systems. Chatterjee's framework uses neural networks and probabilistic models to identify anomalies within milliseconds, preventing disruptions before they spread. For metros like Delhi, Mumbai, and Bengaluru already facing severe congestion the role of AI is not optional but a public safety necessity.
Inside the Framework
The research integrates several advanced techniques into a single framework. Long Short-Term Memory (LSTM) models capture sequential patterns in traffic data, while Naive Bayes classifiers enhance classification accuracy. Federated learning enables the system to train collaboratively without exposing sensitive driver data, and blockchain provides tamper-proof validation of updates.
The framework achieved significantly higher accuracy than traditional IoV systems, which usually achieve only about 88 91 percent accuracy. More importantly, the framework demonstrated robustness even under high attack density, confirming its scalability and real-world viability.
Bridging Domains: AI in Payments and Mobility
Chatterjee's FinTech background provides a powerful parallel to her mobility research. In financial systems, AI has been indispensable in fraud detection, validating billions of transactions daily within milliseconds. The same principle applies in mobility, where millions of vehicle signals must be verified instantly to ensure the reliability of transport networks.
In payments, AI blocks fraudulent transactions as they occur; in mobility, it blocks malicious vehicle signals in real time. By applying financial-grade trust models to urban transport, the research demonstrates how AI solutions can move seamlessly across sectors. For policymakers, this underscores the importance of cross-sector innovation, where proven governance strategies from banking can inform approaches to mobility and other domains.
Why This Matters for India
India faces one of the toughest mobility challenges globally. Congestion drains nearly 1.5 lakh crore from the economy every year, while Bengaluru commuters lose an average of 243 hours annually in traffic the highest figure recorded worldwide. The Smart Cities Mission has identified IoV and AI-enabled traffic management as key solutions, but their effectiveness depends on citizen trust.
Chatterjee's framework offers an integrated approach to this problem. By using federated learning, it preserves privacy and ensures that sensitive vehicle data never leaves the device. Through blockchain-backed validation, it guarantees the integrity of system updates, making them tamper-proof. And by embedding AI-based anomaly detection, it ensures resilience against cyberattacks and false data injections.
This mirrors India's experience with the Unified Payments Interface (UPI), which only achieved mass adoption after fraud detection and encryption protocols built confidence in the system. Similarly, IoV networks will require AI-driven safeguards as a prerequisite for nationwide rollout.
Why the World Should Care
The governance significance of this research extends beyond India. By 2030, cyberattacks on connected vehicles are projected to cause $23 billion in annual losses for automakers. In the United States, congestion already costs $87 billion annually in lost productivity and fuel.
An AI-powered IoV framework offers governments a scalable model to mitigate such risks. By embedding security, privacy, and reliability directly into the infrastructure, cities worldwide can create trust frameworks for next-generation mobility systems.
AI as a New Governance Tool
The central message of this research is that AI should be treated as a form of governance technology. It must be embedded into city planning and regulatory frameworks, rather than added later as an optional feature. When combined with blockchain and federated learning, AI transforms mobility management from reactive monitoring to proactive governance. Instead of responding after crises occur, systems can anticipate and neutralize threats before they escalate.
For policymakers, this requires integrating AI-led resilience into baseline urban standards, just as safety codes and environmental rules form part of today's planning frameworks.
The Road Ahead
The coming decade will see autonomous vehicles, AI-enabled logistics, and 5G-powered mobility become mainstream. For rapidly urbanizing nations like India, the challenge will not be whether these technologies are adopted but whether they are secure, scalable, and citizen-trusted.
Chatterjee's dual role as a FinTech leader and independent AI researcher positions her uniquely to contribute to this transformation. Her work goes beyond academic theory, offering a practical framework for embedding AI-first trust into urban infrastructure. By designing systems that integrate AI, blockchain, and privacy safeguards from the outset, cities can ensure that smart mobility is not just connected but also safe, efficient, and resilient.
Conclusion
AI is redefining how cities and governments manage digital infrastructure. The research led by Pushpalika Chatterjee illustrates how AI-powered detection, blockchain validation, and federated learning can together create the trust architecture for smart cities.
For India, this offers a pathway to strengthen the Smart Cities Mission, reduce economic losses from congestion, and build public trust in emerging technologies. Globally, the same principles apply as governments prepare for hyper-connected mobility.
The future of smart cities will be judged not just by connectivity or speed, but by their ability to embed trust through AI and resilience from the ground up.
