India Inc. is harnessing AI as a real-time fraud watchdog

AI: The missing piece in the fraud prevention puzzle

Fraudsters are already using AI to execute highly targeted crimes — from deepfake-enabled social engineering and AI-generated voice scams to instant fund diversion and digital arrest schemes. Countering such threats requires equally advanced, AI-driven defenses. Modern AI solutions do not just look for anomalies but combine multiple advanced techniques such as predictive analytics for fraud. This multi-layered approach enables it to detect attacks before any damage is done. Here is how an AI system operates to flag fraud incidents:

• Anomaly detection: One of the key capabilities of an AI system is to spot deviations from normal transaction patterns, making any occurrence of unusual activity an immediate red flag.

• Risk scoring: Assessing the likelihood of fraud and assigning a risk score can help track suspicious transactions or users, enabling risk management teams to jump into action immediately.

• Network analysis: Organized fraud schemes are deeply embedded within financial systems, often using more than one account. Mapping relationships between accounts can help with financial fraud prevention before it causes mayhem.

• Text mining: Parsing unstructured data (emails, chats, documents) for fraud signals can prove beneficial when it comes to nipping fraud schemes in the bud.

• Identity verification: Leveraging checks such as biometrics, device fingerprints and behavioral analytics to confirm user authenticity enables instant detection.  

AI in action

Constantly evolving AI systems are trained to catch everything — from traditional card fraud to AI-generated voice scams — inspiring regulatory confidence. Transformer-based models can now evaluate hundreds of transaction characteristics simultaneously, outperforming older statistical methods in both speed and accuracy. Hybrid models that combine decision trees and neural networks are touted to achieve response times of under 100 milliseconds with minimal false positives.
 

Large financial institutions are increasingly depending on AI systems to monitor every transaction, flagging potential digital fraud risks within milliseconds. Behavioral AI is also being implemented to profile user activity and raise alerts for activities such as sudden large withdrawals or logins from unfamiliar locations. When it comes to proactive fraud risk management systems, AI is helping companies conduct smart due diligence checks for high-value transfers. 
 

AI infrastructure rooted in governance

India’s regulatory ecosystem is providing an impetus to embedding AI within financial systems to bring fraud incidents in check. From introducing fraud detection tools to detect mule accounts and fraudulent transaction networks in real time, directing banks to adopt the Financial Fraud Risk Indicator (FRI) that enables real-time alerts on risky mobile numbers, to introducing the Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) to encourage responsible implementation of AI structures — RBI is sending out a clear message. Building digital systems rooted in trust comes from adopting good governance practices and achieving systemic resilience. AI systems built on Responsible AI guidelines can expedite fraud detection and boost proactive fraud risk management efforts. 

Building real-time AI command centers

AI-enabled command centers can integrate advanced data and fraud analytics, document authentication, anomaly detection and CCTV-based surveillance insights to reduce false positives in fraud detection, monitor transactions, vendor activities, employee claims, onboarding processes and physical security risks.
 

Enabling proactive risk identification through metadata analysis, OCR and ML can help companies: 

• Set up centralized dashboards
• Achieve automated workflows
• Integrate whistleblower management modules for faster resolution, traceable investigations and audit readiness 

This holistic approach strengthens governance, reduces manual effort and enhances fraud resilience across enterprise ecosystems. 
 

Achieving fraud resilience: One step at a time

India is setting a global benchmark when it comes to digitalization of financial systems. However, to maintain the pace of progress, it is crucial to arrest proliferating fraud incidents. AI-powered real-time fraud monitoring can enable India Inc. to shift their focus from reactive firefighting to proactive prevention. By embedding AI across transaction lifecycles, companies can not only safeguard consumer trust but also reinforce financial integrity in the digital age. 
 

Amit Mishra, Partner, Forensic & Integrity Services, EY India, has also co-authored this article.