Karnataka Uses AI to Crack Down on Mule Accounts
8,788 Complaints Linked to 869 Accounts
Cyber Command Shifts from Reactive to Preventive Policing
By Our Legal Correspondent
New Delhi: February 23, 2026:
In a major step towards modernizing cybercrime investigations, the Karnataka Police Cyber Command has traced 8,788 complaints to 869 mule accounts and arrested dozens of individuals involved in cyber fraud. The state has shifted from traditional reactive investigations to AI-led prevention, marking a turning point in India’s fight against digital financial crimes.
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What Are Mule Accounts?
Mule accounts are bank accounts created or controlled by fraudsters to launder money obtained through scams. These accounts are often rented or sold by “mule herders” to cybercriminals for a commission. Victims of online fraud unknowingly transfer money into these accounts, making recovery difficult.
Between December 2025 and February 2026, Karnataka’s Cyber Command arrested 68 mule herders and froze hundreds of accounts used for cyber fraud. Investigators seized mobile phones, passbooks, ATM cards, cheque books, and PAN cards during statewide operations.
How AI Tools Are Helping Investigators
The shift to AI-led prevention has transformed Karnataka’s cybercrime strategy:
- Pattern recognition: AI systems analyze thousands of complaints to identify suspicious transaction patterns across banks.
- Link analysis: Algorithms connect mule accounts with fraud networks, revealing hidden relationships.
- Real-time alerts: AI tools flag unusual activity, allowing police to freeze accounts before money is siphoned off.
- Predictive policing: Machine learning models forecast potential fraud hotspots, enabling proactive action.
- Data integration: AI combines information from banks, telecom operators, and digital platforms to build a comprehensive fraud profile.
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This approach has reduced investigation time and improved the chances of recovering stolen funds.
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Why This Matters
Cybercrime is one of the fastest-growing threats in India, with scams ranging from phishing and OTP fraud to investment schemes. Karnataka’s AI-driven model is significant because:
- It prevents fraud before it happens, rather than reacting after victims lose money.
- It strengthens public trust in digital banking and online transactions.
- It sets a precedent for other states to adopt AI-led policing.
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Challenges Ahead
Despite progress, challenges remain:
- Privacy concerns: AI surveillance must balance efficiency with citizens’ rights.
- Coordination with banks: Effective prevention requires seamless cooperation between police and financial institutions.
- Continuous training: Officers must be trained to interpret AI-generated insights.
- Evolving fraud tactics: Cybercriminals constantly adapt, requiring AI systems to evolve too.
Reactions
- Police officials hailed AI as a “force multiplier” in cybercrime prevention.
- Banking experts welcomed the crackdown, noting that mule accounts are a major vulnerability in financial systems.
- Civil rights groups urged caution, stressing the need for transparency and accountability in AI use.
Closing Note
The Karnataka Police’s use of AI-led prevention to dismantle mule account networks marks a new era in cybercrime investigation. By combining technology with proactive policing, the state has shown how artificial intelligence can protect citizens from digital fraud.
This initiative demonstrates that AI is not just a tool for efficiency—it is a safeguard for financial security in the digital age.
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