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SIH26184SoftwareBlockchain & Cybersecurity

Development of a Predictive Analytics Framework for Cybercrime Complaints to Forecast Likely Cash Withdrawal Locations in Advance, Enabling Generation of Actionable Intelligence for Timely and Proactive Cybercrime Intervention.

Ministry of Home Affairs

Ideas submitted
141 / 500
Deadline
30 September 2026
Category
Software
Theme
Blockchain & Cybersecurity

Looks like it needs

AI / MLData / AnalyticsBlockchainCybersecurity

• Background The National Cybercrime Reporting Portal is the centralized Portal, which is serving the whole country. Currently, the Portal facilitates citizens in filing complaints, LEAs act on complaints, Banking/Financial Institutions for their actions along with reports/graphs being pulled on daily basis. Presently, the Portal is receiving approximately 8000 complaints on daily basis. The number of complaints has increased manifold during the past months, and this will continue to rise in future. To address the issue of increasing cybercrimes, the proactive approach shall be adopted. • Description This framework focuses on the mitigation of cybercrimes by adopting a proactive approach. The framework's output will enable the prediction of likely cash withdrawal locations, which, in turn, will allow law enforcement agencies (LEAs)

at the state and local levels, coordinated by I4C, to implement proactive interventions. These interventions could include deploying special teams or alerting local banks and ATMs in high-risk areas. The intelligence generated would also help banks and financial institutions (FIs) through the Citizen Financial Cyber Fraud Reporting and Management System, enabling faster fund blocking and increasing the chances of recovery. By supporting real-time actionable intelligence sharing across jurisdictions, law enforcement agencies and Banks/FIs will be able to respond faster and more effectively to cyber threats. This approach goes beyond merely reacting to complaints and creates a powerful, data-driven defense against financial cyber frauds, strengthening India's overall cybersecurity posture.

Enhancing coordination between law enforcement and financial entities will ensure better detection and prevention of financial crimes, creating a more unified and efficient approach to combating cybercrime.

• Key Deliverables Component:- Description a. Predictive Analytics Engine :-AI/ML-based system to analyse historical cybercrime and financial data to predict potential withdrawal hotspots. Features include pattern detection, geospatial risk modelling, and real-time alerts.

b. Risk Heatmap Dashboard:-GIS-enabled dashboard visualizing real-time and potential risk zones with drill-down filters by time, location, and crime category etc.

c. Law Enforcement Interface:-Secure interface for investigators to access alerts, intelligence reports, and evidence documentation.

d. Alert & Notification System:-Real-time notifications to law enforcements, banks, and I4C officers via SMS,email, API, or dashboard triggers.

How contested this one is

as of 28 Sept
141ideas submitted+25 in 2 days

That puts it 80th of the 240 statements that have any ideas at all, out of 240 on the board. It is moving, so the field here is already forming.

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What a jury will ask about this

  1. 01“Who actually faces this problem today?”

    What works: Naming one real person and what they do instead right now. Reading the statement back is not an answer, they already read it.

  2. 02“This already exists. Why yours?”

    What works: That existing tools are consumer products. Yours is built for the ministry, works offline, in the local language, on official data.

  3. 03“Then why has nobody solved it yet?”

    What works: The real blocker. No connectivity, no incentive, nobody owns the data. You only know this if you read the ministry's own reports.

All 18 questions, with the trap answers →

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