Page 591 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

Objectives: This use case aims to leverage the power of Artificial Intelligence to significantly
enhance the detection and prevention of fraudulent activities within the NGO sector. The
primary objectives are to:

• Automate the identification of financial irregularities and suspicious patterns in NGO 4.6: Finance
transactions.
• Ensure greater compliance with regulatory frameworks such as the FCRA, CSR guidelines,
and tax laws.
• Improve the transparency and accountability of fund allocation and utilization within the
NGO ecosystem.
• Enable early detection of potential fraud, allowing for timely intervention and minimizing
financial losses.

Technological Approach: This use case implements a multi-layered AI-driven system integrating
several cutting-edge technologies:

• Machine Learning (ML): Algorithms will be trained on historical financial data to identify
anomalies indicative of fraud, such as unusual transaction volumes or transfers to
unverified entities.
• Graph Analytics: By building a network of relationships between NGOs, their directors,
addresses, and financial transactions, this approach will detect interconnected fraudulent
entities like duplicate or shell NGOs.
• Geospatial and Satellite Data Analysis: Satellite imagery and location data will be used to
validate the existence and operation of claimed projects on the ground, crossreferencing
NGO reports with real-world evidence.
• Natural Language Processing (NLP) and Sentiment Analysis: AI will analyse social media,
news articles, and whistleblower reports to identify public complaints and allegations of
financial mismanagement or corruption related to NGOs.
• Optical Character Recognition (OCR): This will automate the extraction of information
from scanned documents during registration and compliance checks, enabling efficient
data comparison and anomaly detection.

Expected Impact and Benefits: The implementation of this AI-driven fraud detection system is
expected to yield significant benefits:

The implementation of the AI-driven fraud detection system for NGOs is anticipated to deliver
transformative outcomes, enhancing efficiency, transparency, and trust in the NGO sector. Key
impacts and benefits include:

• Significant Reduction in Fraudulent Activities: The system is projected to reduce fraudulent
transactions by 30% within 12 months of pilot deployment by proactively detecting and
deterring misuse of funds, duplicate registrations, and shell NGOs.
• Enhanced Operational Efficiency: Automation of registration verification, financial
monitoring, and audit prioritization is expected to decrease audit processing time by
50%, reducing manual workload and enabling faster identification of suspicious activities.
• Real-Time Detection and Intervention: Continuous monitoring will enable early detection
of irregularities, with 85% accuracy in risk scoring for high-risk NGOs, facilitating timely
investigations and preventing significant financial losses.
• Robust Project Validation: Geospatial and satellite data analysis will validate 90% of
reported project locations, ensuring funds are utilized for legitimate initiatives and
minimizing discrepancies between reported and actual activities.
• Increased Transparency and Accountability: Real-time tracking of financial transactions
and compliance, coupled with accessible audit trails, will ensure NGOs are held
accountable, fostering a transparent ecosystem for government and CSR funding.

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