@article{NADEEM2021101304, title = {A data-driven approach to reduce electricity theft in developing countries}, journal = {Utilities Policy}, volume = {73}, pages = {101304}, year = {2021}, issn = {0957-1787}, doi = {https://doi.org/10.1016/j.jup.2021.101304}, url = {https://www.sciencedirect.com/science/article/pii/S0957178721001387}, author = {Ahmad Nadeem and Naveed Arshad}, keywords = {Big data analytics, Automated metering infrastructure, Electricity theft}, abstract = {Theft of electricity is a problem in many developing countries. But AMI is paving the way for data-centric architecture to help in theft detection. However, a smart grid or even AMR is a long shot for many developing countries due to the costs involved in its large-scale deployment. This paper presents a technique to detect outliers among electricity users that further investigates electricity theft using data analytics on monthly usage data available to every utility company. Using this technique, we have reduced the search space for theft identification to as low as 3.4% of the total customer base.} }