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Electricity consumer dishonesty is a problem faced by all power utilities. Finding efficient measurements for detecting fraudulent electricity consumption has been an active research area in recent years. This paper presents an approach towards detection of Non-technical Losses (NTLs) of Large Power Consumers (LPC) in Tenaga Nasional Berhad (TNB) Malaysia. The main motivation of this study is to assist Tenaga Nasional Berhad (TNB) Sdn. Bhd. in Malaysia to reduce its NTLs in the LPC distribution sector. Remote meters installed at premises of LPC customers transmit power consumption data including remote meter events wirelessly to TNB Metering Services Sdn. Bhd. The remote meter reading (RMR) consumption data for TNB LPC customers is recorded based on half-hourly intervals. The technique proposed in this paper correlates the half-hourly RMR consumption data with abnormal meter events. The correlated data provides information regarding consumption characteristics i.e. load profiles of LPC customers, which helps to expose abnormal consumption behavior that is known to be highly correlated with NTL activities and electricity theft. Pilot testing results obtained from TNB Distribution (TNBD) Sdn. Bhd. for onsite inspection of LPC customers in peninsular Malaysia indicate the proposed NTL detection technique is effective with a 55% detection hitrate. With the implementation of this intelligent system, NTL activities of LPC customers in TNB Malaysia will reduce significantly.