Cost of rural crime in Leicestershire was £1.2million last year

A report by rural insurers NFU Mutual found Leicestershire was the fourth highest by cost – with Lincolnshire the worst affected county coming in at £2.4million.The insurers say farm vehicles are the top target with Land Rover Defenders, quad bikes and trailers the most common items to be stolen. The theft of farm animals and machinery also increased.Compared to 2020 the county had seen a decrease in crime by 0.7 per cent.But insurers say the pandemic period has been an exception and the respite from rural theft will be short lived with estimates for 2022 showing a rise in costs by more than 40 per cent nationally in the first quarter of the year.NFU Mutual rural affairs specialist Rebecca Davidson said: “Our latest claims figures warn rural theft is quickly gathering momentum as criminals make up for time lost over the past two pandemic years. We’re advising rural people to review their security, to help prevent crime and disruption.“With prices of essential farm equipment such as tractors and quads rising fast and the cost of diesel soaring over the past year, there’s little doubt that criminals will be trying to steal from farms. We also know that essentials of rural living like heating oil tanks will only become more attractive to thieves as costs rise.“Crime in the countryside causes high levels of anxiety and disruption, with many farmers and rural home owners feeling vulnerable due to their isolated location. The knowledge that determined thieves are scouring the countryside looking for targets, and returning to carry out night-time raids can lead to sleepless nights for people in remote areas.”

Farmers are now being urged to boost security as fuel and machinery prices soar and rural locations are expected to be targeted by thieves.

Rebecca added: “As each farm or home is different, every property needs a different approach to keeping thieves out - and there’s an armoury of measures to help do so, from traditional fortification, to technology using movement sensors, to community information networks.”