DVSA Enforcement activity up 35%
In the 2019 Annual Report and Accounts published by DVSA, the key performance measure of cases where DVSA acted upon the most serous MOT fraud, dishonesty and negligence was up 35%, their target for the year being stated set as a 5% increase.
The report states:
“Enforcing the standards
During the year there were 474 cases where we identified and acted upon the most serious MOT fraud, dishonesty and negligence which is an increase of 35% on the previous year. Cases included examples where the MOT tests were conducted substantially incorrectly, or where fraudulent MOTs were conducted, often linked to irresponsible or unlawful car sales. In the most serious cases, this can lead to loss of authority to test, prosecution and imprisonment. This performance has been achieved by better identifying the garages that showed risk of wrongdoing and targeting resources towards those.”
DVSA are using “predictive analytics” on the data generated by the MOT Computer to help them identify fraud and inadequate standards. Otherwise known as artificial intelligence (AI), or machine learning, abnormal MOT Testing behavioural patterns submitted by Testing Stations to the MOT Computer can be identified, allowing DVSA to effectively target their enforcement and inspection activities. This is the Red/Amber/Green (RAG) classification of Testing Stations and Testers which DVSA are now using to target their Vehicle Examiners’ enforcement visits.
Co-incidentally, DVSA will in the future allow Testing Station owners to give access to their MOT computer account to a suitably qualified third party for the purpose of monitoring their own Test data, so that they may be alerted to any ‘anomalies’ and address them, hopefully before DVSA’s bots find them.
Either way, by reducing fraud and dishonest or negligent MOT Testing, the ultimate outcome will be safer roads.