police statement

AI tool identifies fake police statements with high accuracy

Image credit: DT

Cardiff University researchers have developed a program that can spot fake written statements submitted to the police by using a combination of automatic text analysis and advanced machine learning techniques.

The team reported that it has been able to successfully identify false robbery reports with over 80 per cent accuracy.

Known as VeriPol, the tool has already been rolled out across all of Spain to help support police officers and indicate where further investigations are necessary.

It is specific to reports of robbery at the moment and can recognise patterns that are more common with false claims, such as the types of items reported stolen, finer details of incidents and descriptions of a perpetrator.

Veripol was designed using natural language processing – a branch of artificial intelligence that helps computers understand, interpret and manipulate human language.

It uses algorithms to identify and quantify various features in text, such as adjectives, acronyms, verbs, nouns, punctuation marks and numbers and figures.

Historical police reports that were known to be false have been fed through VeriPol so that it could code each one and begin to ‘learn’ the specific patterns.

An initial study of more than 1,000 police reports from the Spanish National Police showed that it was “extremely effective in discriminating between false and true reports”, with a success rate of more than 80 per cent.

VeriPol identified a number of themes that were common amongst false robbery reports, including shorter statements that were more focussed on the stolen property than the incident; a lack of precise detail about the incident itself; limited details of the attacker, and a lack of witnesses or other hard evidence, such as contacting a police officer or doctor straight after the incident.

The research team believe the tool could save the police both time and effort by complementing traditional investigative techniques, whilst also deterring people from filing fake statements in the first place.

False statements not only contaminate police databases and damage the outcomes of criminal investigations, but also waste significant amounts of public resources that could be dedicated to pursuing other crimes.

“As an example, our model began to identify false statements where it was reported that incidents happened from behind or where the aggressors were wearing helmets,” said study co-author Dr Jose Camacho-Collados from Cardiff University.

“Similarly, other clear indicators of falsehood were descriptions of the type of objects stolen. References to iPhones and Samsung were associated with false claims, whereas bicycles and necklaces were correlated with true reports.”

VeriPol was put to task on a real-life pilot study in the urban areas of Murcia and Malaga in Spain in June 2017. In just one week, 25 cases of false robbery reports were detected in Murcia, resulting in the cases being closed and a further 39 were detected and closed in Malaga.

In comparison, over the course of eight years between 2008 and 2016, the average number of false reports detected and cases closed by police officers in the month of June was 3.33 for Murcia and 12.14 for Malaga.

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