Artificial Intelligence (AI) now enables organizations to find and detects fake claims. Researchers from the Charles III University of Madrid and Cardiff University have introduced a system called dubbed VeriPol which is a machine learning system to identify false or fake statements through automatic text analysis. It can assure about 80 percent of accuracy in finding fake robbery reports. For insurance purposes, AI can be used as a medium to find out a fake claim without the need of a policeman. In Spain, the law enforcement organizations have adopted AI technologies to expose fake and theft claims.

There's no foolproof way to know if someone's verbally telling lies, but scientists have developed a tool that seems remarkably accurate at judging written falsehoods. Using machine learning and text analysis, they've been able to identify false robbery reports with such accuracy that the tool is now being rolled out to police stations across Spain. Computer scientists from Cardiff University and Charles III University of Madrid developed the tool, called VeriPol, specifically to focus on robbery reports. In their paper, published in the journal Knowledge-Based Systems earlier this year, they describe how they trained a machine-learning model on more than 1000 police robbery reports from Spanish National Police, including those that were known to be false. A pilot study in Murcia and Malaga in June 2017 found that, once VeriPol identified a report as having a high probability of being false, 83% of these cases were closed after the claimants faced further questioning.

Scientists have developed a computer tool that can spot if somebody has filed a fake police statement - based purely on text included in the document. The tool has been rolled out across Spain to support police officers and indicate where further investigations are necessary. And, so far, it has been able to successfully identify false robbery reports with over 80 per cent accuracy. Known as VeriPol, the tool is specific to reports of robbery 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. The research team, which included computer science experts from Cardiff University and Charles III University of Madrid, believe the tool could save the police time and effort by complementing traditional investigative techniques, whilst also deterring people from filing fake statements in the first place.