How does a police department locate a “dangerous sexual predator using only the perpetrator’s first name and a street name the suspect may – or may not – have lived on[?]” That was the dilemma facing the Springfield, Massachusetts Police Department in 2018. /1/ The police turned to Thompson Reuters, a “leading source of news and information for professional markets.”

Cristina Fernandez is a Crime Analyst and Reporting Supervisor at the Springfield Police Department. She “describes[d] how difficult it was assisting with an investigation with so little information to go on. ‘We had his first name and we had a street address – at least, we thought we had a street address,’ said Fernandez, adding that initially the street name had been incorrectly listed in the police report.” /2/

According to a blog post from Thompson Reuters, “[t]he incident began when a woman reported to the SPD that she had been raped and held against her will by a man she met through social media. ‘She really didn’t know much else about him,” Fernandez said. “But he had taken her back to his place and had assaulted her there.'” /3/

With very little to go on, Fernandez turned to the private sector, which can harness the power of data to crack open cases like sexual assault and terrorism. Using the Thomson Reuters CLEAR search database, Fernandez was able to “pull up vital information based on even a little bit of data.” Since “[t]here is no way within our internal case management system to search for a suspect by first name only, so we had to look outside our own system for resources[,]” Fernandez was able to use the “robust search” capabilities that CLEAR offers so that even with “minimal pieces of information, [she] can usually generate a list of names and at least it’s a starting point…” /4/

While “none of the names on the list generated by CLEAR was an exact match for the street name[,] one of the individuals lived on a street with a similar name. That person was also of a comparable age to the reported suspect.” From there, police “analysts believed this might be their man in the end, Fernandez and that the address in the police report might be wrong.” Using information generated by Thompson Reuters, the police could then look to other research tools and technologies. Ultimately, the police were able to zero in on the suspect who was “arrested and charged with kidnapping, assault and battery, aggravated rape, and indecent assault and battery.” The blog noted that the man convicted in the case may also have perpetrated other crimes. /5/

/1/ Springfield PD catches a predator: How Thomson Reuters CLEAR helped the Springfield Police Department catch a predator using very few clues, blog post, April 2018.

/2/ Id.

/3/ Id.

/4/ Id.

/5/ Id.