The annual crime reports prepared by the Ministry of the Interior show ascending graphs in cases of sexual assault, with a single decline in the times of the pandemic. The latest report, published in 2022 and corresponding to events that occurred in 2021, includes 17,016 sexual crimes, compared to 15,319 in 2019, 13,782 in 2018 and 11,692 in 2017. Four out of five of those registered in 2021, 13,856, were abuses and sexual assaults. In 3,795 of these cases there was penetration.
These are the ones for which there is a record because they are reported, but it is estimated that the hidden bag of sexual violence is over 90%, that is, that nine out of ten attacks never come to the attention of the authorities. In Spain, according to the last Macro-survey of Violence against Women of the Ministry of Equalityreaches 92%, only eight out of 100 women denounce it.
Of those that are known, and as usually happens with a good part of the crimes in Spain, there is a high level of police clarification, 80%. However, that remaining 20% becomes a headache and an obsession for researchers. “In most of the sexual crimes of people over 16 years of age, the aggressor is unknown to the victim (68%), there is no previous relationship between them, the main difficulty in locating them,” says Sergeant Manuel Ramos, who presented his doctoral thesis on the matter at the Law School of the Complutense University in 2022 (Criminological profile of the unknown sex offender: predictive analysis applied to criminal investigation). The latest Interior report also includes it in its conclusions: “In the majority of victimizations, the relationship is none/unknown.”
After five years of intense study of hundreds of cases and their casuistry, Ramos, together with the Criminal Behavior Analysis Section of the Judicial Police Technical Unit of the Civil Guard, has developed a tool based on an algorithm capable of crossing hundreds of of variables —previously entered into its system— and to indicate, according to a series of probabilistic coefficients, potential suspects of committed sexual assaults and areas in which they can be found, according to the information handled in police files.
“It helps us to target and start an investigation, to prioritize and not start from scratch, completely blindly,” explains Ramos. “Then we, psychologists and criminologists, collect the data provided by the machine and interpret it for each specific case,” he says. The tool, which still doesn’t have a name, is beginning to be tested and bear fruit, he says. The system in question is similar to the one created to measure the risk of sexist aggression, although the variables and the objective are different.
The generic profile of this unknown sex offender in Spain is that of a man between the ages of 30 and 40 who lives relatively close to the place where he commits the crime. Approximately 50% are Spanish of origin and three fifths of them have a previous police record for committing other crimes, based on statistical data. On the other hand, the most frequent victim profile is that of a woman between the ages of 17 and 30.
“After compare the profile of the Spanish sexual offender with that of other countries from our environment, we see that here, in Spain, they mostly act impulsively, almost always responding to a sexual drive, without there being a great degree of planning of the attack, which is precisely why it is often frustrated by environmental factors: witnesses face-to-face, unexpected reactions from the victim, weather, an event that he did not count on, an accident… ”, warns Ramos.
The team led by Commander Andrés Sotoca wanted to go much deeper to develop a “predictive” artificial intelligence that could help them in their investigations. In this way, they not only profiled the type of sexual offenders detected in Spain, but also analyzed the type of sexual assaults that are most frequently committed in the country, in order to analyze whether correspondences could be established between them. In this way, with the data collected from that sexual violence that is reported, they came to determine five types of perpetrators and five types of predominant violations.
One. Those who do not have a prior record or administrative offenses, are foreigners, are under 25 years of age or between the ages of 32 and 40, and reside more than a thousand meters from the scene of the events.
Two. Men of foreign nationality with traffic offenses who live less than a thousand meters from the place where they act and without a specific age.
Three. Spaniards under 25 years of age who live less than a thousand meters from their victim and with a police record (for non-violent or sexual acts), although without administrative offenses.
Four. Spaniards between the ages of 32 and 40 with a violent (non-sexual) history and administrative offenses and who live far from the scene of the events.
Five. Men with a history of sexual crimes who live close to the scene of the events, without addiction problems and who are either under 25 or over 40 years of age.
The profiles of the aggressions
Assault with trespassing. The crime is committed within the victim’s home after being suddenly attacked by the perpetrator while accessing the home, doorway, or near it. They are committed mainly in the afternoon or early morning, they are attacks that are not usually consummated due to the context in which they occur (with witnesses and/or screams) and despite the physical violence used by the attacker.
By deception at the author’s address. The attacker approaches the victim on public roads in the afternoon or early at night and, through some kind of deception, manages to move her to her own home. Also due to the context (witnesses, screams, unexpected situations…), this type of attack is often frustrated.
Sudden action in nightlife. In a local, the perpetrator suddenly attacks the victim, who is conscious but under the influence of alcohol and/or drugs, and tries to control her with physical violence, but circumstances prevent her from consuming the rape.
Impulsive attack on public roads. The attacker suddenly attacks the victim in the street in the context of his usual routine, causing injuries but frustrating his intentions.
And with deceit in nightlife. The attacker approaches the victim through some kind of deception and convinces her to leave the place where they are and attacks her when he has managed to move her to a place where she feels safe and where she rapes the victim.
Conclusions after the data crossing
The conclusion that researchers have reached after analyzing hundreds of cases and crossing both categories (types of facts and types of authors) with each other is surprising. It turns out that “the profile of the foreign aggressor without prior records is related to the sudden attack in nightlife.” The profile of the “local perpetrator with no criminal record appears more linked to acts committed with deceit in nightlife venues.” In addition, they deduce that “local perpetrators with a police record are the ones who commit the attacks with trespassing the most,” while “violent foreigners are associated with attacks perpetrated with deceit at the perpetrator’s home.” Finally, “they are usually local sexual offenders who commit impulsive acts on public roads.”
The artificial intelligence developed by this team and which is now being implemented makes it possible to enter all those indicated variables, depending on the details provided by the victim, both those that have to do with the perpetrator and the way in which the act was perpetrated. “It was in a disco, at dawn, we had been drinking, she introduced herself to me, told me she was 23 years old, she accompanied me to the bathroom and there she attacked me,” for example. “The more data that can be provided, the more accurate the machine will be, capable of crossing all these variables at the same time, and even generating a mapping, indicating areas where possible suspects may reside,” warns Ramos. “And better be able to lead the way in search of the wanted sex offender.”
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