VERA for profiling criminals

Criminal profiling is a critical tool for police investigations. The behavioral analysis section of the APN in Spain currently uses the VERA method to profile criminals. Developed by D. Juan E. Soto Castro, section head and National Police, psychologist and researcher, the VERA method is consolidating as one of the most successful and professional to define this type of profile.

SEEA is an acronym for Victima-Scene-Reconstruction-Author(Victim-Scene-Reconstruction-Author). The method applies in cases of homicide, kidnapping, theft, sexual assault, in isolated or serial cases, as well as in case of disappearance of high-risk persons. He uses a combination of concepts and principles derived from psychology, research studies and his own professional experience.

  • When collecting data.
  • All are categorized according to their membership in the different sections.
  • Differed from each other by data relating to the victim.
  • The crime scene.
  • The potential aggressor.
  • Etc.
  • Each data is identified by a code where the first letter is D (data).

The second letter corresponds to the block in which it is classified (Victim V, Scene E) followed by its order number. When collecting data, it is important that a clear distinction be made between modus operandi, ritual, staging and personal seal. All of this is the first phase of data collection.

In the second phase, inferences are made that a crime or crime is a very complex scenario, and the assumption is that most of them follow a common path, so it is essential to accurately reconstruct the history they represent. In this way, the collected data is analyzed individually, but also together.

As in the first phase, each of the inferences is recorded and received a code, in this case it will always start with the letter I of inference, followed by the corresponding letter if it refers to the victim, the victim, etc. Inferences must be rigorous and objective. In addition, they should be deleted when new data requires it.

The third phase is hypothesis. They will be encoded as in the previous phase, this time with the letter H. A list of hypotheses is drawn up, which will be the starting point for the elaboration of the criminal profile, which can be derived from each other, that is, they develop gradually.

The information collected includes the characteristics of the victim. It is essential to know the reasons why this person in question was chosen as a victim; if it was a random decision, whether it belonged to a risk group, etc. In addition, crime scene inspection and related locations also provide valuable profiling information.

Reconstruction of the crime is what clarifies the modus operandi, staging, ritual or personal seal of the criminal, so reconstruction seeks to understand how this happened and analyzes the perpetrator’s interaction with the victim from behavioral analysis. it is linked and elaborated on the basis of multiple theories and research studies in the field of psychology.

The collection of data about the offender is done with special attention and should result in as close a description as possible of the physical appearance and behavior profile, so this is the phase that will allow researchers to obtain more accurate information about the offender.

The entire VERA method is a progressive and cumulative technique in which data, inferences and assumptions can be added, to which all appropriate psychological principles are applied to sufficiently understand the personality and behavior of the aggressor, offender or offender.

The VERA method has proven to be very effective in defining the psychological profiles of offenders; In addition, this method is particularly useful in other areas; it also allows the creation of a statistical database of perpetrators, criminals and criminals classified by criminal and psychological typology. .

It also compares the profile developed with the actual profile of the offender once stopped, which is a very effective tool to improve the definition of future profiles that can be based on those previously developed by data matching, and can be very useful for the future. research projects, as well as to improve ongoing ones.

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