Understanding Psychographics and Demographics in AML
The fight against financial crime is unrelenting. At the forefront are the AML officers trying to understand transactions and an identity in a confused picture of never ending data. Understanding Psychographics and Demographics in AML may just be part of the answer. Read on to find out how these two disciplines can assist in the fight against international Organised Crime Groups (OCGs).
Most people have a grasp of demographics. The basic categorisation of individuals around gender, age, ethnicity etc. Demographics have been used by marketers, social scientists and governments for the last few centuries.
However, use of Psychographics is a relatively new concept. It is the study and classification of people according to their attitudes, aspirations, and other psychological criteria, especially in market research.
In this post I will outline why using psychographics to classify people is important to AML. How it can aid the battle to control the illegal flow of money into the financial system and how it can help with risk based decision making.
There is a significant library of study into the classification of people, mostly along personality traits. The most renowned is the OCEAN model.
- Openness to Closed personality
- Conscientiousness to Careless
- Extrovert to Introvert
- Agreeableness to Obtuse
- Neurotic to Secure.
In one study it was found that psychopathy is distinctively different from criminality in that, “the majority of psychopaths are not criminal, and the majority of criminals are not psychopaths.”
The study of an individuals personality to align characteristics that make a person more likely to commit crime are plentiful. Psychologists broadly agree people can be classified as likely to commit crime by understanding their personality.
The personality develops from a very young age and scientists have found studying personality in the young can frequently identify those more likely to commit crimes later in life.
There is also evidence to show recidivist criminals display personality traits that coalesce around specific categories to indicate at release from prison, if the person is likely to be drawn back into a life of crime again.
Of course personality develops as a person ages, from child to adult. Influences from an early age like, background, economic wellbeing, health, parental skills and external human relationships will all teach a child what is socially acceptable and ‘right’ versus wrong. Scientists have shown children suffering adverse influences have smaller brains than the average child as young as two years old. This is the result of hormonal fluids damaging the neuron pathways being developed in the brain; brought on by stress and viewing/experiencing acts of violence for example.
So the argument of born or raised as a criminal isn’t really a debate, a child’s external environment as well as its capacity to learn will impact the relative chances of success the child will secure later in life. Of course for those left behind a life of crime might be learned behavior from bad influences or simply a necessity to survive.
This is all general in nature with studies showing normal distribution of results with outliers in both directions; as one would expect.
Behaviour is largely a result of how a person thinks and perceives. The personality is what ‘makes’ a person who they are. Both are dynamic but will group around certain beliefs and morals the person has. So the most placid person can become enraged but will ultimately revert to type.
Once criminal behavior becomes a ‘norm’ it will be very difficult for a person to break the cycle. Reduced chances from an intolerant society make it more difficult to rehabilitate, even if the criminal wanted to. The matrix of risk to reward will influence behavior causing repeated criminality and a learned attitude towards others. This causes repeat offending.
But how is this relevant to Anti-Money Laundering and financial crime in general?
The AML Psychographic Risk Model
It is said that just on Facebook a regular user has over 7000 individual data points about them and their life. It plainly cannot be ignored when an individual who can be identified adds a video to youtube showing acts of criminality or terrorism; yet this data isn’t picked up and processed as intelligence for the AML fight.
- Usual demographics
- Economic status
- Employment status
- Places of resort
- Family status
- and on and on.
The data from other reference points held online about each and every one of us is enough for data scientists and psychologists to accurately model the average financial criminal. It is but one step further to then model that to individuals as they present as customers of financial institutes.
Clearly, using psychographics to identify ‘groups’ to target marketing messages to is widely accepted as a good way to do business. Using it to identify who is likely to commit crime less so. This is because the normal distribution will detail a group coalescing around the right personality traits to become a criminal. What it won’t do is indicate conclusively that a specific individual is a criminal even if they are within the coalesced group.
However, data such as this has been used to win elections, fight propaganda wars in Afghanistan and Iraq and accurately predict marketing trends globally. It is churlish to rule out its applicability to identifying groups that may present more of a risk to the financial industry to allow specific measures to be taken when managing business within that group. This isn’t far removed from understanding the risk jurisdictions present and having policies and processes in place to do business within those jurisdictions. Clearly, not everyone in Afghanistan is a criminal, yet when we do business with an entity from that jurisdiction, restrictions will be in place to ensure compliance with the risk based approach and regulations.
Psychographics will simply make those decisions more informed in a scientific way. Not based on a border but on social psychological science.
CYW Solutions are building an intelligence system that will use;
- Psychographic data;
- Jurisdiction risk;
- Entity data (company/individual);
- Internal and external criminal data;
- Transaction data;
- Adverse media;
- Dark Web data;
- Authority data; and
- Undercover operational data.
We will be using this to build a more informed picture of who it is you are about to do business with, the risk they present and how you can mitigate that risk.
It’s quite simply better business.
You can join our journey to understanding psychographics and demographics in AML by talking to us.