A skilled ring of international fraudsters has been submitting false unemployment claims for individuals that still have steady work.
But where historical rules-based systems fail,artificial intelligencetrained on high-quality data excels.
It’s free, every week, in your inbox.
Wells Fargo will never ask for your personal information in an email.
Did you notice that Wells Fargo was spelled with: one lowercase L and one uppercase i?
Or worse, the attacker can clean your accounts in one motion before you realize whats happened.
The analysis of time series data can be used for anomaly detection.
It works by comparing the consumers transactions with their own recent transaction history.
If the probability of suspicious activity is above a certain threshold, it alerts human users of the danger.
Alternatively, for very high probabilities, it might block transactions automatically.
For example, you may have a history of spending $30 per week at restaurants.
To make these models effective, high-quality training data is essential.
Training data is used to teach the model how to classify transactions as anomalies.
Subject matter experts help the computer learn by manually identifying suspicious activity.
The machine then uses the complex knowledge it learned from the training data to make predictions about novel data.
The trouble is that attackers are constantly innovating with new techniques that throw off the computers.
A different kind of anomaly detection called unsupervised outlier detection helps us to root out emerging patterns of abuse.
Consider a drug trafficking organization that regularly executes cash sales in excess of $1M.
If they were to deposit the money directly, the transaction would be detected and blocked.
This technique is an example of money laundering.
This emerging discipline is calledexplainable AI (XAI).
Lets return to our example of going out to restaurants.
As we collect more and more information about how users behave, the power of AI burgeons.
The more data at our disposal, the more accurately we can scrutinize suspicious behavior.
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