Public organizations rely on pre-determined assumptions from
past experiences to identify suspicious indicators and assess
potential risks. For example, customs authorities need to decide
which containers or commodities ought to be examined, while tax
authorities need to determine which individuals and companies
require auditing.
To cost-effectively overcome these challenges, organizations need
to harness machine learning algorithms which can be trained to
alert users of risky events and conditions.
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Decision intelligence