real - t ime frau d de t e c t i o n
perform. To synthesize, these agents allow multiple tasks to be handled in parallel to enable faster data processing.
The above approach combines the
strengths and synergies of both cloud
computing and machine learning algorithms, providing a small company or even
a startup that is unlikely to have specialized
staff and necessary infrastructure for what
is a computationally intensive approach,
the ability to build a system that make decisions based on historical transactions.
Creating the Analytical Data Set
For the specific use case of fraud
detection for financial transactions, consider the following work that Mu Sigma
did with a client in the financial services
industry. The dat