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At the request of one of the UK's most successful fraud detection system software providers, AIAI undertook an investigation into methods of applying new AI technologies to increase the accuracy of the already highly advanced systems presently in use. While the firm's software presently reduces the number of necessary fraud investigations by several orders of magnitude, our investigation showed that utilising adaptive algorithms and fuzzy logic results in significant diagnostic improvement on the most difficult sub-section of cases.

The goal of the work was to reduce the number of applications referred for costly manual investigation after the existing detection systems had been utilised. It was decided to use Case-Based Reasoning (CBR) for this end, a technique based on the intuition that new problems are often similar to previously encountered problems, and therefore, that past solutions may be of use in the current situation.

The developed CBR system was able to prioritise the referred applications from the most to the least suspicious, aiding the decision process of the fraud investigator.
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