Self-service terminal

Registers – Systems controlled by data bearing records – Banking systems

Reexamination Certificate

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C235S375000, C705S035000

Reexamination Certificate

active

07942315

ABSTRACT:
A method of detecting attempted fraud at a self-service terminal. The method involves providing a classifier having a plurality of input zones, each input zone being adapted to receive data of a different modality. The classifier may be a statistical model. The method also involves mapping inputs from a plurality of sensors in the self-service terminal to respective input zones of the classifier. For each input zone, the classifier independently operates on inputs within that zone to create a weighted set; combines the weighted sets using a dedicated weighting function for each weighted set to produce a composite set; and derives a plurality of class values from the composite set to create a classification result. The classification result can be used to predict the probability of abnormal operation, which may be indicative of fraud.

REFERENCES:
patent: 2005/0255919 (2005-11-01), Nelson
patent: 2006/0169764 (2006-08-01), Ross et al.
Girolami et al., “Hierarchic Bayesian Models for Kernel Learning”, Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, G12 8QQ, UK.
Albert et al., “Bayesian Analysis of Binary and Polychotomous Response Data”, Journal of the American Statistical Association, vol. 88, No. 422 (Jun. 1993), pp. 669-679, http://www.jstor.org, Tue Mar. 20 13:24:16 2007.

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