A method of automatically auditing a document to determine whether the document is genuine, wherein the method comprises: generating an image of the document to be audited, pre-processing the image to obtain at least one segment of the image with an area of interest, dividing the at least one segment into portions containing single characters and/or combinations of characters, performing a validation of at least two single characters and/or at least two combinations of characters, the validation being carried out for each of the single character and/or character combinations for at least two different categories, creating score values for each category for each validated single character and/or character combination, creating feature vectors for each single character and/or character combination, components of the feature vectors being the score values for the single character and/or character combination for each respective category, classifying the feature vectors to determine whether the single character or character combination to which the feature vector is associated is genuine, wherein the generation of said segments and/or the validation of the single characters and/or the character combinations and/or associated scoring of values for each category and/or the classification of the feature vectors is performed using an artificial neural network, wherein the classification involves a cluster analysis, wherein a single-character cluster analysis is performed for each feature vector associated with a corresponding single character, a multi-character cluster analysis is performed for feature vectors (171 to 175, 191 to 193) associated with a plurality of characters, and a document-wide cluster analysis is performed for all feature vectors associated with the characters of the document, wherein the single-character cluster analysis comprises obtaining a similarity indication between at least two feature vectors associated with single characters, wherein, when the similarity indication obtained violates a defined threshold, the single character associated with the corresponding dissimilar feature vector is considered to be non-genuine; and wherein the multi-character cluster analysis comprises obtaining a similarity indication between at least two feature vectors (171 to 175, 191 to 193) associated with a combination of characters, wherein, when the similarity indication obtained violates a defined threshold, the plurality of characters associated with the corresponding dissimilar feature vector are considered to be non-genuine, wherein the document-wide cluster analysis comprises obtaining a similarity indication between a feature vector associated with a single character or a combination of characters, and an aggregated mean feature vector associated with all characters in the entire document, wherein, when the similarity indication obtained violates a defined threshold, the single character associated with the corresponding dissimilar feature vector is considered to be non-genuine. generating an image of the document to be audited, pre-processing the image to obtain at least one segment of the image with an area of interest, dividing the at least one segment into portions containing single characters and/or combinations of characters, performing a validation of at least two single characters and/or at least two combinations of characters, the validation being carried out for each of the single character and/or character combinations for at least two different categories, creating score values for each category for each validated single character and/or character combination, creating feature vectors for each single character and/or character combination, components of the feature vectors being the score values for the single character and/or character combination for each respective category, classifying the feature vectors to determine whether the single character or character combination to which the feature vector is associated is genuine, wherein the multi-character cluster analysis comprises obtaining a similarity indication between at least two feature vectors (171 to 175, 191 to 193) associated with a combination of characters, wherein, when the similarity indication obtained violates a defined threshold, the plurality of characters associated with the corresponding dissimilar feature vector are considered to be non-genuine,