In this article, methods for user recognition by online handwriting are experimentally analyzed using a combination of demographic data of users in relation to their handwriting habits. Online handwriting as a biometric method is characterized by having high variations of characteristics that influences the reliance and security of this method. These variations have not been researched in detail so far. Especially in cross-cultural application it is urgent to reveal the impact of personal background to security aspects in biometrics. Metadata represent the background of writers, by introducing cultural, biological and conditional (changing) aspects like fist language, country of origin, gender, handedness, experiences the influence handwriting and language skills. The goal is the revelation of intercultural impacts on handwriting in order to achieve higher security in biometrical systems. In our experiments, in order to achieve a relatively high coverage, 48 different handwriting tasks have been accomplished by 47 users from three countries (Germany, India and Italy) have been investigated with respect to the relations of metadata and biometric recognition performance. For this purpose, hypotheses have been formulated and have been evaluated using the measurement of well-known recognition error rates from biometrics. The evaluation addressed both: system reliance and security threads by skilled forgeries. For the later purpose, a novel forgery type is introduced, which applies the personal metadata to security aspects and includes new methods of security tests. Finally in our paper, we formulate recommendations for specific user groups and handwriting samples.