Hyperspectral analysis is employed in many different areas, such as medicine, environmental studies, security and forensics. Focusing on law enforcement, ink discrimination has become an important factor for the detection of fraudulent documents. This paper proposes an approach for ink analysis in handwritten documents and pen verification using hyperspectral analysis and Least Square SVM classification. The proposed method obtains immediate results in a non-contact way from the document or test sample. The first step is to determine the best possible lighting conditions. Then a detailed study is made of components and properties of the ink and pens used. This paper proposes a classification method based on the hyperspectral characteristics of the ink derived from its physical properties. Furthermore, a database of hyperspectral curves of several types of inks is made, which is used to obtain the characteristics of different inks. The proposed method for automated ink type identification is tested using 25 different pens and more than 1000 samples. The achieved discrimination between types of ink was 87.5%. The experimental protocol includes three different scenarios.