A method for identifying fraudulent content provider-user device pairs, the method being implemented on at least one computing device having at least one processor, memory, and communications circuitry, and the method comprising: determining an initial user risk value associated with a user device and an initial content provider risk value associated with a content provider, wherein: the initial user risk value is based on a click-through rate, CTR, associated with the user device determined based on user interactions with the content provided by the content provider, and the initial content provider risk value is based on a CTR associated with the content provider and indicative of a number of content items of a total number of content items displayed by the content provider that were clicked; generating a first functional representation of a user risk value based on the initial user risk value and relational data representing a relationship between a plurality of content providers and a plurality of user devices; generating a second functional representation of a content provider risk value based on the initial content provider risk value and the relational data; determining a converged user risk value and a converged content provider risk value associated with the first functional representation and the second functional representation converging, wherein convergence is obtained when a change in each of the first functional representation and the second functional representation from one iteration to a subsequent iteration is less than a convergence threshold value; determining a pair risk value based on the converged user risk value and the converged content provider risk value; and applying a fraudulent label to the content provider and the user device in response to the pair risk value satisfying a condition. determining an initial user risk value associated with a user device and an initial content provider risk value associated with a content provider, wherein: the initial user risk value is based on a click-through rate, CTR, associated with the user device determined based on user interactions with the content provided by the content provider, and the initial content provider risk value is based on a CTR associated with the content provider and indicative of a number of content items of a total number of content items displayed by the content provider that were clicked; generating a first functional representation of a user risk value based on the initial user risk value and relational data representing a relationship between a plurality of content providers and a plurality of user devices; the initial user risk value is based on a click-through rate, CTR, associated with the user device determined based on user interactions with the content provided by the content provider, and the initial content provider risk value is based on a CTR associated with the content provider and indicative of a number of content items of a total number of content items displayed by the content provider that were clicked; generating a first functional representation of a user risk value based on the initial user risk value and relational data representing a relationship between a plurality of content providers and a plurality of user devices; generating a second functional representation of a content provider risk value based on the initial content provider risk value and the relational data; determining a converged user risk value and a converged content provider risk value associated with the first functional representation and the second functional representation converging, wherein convergence is obtained when a change in each of the first functional representation and the second functional representation from one iteration to a subsequent iteration is less than a convergence threshold value; determining a pair risk value based on the converged user risk value and the converged content provider risk value; and applying a fraudulent label to the content provider and the user device in response to the pair risk value satisfying a condition.