Digital finance and trading platforms face significant challenges in maintaining user trust while preventing fraud, as any lapse can lead to severe financial and reputational consequences. Fraud and risk teams must balance stringent security measures with the need for seamless user experiences, especially as platforms expand into areas like cryptocurrency and tokenized assets. Effective fraud prevention relies on tools like data processing, statistical analysis, risk scoring, and graph modeling, but these tools are only as effective as the quality of data they process. Device intelligence, providing real-time and accurate data, is crucial for enhancing the fidelity of fraud detection systems without impacting user experience. By integrating precise signals such as IP geolocation and login velocity, platforms can improve their ability to identify and prevent fraud, thereby safeguarding both users and business interests.