Best Financial Risk Management Software - Page 10

Compare the Top Financial Risk Management Software as of November 2025 - Page 10

  • 1
    ProfitStars Asset Liability Management
    With ProfitStars Asset Liability ManagementSM – the industry’s leading financial management tool for over 30 years, you’ll get a strategic approach to managing risk by closely integrating your institution’s initiatives with your ALM program. Plus, it’s now part of the hosted Financial Performance Suite. Easily track “what-if” scenarios with strategic monitors that automatically create audit trails, analyze market risk in response to interest rate risk regulatory requirements, determine accurate values for FAS107 reporting, and create detailed, summary, and variance finance and budget reports.
  • 2
    PD-Trak

    PD-Trak

    PD-Trak Solutions

    PD-Trak is an idea, project and portfolio management system that is optimized to manage product development projects using a stage/phase-gate process. It is a highly scalable, cost effective solution for small start-ups and large multi-national corporations. PD-Trak combines the accessibility of a web application with the power and familiarity of Excel, PowerPoint and MS Project (use of MS Office tools optional). PD-Trak Solutions offers consulting and training services related to PPM and stage/phase-gate.
  • 3
    CYBERA

    CYBERA

    CYBERA

    We close gaps that allow cyber criminals to thrive by sharing actionable information in real-time and coordinating a global legal response to support victims of scams and online fraud. It is imperative to raise the cost of conducting cybercrime and increase the risks for cybercriminals. This can only be achieved through effective cooperation, with companies working alongside each other and side by side with law enforcement. Contact us and become a part of our mission to fight cybercrime today. High quality data providing actionable intelligence on money mules, including Wallet Address, IBANs, email and social. Protect customers by improving rules and ML-models with additional insights, reducing false positives, while still preventing fraud.