Number of Seats/Users: ModelRisk offers discounts based on the number of users or seats. A higher volume typically leads to a better discount structure, especially for enterprise-level usage.

Commitment to a Long-Term Contract: Discounts are often provided to companies that commit to using the service for a longer period (e.g., 1-year or 3-year contracts). A longer commitment shows ModelRisk that the company is serious and willing to invest in the platform long-term.

No Active Discounts: Companies that are not already receiving other active discounts may have a better chance of qualifying for additional discounts from ModelRisk. ModelRisk reserves discounts for new customers or those not currently under promotional pricing.

Volume or Usage Commitment: ModelRisk offers discounts if you agree to a minimum amount of usage or transaction volume. This could be based on data storage, transactions, or other metrics tied to how much you will use the platform.

Enterprise-Level Negotiation: Companies that qualify as “enterprise” due to their size or complexity (e.g., having large teams, multiple departments, or geographical presence) may be eligible for additional discounts from ModelRisk. Such companies are often in a position to negotiate for better pricing.

Early Renewal or Prepayment: ModelRisk often offers discounts if you renew early or prepay for the entire contract period. This is a common approach to securing a lower price.

Here at Spendbase our internal data shows that ModelRisk is seen as a powerful, specialist tool that delivers strong value for quantitative teams, but it comes with some usability and environment caveats you’ll want to factor into budgeting and negotiation.

Key strengths our Spendbase clients highlight:

• Seamless Excel integration
• Excel add‑in works well with existing models.

• No heavy coding needed for Monte Carlo simulations.

• Strong analytics and modeling depth

• Wide range of probability distributions.
• Automated distribution fitting saves expert time.
• Advanced features like copulas for correlation and aggregation are appreciated by insurers and financial teams.

• Works well for:

  • Weather derivatives
  • DCF and valuation work
  • Actuarial experience analysis
  • Project and capital risk analysis

• Reporting and visualization

• Clear input/output PDFs, tornado, spider, and scatter plots.

• Built‑in reporting and export functions support stakeholder communication.

• Support quality

• When support engages, it is described as highly knowledgeable and helpful.

Key pain points that impact cost and adoption:

• Learning curve and usability
• Interface assumes familiarity with objects/functions and basic programming concepts.

• Some clients wish for more user‑friendly utilities (e.g., interpolation, numerical differentiation, easier PERT fitting).

• Stability and bugs

• Occasional lock‑ups, sometimes blamed on heavy Excel/plugin setups.

• Known issues around copula reporting tools.

• Platform and workflow friction

• No native Mac support; Mac users must run a Windows VM, adding indirect cost.
• Function prefixing (typing “Vose” each time) is a minor but frequent annoyance.

How we typically advise clients on discounts and optimization:

• Use the advanced feature set as leverage: your teams clearly use the deep statistical toolkit, so volume and long‑term commitments should be negotiated against roadmap items (e.g., Mac support, bug fixes, UX improvements).
• Budget for training: the learning curve justifies asking for bundled training, extra documentation, or extended onboarding at no additional cost.
• Consider environment costs: if part of your team is on Mac, we flag VM overhead as a reason to seek stronger commercial terms or additional support coverage.