The strategic partnership enables local delivery of Numerix’s broad portfolio across pricing, valuation, market risk, and balance sheet use cases, supported by PiP LatAm’s regional expertise.
Feb 5— Numerix, a leading capital markets quantitative analytics technology provider, announces an expanded partnership with Proveedor Integral de Precios (PiP LatAm), the leading independent price provider in Latin America, to deliver Numerix solutions to institutions across Spanish-speaking Latin America.
The expanded partnership establishes PiP LatAm as a strategic regional delivery and go-to-market partner for Numerix across Spanish-speaking Latin America, combining Numerix’s analytics with PiP LatAm’s local market knowledge and in-region support. Building on strong demand for counterparty credit risk and xVA, the expanded alliance reflects growing adoption of Numerix analytics across a wider range of pricing, valuation, and risk management use cases.
Through this model, banks, broker-dealers, insurance companies, and asset managers can access a broader range of Numerix capabilities, spanning pricing, valuation, market risk, and balance sheet risk management, delivered locally through PiP LatAm. Building on prior collaboration, Numerix previously supported PiP’s transition from an enterprise deployment to a SaaS-based valuation platform for xVA, improving scalability and operational efficiency.
Underpinning this model, Numerix solutions can operate as a core analytics engine within an institution’s existing technology ecosystem, integrating with third-party trading, risk, treasury, and data platforms to generate consistent pricing and risk analytics. These analytics can be consumed by downstream systems, including systems of record, enabling firms to scale analytics capabilities while preserving established workflows and technology investments.
The partnership allows customers to benefit from faster implementation, support aligned with regional regulatory requirements, and scalable analytics workflows across trading, risk, and treasury, enabling a shift away from fragmented or manual processes toward more centralized, analytics-driven environments.
