Proven Results - Quantitative Intelligence

---

These stories show how cipris embeds AI-first quant intelligence into organisations—creating reusable infrastructure, shared libraries, and governance frameworks that scale and deliver competitive advantage(*).

What the client needed:
A FinTech startup needed a full quantitative pricing library, governance & documentation, and model risk framework from scratch so it could compete in sophisticated derivatives markets.

What we did:
We delivered an AI-first quantitative intelligence ecosystem including vanilla, barrier, binary & FlexStrip options pricers; dual-curve yield modelling with LIBOR/RFR transitions; implied volatility models with outlier detection; arbitrage-free volatility curves for commodity markets; full testing suites and robust documentation; and a model risk rating framework. We also provided strategic quantitative advice and roadmap.

What the client gained:

• Immediate move-in with institutional-grade quant infrastructure
• Repository of reusable models supporting multiple product types
• Governance, documentation and validation built into every component
• Credibility to enter markets with regulatory confidence

What the client needed:
A risk team lacked shared tools and reusable components, which led to slow development, inconsistent methodologies, and duplicated effort.

What we did:
We built a shared VBA knowledge-library (XLA) of quantitative components, standardised methodologies, and reusable solutions. This enabled greater reuse among team members and consistency across risk/model work.

What the client gained:

• Quicker development cycles and reduced duplication
• Consistent methods across the team, reducing error risk
• Embedded quant capability that scales with business load

(*) Some results are based on the founder's extensive experience at top-tier financial institutions.