Banking & Financial ServicesCapital MarketsBusiness Applications

Reserves Framework Rationalization

Context

In a context of IT transformation and increasing regulatory requirements, a leading investment banking institution launched an initiative to rationalize its reserves framework used by trading activities. The objective is to improve the reliability and transparency of calculation methodologies used for reserves, particularly within Independent Price Verification (IPV) and risk management processes. In this context, Avaliance contributed to the review of quantitative models within the TRO team, in close collaboration with trading, quantitative research, and model validation teams.

Challenges

The client needed to strengthen the reliability and traceability of its reserve calculation methodologies while ensuring compliance with regulatory requirements, particularly SR11-7 related to model governance.

Key challenges included formalizing methodological approaches, improving model transparency, automating calculation processes, and enhancing coordination between Front Office, quantitative research, and model validation teams.

Avaliance Intervention

Achievements

Avaliance contributed to the rationalization and formalization of the reserves framework through several key actions:
  • review of quantitative models (IPV, risk, and reserves) supporting trading activities

  • drafting of conceptual and regulatory documentation compliant with the SR11-7 framework

  • collaboration with trading and quant research on the methodological foundations of pricing models

  • revision of reserve calculation methods using empirical, statistical, or actuarial approaches

  • industrialization of calculation processes using automated Python and Excel tools

Technologies & Frameworks

Python
Excel / VBA
SR11-7
IPV (Independent Price Verification)
Pricing Models
TRO
Capital Markets

Results

Avaliance’s intervention enabled the client to achieve structuring outcomes:
1
improved reliability and transparency of reserve methodologies
2
strengthened alignment with SR11-7 regulatory requirements
3
enhanced traceability of models and calculation assumptions
4
industrialization of calculation processes through Python-based automation
5
improved coordination between trading, quantitative research, and model validation teams
Logo