Price Analytics

Introduction

Price Analytics at a Tier 1 Investment Bank client was seen as a “no-go” area due to a distributed and complex IT architecture, with a lack of tractability and the dropping of price information with the data flow from the front office. Pomerol introduced Lavastorm as the ETL tool and managed to quickly re-engineer pricing logic for a number of systems.

Challenges

• Obtaining Greater Transparency.
• Pricing systems containing disparate data.
• Poor front end reporting regarding pricing plans.
• No analytics for the different buckets of clients that should be priced in a similar way (according to Notional, Trade Count, Currency Pair Types etc.).

Solutions

• A series of data models were produced to harmonize price structures across the “spot” and “Forward” products.
• Created script to map price plan files against the existing trade set for audit / compliance checking.
• Developed an analytical application to enable optimal client pricing.

Benefits

• Compliance benefits – business assurance that clients are priced according to agreed parameters.
• Price Optimization – identification of incorrectly priced clients, and the selection of the appropriate price plan according to a number of parameters (size, trade count, notional volume, currency pair activity)

Impacts

• The client managed to remove business risk by improving audit and compliance.
• Customer relationships – the client managed to correctly and appropriately price clients.