Price Analytics


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.



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.).



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.



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)



The client managed to remove business risk by improving audit and compliance.

Customer relationships – the client managed to correctly and appropriately price clients.