Price disparity analytics – driving revenue uplift
The transaction banking arm of a global Universal Bank, was looking to drive revenue growth by assessing pricing disparity across their cash management client base.
CPRA had to address a data set of over 100 mm rows: but it lead to a €50 mm annualised uplift.
A large, complex data picture
The cash management business had a large global footprint but no single data model to control the numerous products and pricing points, resulting in a highly fragmented billing and charging landscape.
Pricing schedules could be complex with rebates, bundled products, incremental and tiered based prices.
We needed to extract, normalise and merge data from 35+ global billing and charging systems to support the revenue disparity exercise.
In addition, we constructed a robust methodology to link together clients across different locations to ensure a robust client hierarchy was used in the disparity analysis.
Price disparity analysis methodology
Using the normalised transactional records from each of the global billing and charging systems, we re-priced 100m+ transactions to validate the pricing methodologies applied and to identify revenue leakage; this data was then enriched with client and product hierarchies.
Products were identified for analysis and were initially put into volume buckets where appropriate.
For each volume bucket a 50th and 75th percentile price was calculated and fed back to the business in a pricing workshop.
Target prices were determined from the pricing workshop, these new target prices were applied to the historical transactions; having already confirmed the pricing structures we could calculate the new revenue based on the target prices.
Different checks, capping and harmonisation processes were implemented to modulate the uplift.
Outputs were then generated by client for new and old pricing for review by the business.
A highly successful piece of data analytics delivering enhanced divisional profitability
The programme was highly successful generating an uplift of €50m of additional revenue on an annualised basis.
The development of a robust set of capping logic at both the overall client and client-product level resulted in an extremely low level of client attrition.
The use of minimum revenue limits allowed the cash management business to further improve profitability.