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Financial Analysis

Revenue Management for Network Pricing

Context

A large company with over USD 200 million annual revenues had a dispersion problem: equivalent merchants and types of subnetworks were priced very differently. 


It was not only about pricing though: they didn’t have a quoting internal process either.

Method

Exploratory Descriptive Analysis followed by Machine Learning, we sought which variables were determinants of the undesired dispersion. With this formally set, it was possible to engineer a quantitative structure for their clients’ rentability, followed by adjustments by the company.


A quoting app was designed by Finor, followed by a simulations one, resolving many previously important flaws.

Benefits Achieved

• Effective control over their client's portfolio, 
• Formal key processes governance established with useful apps for the team,
• Added USD 100k monthly recurrent revenue.

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