QxBranch delivers predictive analytics solutions with a focus on explainability and transparency
QxBranch brings expertise in data science, machine learning, and visualization, pioneering explainable solutions for the most complex problems.
Maximize Data Potential with Predictive Analytics
From strategy and consulting to scalable data-driven software solutions, we help clients maximize the potential of their data
Assess & Strategize
QxBranch works with businesses beginning the analytics journey and provides guidance on how to make the most of the data they already have through targeted workshops and data strategy consulting, data assessments, and talent strategy
Analyze & Validate
QxBranch works with stakeholders to identify pain points across the business and develops actionable data science hypotheses for investigation through exploratory analysis, proofs of concept, and Analytics as a Service that flexes with business needs
Scale & Deploy
QxBranch combines the art of data science with the rigor of software engineering to develop customized and scalable data science solutions which generate insights and gain efficiencies across the business
Predictive Analytics Solutions
QxBranch offers explainable data science solutions for complex, high-value challenges which enable model validation and improvement, satisfy regulatory requirements, and address algorithm and data bias.
Optimize pricing decisions and uncover insights hidden in market data
Case Study: Consumer Behavior in Response to FX Pricing Fluctuations
A multinational banking and financial services institution sought to maximize foreign exchange (FX) product profitability using predictive analytics to derive competitive pricing strategies based on consumer behavioral patterns, macroeconomic insights, and market trends.
- Disparate data sets required assessment and cleansing to address high levels of missing data and to eliminate data errors
- Complex data wrangling required collaboration between analytics experts and domain specialists to derive methodologies to transform the data while retaining relevant information and data quality
- Utilizing a machine learning clustering algorithm, customers were segmented, and profile types were identified
- Factors driving customer behavior to price fluctuations were determined for actionability
- FX product demand curves were calculated for each customer profile
- A data-driven recommendation system was deployed, providing the optimal pricing and transaction margin for FX products by customer profile type
- The system also assessed the likely impact of changing market conditions and profitability by customer profile type
As Director of Data Analytics for QxBranch, Dr. John Kelly leads a team of engineers shaping the technical goals and direction of data analytics capabilities