Use Case  

A global financial index and benchmark provider needed to automate a control to validate and report accuracy checks for each index, benchmarking calculation, and constituent data. The goal was to ensure completeness, timeliness, and accuracy of the data being disseminated to financial subscribers.   

CrossCountry Consulting was engaged to implement a solution to automate the validation, reconciliation, and reporting of index data. Additionally, CrossCountry was tasked with scaling this process for all index-related data to be automatically performed twice a day for 400+ indexes and millions of data points. 

Scaling the automation would replace the manual processes of the operations team who traditionally: 

  • Performed routine manual exports of benchmark data from various data sources to generate reports.   
  • Performed reconciliation and matching to ensure calculations and data dissemination were accurate. 
  • Created and published daily reports for validation. 

Automating these tasks enabled the company to optimize its back office with reduced overhead.  

Our Approach  

CrossCountry worked in collaboration with stakeholders from risk management and index operations to assess all relevant processes in detail, including pain points and data quality challenges. 

Once aware of the full scope of problems, our team of automation experts designed a process and created an easy-to-use front-end application enabling end users to automatically export, transform, and generate reports as needed in real time. 

Our Impact  

CrossCountry’s impact was multi-dimensional and led to additional windfalls throughout the business in the form of: 

  • Increased speed and accuracy of data validation and reconciliation. 
  • Improved data quality and processing consistency across the RCM and purchasing function. 
  • Reduced time required to produce evidence of control as required to meet industry standards.   
  • Condensed time to prepare controls and evidence of controls from 6 hours a day to 5 minutes. 
  • Added transparency, auditability, and accessibility.  
  • Focused investigation of the root causes of data discrepancies versus manual preparation of data.