Financial services firms all around the world are struggling to keep up with evolving, increasingly complex Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations. Since the 2008 crisis, firms have been hit with $36 billion in KYC, AML, or sanction related fines, with penalties in 2019 increasing by more than 160% compared to 2018. This led a tier one global investment and corporate bank to reach out to Capco for help in reducing the cost of KYC and providing a better customer experience. 

Capco's blend of industry expertise, KYC and regulatory knowledge coupled with strong analytics & data capabilities to build smarter solutions in client lifecycle management/operations stood out to the client. Using our multi-disciplinary teams, we drive greater effectiveness and provide deeper insights which can be tailored to a firm’s strategic business priorities. 


As well as the pressure of tight regulatory deadlines, a big challenge was data governance and quality. The bank’s data was housed in silos across different business departments, controlled by different stakeholders and had several quality issues. 

Capco was tasked with:  

  • Understanding the root causes driving up time and driving down accuracy of KYC processing  
  • Understanding the most effective areas to introduce automation to reduce manual workloads 
  • Optimizing manually intensive processes within client lifecycle management (CLM), such as client offboarding  
  • Predicting the probability of a client being offboarded or quarantined mid-KYC cycle and avoid associated KYC costs 
  • Reducing costs and avoiding future cost wastage. 


To meet this challenge, we assembled a team of three data scientists, one data analyst, a CLM & KYC expert and a process analyst. Combined, the team had a wealth of industry experience and technical skills in data wrangling, feature engineering, process mapping and Machine Learning, using tools such as Python and Celonis.  

The team did the following:   

Conducted exploratory data analysis on all the relevant datasets to understand how the data was structured and uncover relationships between the datasets 

Cleaned, aggregated and joined together these datasets to create a single, enriched dataset which included details such as complexity of files, fungibility between locations and processing time and quality scores for different KYC teams as well as business variables such as cost to automate per location / system, ability to hire or relocate FTEs to regions and working hours per location  

Build models to explore different business outcomes:  

  • Root cause analysis – built regression models to explore the underlying reasons behind varying KYC processing times & the inaccuracies in the KYC files  
  • Simulation Analysis - used simulation algorithms to provide a real-time view of each task's progress and the utilisation of FTEs and RPA bots on a day-by-day level to process KYC and Offboarding tasks  
  • Quarantine/Offboarding Prediction – build prediction algorithms to forecast which clients were at high risk of being quarantined or offboarded; these clients were deprioritized from the KYC process to reduce cost wastage.  


A senior MD at the client commented, had been ‘a real gamechanger’, helping them to achieve the following the business benefits:

  • Cost avoidances of £10+ million by accurately predicting which clients will be quarantined or offboarded
  • Key areas for automation across KYC and offboarding processes were identified; led to reduction of processing times by 15 percent
  • Outputs from the offboarding prediction models being used to forecast the capacity required to complete KYC / offboarding tasks and maintain daily monitoring and control against the execution of these processes. 

Today, the increased efficiency, transparent capacity modelling and effective introduction of automation has enabled the bank to be more aligned to regulatory KYC requirements. The bank also remarked that the models have proven ‘invaluable’ and were ‘executed brilliantly by Capco’.