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Editorial

How Delta Capita used Python to strengthen a Client’s Sanctions Screening process

In today’s rapidly evolving banking landscape, ensuring compliance with international sanctions regimes is critical to preserving the integrity of the financial system. Currently, we are also witnessing significantly increased operational pressure on our clients’ screening processes due to geopolitical events such as the ongoing conflict in Eastern Europe.

Contributor

Conor is a Chartered Management Institute-certified Project Manager in Data Analytics and BI with demonstrated success in leading and delivering exceptional solutions for clients in the industry.

Conor Lane
Principal Consultant

In today’s rapidly evolving banking landscape, ensuring compliance with international sanctions regimes is critical to preserving the integrity of the financial system. Currently, we are also witnessing significantly increased operational pressure on our clients’ screening processes due to geopolitical events such as the ongoing conflict in Eastern Europe.

Delta Capita has implemented a host of Data and Technology solutions to streamline and automate the sanctions screening process, resulting in faster and more accurate results for our clients. This article focuses, in detail, on how we used Python in conjunction with several low-code tools to build a robust and cost-saving sanctions screening workflow for a Global Investment Bank.

The consequences of negligence

Financial crime sanctions are serious. Offenders can face:

  • Monetary fines,
  • Confiscation of earnings,
  • Restitution,
  • Criminal culpability, and
  • Reputational damage


Cumulatively $13.9 billion was issued in fines by the top 5 offenders in recent years alone.

Data-centric Methods to optimise Sanctions Screening Workflows

Sanctions screening – the process of comparing individuals and companies to government sanction lists – can benefit greatly from effective data analytics and technology tooling. Some of the methods that have been used by our team include:

1. Data Profiling: Effective sanctions screening workflows require data purification before analysis to address data quality concerns such as missing fields, duplicates, and outliers. Python’s Data Profiling Library and YData Profilings extensions give valuable summary statistics and visualisation to understand up-front data distribution and variability

2. Machine Learning: using predictive analytics and advanced algorithms can help to quickly analyse very large data sets and identify potential sanctions violations by spotting transaction patterns with high-risk countries or individuals

3. Intelligent Automation: low-code workflow automation tools such as Alteryx and SAS can help to produce fast and effective automated analytics, from multiple data inputs, to reduce the number of false positive and negative screening alerts and expedite turnaround time 

4. Advanced Analytics: Data manipulation, cleansing and analysis are made easier using extensions such as Python Regex, where regular expressions are employed for pattern matching and data standardisation, or libraries such as NumPy and Pandas for mathematical data normalisation


Our experience with a Tier 1 Investment Bank

One of Delta Capita’s clients approached us to implement a team of data and KYC experts that could strengthen their E2E sanctions screening process. The process flow we built looked like this:

Benefits for our client: 

How can Delta Capita help you?

Our CLM and regulatory centre of excellence, combined with our data and technology expertise place us very well to assist in defining and implementing an improved sanctions screening process for your organisation. Trust us to provide the guidance and support you need to manage your compliance risks effectively and safeguard against financial crime.

To find out more about Delta Capita’s extensive suite of CLM and Data solutions, contact us today.