Restricted List Discovery & Data Design

Executive Summary

How to cleanse a messy data set, captured manually for years in Excel and critical to the ongoing compliance and profitability of the business?

An alternative asset management firm had significant data quality issues relating to the tracking of signed NDAs & restricted entities, holding master data in Excel. A 6-week collaboration with psKINETIC provided an initial cleanse of the data, development of a POC application and To Be solution overview, as well as providing the client with an ongoing approach to cleanse and collect better data in the interim until a full solution can go live.

About the Client

The Client was founded in 2009 with the ambition of creating one of Europe’s leading investment platforms. We focus on delivering best-in-class risk-adjusted returns for our investors across our strategies: Direct Lending, Special Opportunities and High-Yield Credit.”

The Challenges

The age-old problem of starting to track a business process in a simple Excel sheet, soon results in a business-critical function relying on an unwieldy, complicated spreadsheet with patchy or unreliable data.

This is a common challenge across the industry, with a data collection approach that was poorly defined initially which has led to an inefficient and perhaps risky area of the business.

In this case, the data regards the tracking of signed NDAs and what non-public information is held by the firm, restricting activities against that entity for other areas of the business. The tracking document therefore has the tricky balancing act of providing accurate information to ensure regulatory compliance, while also trying to be as up to date as possible and not restrict teams unnecessarily, reducing income opportunity for the business.

The Solution

The initial engagement with psKINETIC was a 6-week project to understand the problem, provide a data cleanse roadmap and outline an MVP solution that would enable the team to easily maintain a more structured and reliable data set going forward.

SME workshops and interviews with key stakeholders were used to dig into the issues in the data & processes. In parallel, detailed analysis and automated cleansing of the dataset took place. Through these activities, a new data model was defined that correctly mapped the complex relationships between restricted entities & NDAs.  

This rolled into the development of a POC application to start testing the cleansed data model against their use cases and uncover further requirements. The project concluded with the issue of a To Be solution overview and 7-week plan to Go Live, as well as updates to the original excel tracker (using the new data structure and cleansed data) which would improve their data across the interim period and allow for a quick import of the data to the application at Go Live.


Providing with a new tracker to structure new data in the interim, will now improve their data day-to-day rather than make it worse. With 200 NDAs being signed each month, the interim solution became a priority to ensure new data was collected in a better way until a solution is live. A cut off was therefore created, ensuring the scale of the data required to be cleansed was no longer increasing.

As part of the cleansing of the existing data, 45% of the ~5000 NDAs previously treated as ‘Active’ restrictions were identified as expired. This and various other ongoing cleansing tasks will now steadily reduce the remaining data required to be reviewed, safe in the knowledge that new data collected will be better structured when collected going forward.

A solution will now be built store this data permanently and manage the workflow in a controlled and consistent way. The MVP defined will be delivered in 7 weeks, aiming to quickly pull together the required functionality to manage the list in a database using an app.

Further features will then be defined and implemented, for example, reporting opportunities will open up as more and more structured data is collected, as well as the opportunity to get a wider user base to provide input at the right points in the workflow to reduce manual burden on a central admin team.