A European retail bank approached Acin in 2021, asking if we had any technology that could help them better understand their Operational Risk environment. They had spent over a year searching for ways to accelerate their way through tens of thousands of individual controls from their Investment Bank and their Retail branch network spanning 15 European and APAC regions. 

The expanse of data and its associated complexity resulted from several global risk frameworks, an ever-increasing volume of regional policies and standards, and an explosion of non-standard controls that had become costly to manage, inefficient and ineffective. 

The primary objective of their transformation program was to connect up process-to-risks-to-controls, but first, they had to figure out what all the important data was. They knew they had a lot of duplicate Control Objectives throughout the Control environment and a lot of duplication and proliferation amongst the Controls themselves. The total amount of process-procedure-control-risk connections they calculated that had to be analyzed exceeded several tens of thousands of rows of data; very difficult to do without some sort of AI capability or industrialized process.  

After a fruitless 12-month search, this bank could not find suitable technology that could be trained to understand their risk control landscape quickly, nor could they find a consultancy with the skills to achieve their analysis objectives fast enough and to a reasonable budget.

After agreeing on the scope, Acin ingested the data from a number of countries and processed it through our AI engine. Our Op Risk data processing capability is a combination of NLP and ML technologies that have been trained on over 400,000 rows of data from 20 global firms over the last few years. Every data refresh also goes through a comprehensive review process by our SME team to ensure accuracy. Final results are then assessed by the client firm’s SME’s from respective divisions and offices; Markets, Corporate Finance, Asset Management, Retail, Wealth or Front, Middle, Back or KYC, Credit, Loans etc.

After just a few weeks, Acin returned a preliminary set of results to the client, providing highly valuable insights into the data quality and precise levels of CO duplication and Control duplication and proliferation. 

Following a review of the results, we concluded the opportunity for compression was: 

  • >75% for Control Objectives 
  • >65% for Controls 

Solving some of the bank’s complex data challenges was the first phase of its strategy to prioritize changes that allowed it to improve operational risk management continuously.  

Both parties are now working with 3rd party consulting companies to agree and curate the recommended changes throughout the bank. Benefits to the bank are estimated at:   

  • Several FTE savings p.a. 
  • Removal of a management overhead associated with hundreds of unnecessary controls 
  • 4M Euro savings over 3 years (based on an annual ‘cost per Control’ of Euro 1,500 
  • Acceleration of the overarching transformation project because the control review process was enabled and accelerated by a partner with the right combination of technology and OpRisk skills.  

What next 

If you’re interested in how all this works to further reduce residual risk or remediate faster, please reach out to our practitioner teams in the US or Europe, or myself directly.

Kieron Sambrook-Smith, CRO, Acin 

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