Data-driven management of audit and internal control

Increase the efficiency of control management with consolidated real-time indicators

Firms need to strike a balance between the increasing impact of regulatory and reporting responsibilities and allocation of resources. Audit and internal control functions are faced with the challenge of creating operational efficiencies – especially considering the exponential increase in the cost of non-compliance.

Advanced analytics, machine learning and RPA provide the technological agility to take over tedious and repetitive tasks and direct your team’s resources towards process control or the highest risk entities. But how do you scale up these techniques? How do you utilize them as a day-to-day working tool if data are hard to access, dispersed between multiple sources and often poor quality?

The Scaled Risk data automation platform streamlines this all-important data management function, which often makes up 80% of the workload for a data analysis project. Our platform features an automated recovery process for dispersed information (customer and counterparty characteristics, transactions, completeness and KYC document update timing). It addresses data quality and consolidates the information in a constantly updated, standardised view that teams can access using a simple search engine.

In the banking world, having granular information on customers and counterparties at your fingertips (most recent update of KYC documents, completeness, income thresholds, etc.) is vital to easily calculate an overall compliance score by subsidiary, branch or agency and segment the score by field (AML compliance, tax compliance, credit risk). Internal control managers can swiftly identify the highest-risk entities and/or areas and introduce the appropriate remedial actions.