What do you do if the risk associated with a proposed data and analytics initiative is slightly above the tolerance level determined by your stakeholders?
Sort By:
Oldest
Head of Global Data & AI Center of Excellence in Consumer Goods3 months ago
From our perspective, managing data and analytics initiatives involves a delicate balance between assessing value and mitigating risk. We have a framework that facilitates discussions around these aspects, particularly when transitioning from a decentralized model to a more integrated “hub and spoke” model. This structural shift results in the D&A Centre of Excellence enabling conversations between the functions or teams involved in a particular use case. We rely on risk and value measurements and this committee to deal with those cases where risk is above what we can tolerate.
When considering initiatives where the risk slightly exceeds the predefined tolerance levels, we engage closely with our Chief Risk Officer to evaluate the implications. Our approach includes a data quality management framework where we establish data quality scores and set tolerance levels for data quality. The fact that everyone, from the board all the way down to mid-management level executives, understands the concept of the risk tolerance, ensures that they know what it actually means to be “slightly above the tolerance” and what that could impact. This way, we can make informed decisions and maintain a balance between risk management and the operational needs of the bank.