Most banks have a great vision of what they’d like to achieve in terms of digital risk management, but achieving this goal can appear daunting.
New Year, new you! That’s the seasonal promise of every January gym advert. Many of us set ourselves personal goals at this time of year - I can’t be the only one planning to work a bit harder on my fitness after the Christmas break.
What’s true for me is also true for our banking institutions. As I wrote in November, banks find themselves struggling with an unhealthy combination of customer expectations, investor demands, technological disruption and growing regulation.
So as they start the New Year, many bank boards are planning to turn over a new leaf and build the lean, muscular organisation they’ve always dreamed about. In the risk management arena, this often means setting a goal of achieving a complete digital risk transformation.
Most banks have a great vision of what they’d like to achieve in terms of digital risk management, but achieving this goal can appear daunting. Practical obstacles in areas such as data quality, analytic capabilities, innovation and change management are often significant. This means that while banks may be able to adapt their existing approach, most feel unable to execute the sort of transformation that’s required to achieve their vision.
The good news is that banks can ‘eat the elephant one bite a time’. Achieving a digital risk management transformation typically requires taking a number of key steps. These are likely to include setting a clear risk strategy, developing analytic tools, nurturing innovative talent and partnering with suppliers – or even rivals. And in my experience, effective data governance is often the best place to start.
There are several reasons why data governance is a good starting point. The most obvious is that good data is a pre-requisite for good risk management, especially if banks are to harness the growing power of data analytics. Like most businesses, banks suffer from fragmented and unreliable in-house data. It’s essential to iron out inconsistencies in the quality and accessibility of existing data before supplementing it with alternative data from external providers.
In my view, the key to good data quality is to view data as an asset, and manage it accordingly. Which data items are valuable and which are not? That can be a difficult question to answer. Some data is vital for compliance; some for analysis; and some may not be needed at all. Furthermore, this assessment may change at every stage of the client lifecycle.
Another reason to view to data as an asset is to make sure it doesn’t become a liability. The arrival of MiFID II and the approach of GDPR are a compelling reminder that datasets and data models can not only create value, but also create risks. With this in mind, we are starting to see some banks set themselves data risk appetites for the first time.
To be clear, effective data governance is only one step towards transforming digital risk management. But, as with any New Year resolution, that crucial first step is often the most important! Getting started and achieving some quick wins can boost confidence, skills and experience. Just as importantly, it can help to change culture and put the remaining challenges into perspective.