According to a recent study done in 2021, 90% of financial institutions (FIs) say that they are under pressure to utilise analytics and data-driven capabilities as they have realised that data-driven decision-making is key to the business. However, fewer than half of FIs are able to base their decisions on their data.
On top of that, similar to the Hong Kong Monetary Authority’s (HKMA) Supervision for Bank Culture1, the Individual Accountability and Conduct (IAC) guidelines2 rolled out by the Monetary Authority of Singapore (MAS) became effective on September 2021. The guidelines aim to increase the level of accountability of senior managers and advocated policies and processes at FIs to embed risk ownership at all levels of the organisation.
FIs are required to achieve the five outcomes shown in Figure 1 regarding senior managers, material risk personnel and all employees. This creates additional stress in addition to the complex labyrinth of regulations that FIs must satisfy. In particular, outcome 4 – Strengthening Oversight – calls for FIs to establish a stronger corporate governance backed up by an effective internal control framework with the ability to identify key risk exposures across risk taxonomies.
In the course of achieving a reasonable level of oversight, FIs find themselves facing several challenges. These challenges include a lack of:
FIs are now able to adopt an effective risk supervision framework thanks to:
However, the adoption of such frameworks is not an easy journey for FIs, as it requires a combination of business and data knowledge. In response to such problems, Synpulse has defined the Synpulse Risk Supervisory Framework, or SRS Framework, to facilitate appropriate supervision over all key risk indicators within the bank.
The SRS Framework comprises two key building blocks:
FIs are in possession of massive amounts of valuable risk-related data, but more often than not they are not able to fully realise the potential owing to the absence of an appropriate risk supervisory framework. The SRS Framework enables FIs to perform data-driven decision-making and essentially allows a paradigm shift in an FI’s operating model with respect to risk-related topics.
We understand that the implementation journey may not be that straightforward. Other challenges include the big data conundrum, where the “garbage in, garbage out” effect may end up harming FIs because it not only provides irrelevant and inaccurate information, but can also lead to wrong decision-making. Synpulse has been through these and have learnt to “boil the ocean” in iterations. With good quality data, it will take FIs from data collection to delivering business value.
In the next installment of the SRS Framework articles, we will cover the second key building block of SRS, the Risk Insights Dashboard. We’ll be elaborating how the solution helps with identification of risk concentration within the organisation and demonstrates the overall level of an FI’s risk exposure across various risk taxonomies.