Faced with increased pressure and greater scrutiny from regulatory bodies, the demands on product control teams are increasing and are showing no signs of stopping. Teams require instant insight into Profit & Loss (P&L) data, the ability to quickly analyse a large number of KPIs, and the foresight to identify mis-matches to ensure the best possible operational decisions are made. It is in these demanding scenarios that in-memory analytics technologies bring significant advantages to the table and enable heightened visibility across the entire supply chain for product controllers.
Three main reasons account for that:
Reason #1: As a result of the financial crisis, the product control function is now under pressure to deliver the official P&L at day+1 notice. The end-to-end validation process easily eats into resource bandwidth given that it is a complex procedure needing to be completed in a very limited time window. In-memory analytics is able to accelerate the task of aggregating massive amounts of heterogeneous data (front-office, risk, and accounting) in such tight time frames. The speed of data aggregation facilitates the P&L reconciliation process, and allows product controllers to spend valuable time on the “P&L explain” process.
Reason #2: “P&L explain” is more important than ever, and is a process which manual set-ups have considerably slowed down in the past. Product controllers now need to be able to rely on a decision-making environment that helps conduct the “P&L explain” process quickly and effectively. In-memory analytics enables personalised outcomes by offering product controllers the freedom to analyse data and KPIs using their own business logic or “what-if” scenarios, with the level of detail that suits them individually. Moreover, this type of technology has the power to generate smarter ‘on the fly’ analysis, as and when it is needed. For example, rule-based mechanisms can trigger automatic alerts to product controllers in the event of a data quality issue, a reconciliation problem or a risk limit breach.
Reason #3: Product controllers need to be able to secure rapid approvals on adjustments. More importantly, officially published and approved P&Ls need to be documented with traceable evidence so that they can be audited for regulatory reporting purposes. The most advanced in-memory analytics solutions can make significant contributions to the P&L sign-off process by enforcing automated workflows within the same analytical environment. This demonstrates a major improvement on traditional spreadsheets as a means to validate P&L adjustments. As a result, reporting times can be shortened and product controllers are better able to meet regulatory demands.
In summary, in-memory analysis has the potential to transform product control from a cumbersome process to a seamless tool that supplies teams with the full information they need, when they need it. This can drastically improve the communication of business performance between product control and the front-office, enhancing the transparency of the bank’s overall P&L and balance sheet. It results in a leaner and more effective organisation, with improved ability to meet stringent regulatory requirements.
