By Ian Quine, Alpha Insight
There can be nobody in the banking or finance sector who fails to recognise that organisations cannot continue to work in silos. Siloed working is the enemy everyone wants to defeat.
Indeed, having IT systems that were formed in an era of strongly defined – and defended – internal boundaries is now universally recognised to be deleterious to any organisation.
Unfortunately, in banking, it is still hard to overcome. Not only are banks highly compartmentalised but all such institutions have built up diverse systems over time in response to specific events or challenges such as mergers or the emergence of new markets. In this context the imperative to become truly data-driven is difficult to fulfil.
The division into silos cuts right across institutions. It could cover the different software that is in use, such as different business applications with the same functionality. The separation could equally be into business silos with staff in one looking at intelligence relating to specific challenges such as MiFID II or BCBS 239 compliance, while others examine the smooth and efficient functioning of payments processes.
However, bank processes themselves do not work in silos. Moreover, clients and regulators expect banks to deliver the outcomes of what they process by controlling the end-to-end flows. Siloed thinking and management blocks this end-to-end view and means there is no effective oversight on whether the bank is delivering what it needs to in a stable and efficient manner. Threats can develop and go unnoticed, with appalling consequences such as failures to achieve regulatory reporting compliance or fulfil payment obligations.
Getting an end-to-end view need not be that hard however. Banks have a large array of systems which monitor the technology landscape. Given that 90 per cent-plus of a bank’s end-to-end processes function through technology, these tools provide rich-pickings of data from which to make sense of performance.
This requires two elements. Firstly, an understanding of what the end-to-end flow looks like. Alpha Insight has deep understanding and experience of achieving this, something we pass on to clients. The second is the technology to obtain the insight needed. There is a market sector – operational intelligence – which supports this. Such solutions transform organisations without needing to rip out systems or insert expensive new layers of technology.
By operational intelligence we mean real-time dynamic, business analytics that gives full visibility of data and provides critical insights into streaming events and business operations.
Essentially, this is about data residing in the machine layer around the bank or institution. Operational intelligence is able to run queries against this data to deliver real-time analytic results. It confers the ability to make decisions and take action immediately, whether that is through human agency or automation.
End-to-end operational intelligence sees over the tops of the silos, revealing problems that cannot be detected through reporting on systems and processes within them, or through monitoring systems that track only individual applications. The data that is required to achieve this can be captured from database management systems or other aspects of the applications.
Intelligence and logic
Of course, there is no point collecting a mass of observations about the environment when it will overwhelm whoever needs to use it.
It is here that with expertise in the banking and finance sector, operational intelligence creates new levels of assurance and efficiency right across the organisation by applying business logic.
This begins with mapping the IT systems and the way each process within a bank relates to the underlying technology. Smart metrics can then be defined and linked to business performance. Thresholds, alerting parameters and measurement points to support the metrics are also then delineated. Dashboards are designed and tested and teams trained prior to the development of analytics, allowing a solution’s predictive capability to develop.
This important series of steps will ensure that the right set of KPIs and alerting thresholds is set and embedded into existing monitoring solutions.
This is an important advantage as within a large organisation, each silo is likely to have its own monitoring, whether that is the head of security looking at the movement of sensitive files, or the compliance department keeping on top of risky activity.
Potentially, these different sides of the organisation may be looking for the same thing. So there is a flow of data going through the business that is constantly being queried by different parties who may have their own monitoring tools. The use of an operational intelligence approach offers opportunities to rationalise the monitoring.
A significant advantage of this approach is that it requires organisations to spend less on their own infrastructure by proceeding in incremental steps, resulting in faster time to insight. This is because as each department or segment of the business moves to operational intelligence, its monitoring is already in place, requiring no new hardware or disruption.
One of the main lessons from deployment of operational intelligence is that implementation in stages is the preferred approach. Not only will this deliver business benefits quickly, it reduces risk by keeping a cap on costs as each element of the project progresses.
Indeed, the impact of the queries on the business also reduces costs, because data is only collected once and then reused, requiring less management overheads. An institution needs to be fully apprised of the critical aspects in its monthly, quarterly and annual business flows, and these are targets around which dashboards are created.
As more of the separate business flows within a large organisation come under the oversight of an operational intelligence solution, so the big data repository holding the metrics and their underlying information can be expanded.
Operational intelligence is now the easiest and most assured way of overcoming the severe drawbacks of silos within a highly complex organisation such as an investment bank, where speed and accuracy cannot be compromised, but where the absence of an end-to-end view of payments or credit risk has potentially devastating consequences. This is a technology that achieves the business’s goals with minimal disruption and with a firm lid on costs.