Risk Aggregation and Capital Efficiency

Laying the Foundations by Improving Analytics Productivity and Data Quality

Capital planning and management have never been more important than they are today, driven by Basel III as well as new local regulations - and the journey is far from over.

The new regulatory regime has been the impetus for financial institutions to integrate data management and analytics into their risk management platforms. While sophisticated analytic tools are available for industrialisation, risk aggregation and capital planning, the way analytics is used is still in its infancy across the industry.

Mike Jones has led risk teams at a number of major financial institutions including ANZ Banking Group and HSBC, and is now managing director of analytics consultancy, Connected Analytics. He says that analytics maturity is a barrier for institutions looking for more insight into their organisations, especially in terms of capital management.

“Furthering the analytic maturity curve will support the capital efficiency agenda. This includes the associated tools, technology, processes, automation, culture and governance,” says Jones.


Organisationally, big data and big analytics needs to be part of plans for structured evolution.

Mike Jones
Managing Director, Connected Analytics

Integrating data remains a challenge

While financial organisations are aware of the importance of analytics, they face challenges around the integration of data across multiple sources and how to manage it effectively when the quality is poor or lacks integrity.

Jones adds that the demands are ever-increasing but the tool sets and foundations – which have evolved project-by-project over the last decade in an unstructured way – are not mature enough to support future demand.

He believes that many organisations that want to be more data-driven need to get back to basics. “Many financial institutions still operate in the silo approach that they adopted in the past. The reality is today’s ‘analytics ecosystem’ comprises many elements that need to connect to each other. And quite often organisations have several parts of their ecosystem, typically across product or divisional silos that are weak and cannot support what is being asked of them,” he says.

SAS Australia’s Head of Risk Intelligence Larry Roadcap adds that getting the foundations right from the beginning ensures a more efficient and cost effective ride along the analytics curve. “One of our major banking customers has built a SAS-based enterprise wide risk analytics platform and regularly highlights how spending time on foundational capabilities, such as data management, has delivered efficiency and scalability. Their programmatic approach has allowed them to add new components faster and at a lower cost as regulations change and their needs become more sophisticated.”

Jones says it’s the "softer" activities that are often overlooked, such as decision making, data culture and governance. “One of the issues that prevents analytics moving ahead is that it isn’t embedded as deeply into the organisation’s culture as it should be,” he says. “There is much of what I call ‘short-termism’ in many organisations and because of this, there is an imbalance where ‘quick wins’ or ‘runs on the board’ are prioritised too often over longer-term outcomes.”

With all of these challenges and disconnects, something as conceptually simple as a single view of customer becomes extremely difficult, he says. “We don’t yet have the basic foundations in place and while we are throwing energy at making it happen, organisations need the right tools and culture in place to be successful. The cost of poor productivity is extremely high and many of the current analytics operating environments are not sustainable.”

Regulation drives holistic approach

Jones says there has been a holistic shift with organisations who are now looking more at the analytics ecosystem and its evolution. “While it is starting to come together, it is expensive to run so they are looking at what tools and technology they can put in place at an enterprise level to run governance and to influence the culture around data.”

He says solutions providers such as SAS help support the different maturity requirements of a range of organisations – whether they are at foundation levels or more mature.

Roadcap adds that SAS customers are making substantial foundational investments to tackle data and risk aggregation issues.

“Compliance with standards such as BCBS 239 and APRA’s CPG 235 may be driving these initiatives in the short term but many institutions see this as a strategic opportunity to align their data strategy with business strategy. SAS is helping these customers with risk solutions that allow them to confidently satisfy regulatory requirements whilst delivering better performance and better risk management,” says Roadcap.

Big data or big distraction

Jones says any conversation around analytics often involves the topic of big data. “To me, big data has turned into a big distraction for some organisations,” he says. “Many would benefit more by focusing on lifting the maturity of their existing data ecosystem and thinking about the role data will play in the future, rather than increasing the complexity by bringing in a different variety, volume and velocity of data they may not be ready for.”

But he says there are conversations around big data in an organisational context that are exciting to have. “Customers will have increasing expectations that we use the data we have about them – structured and unstructured – to better understand them and service their needs. At the same time, in a risk space, could we bring together unstructured social data and leverage it in a capital efficiency conversation? I think that would be an extremely difficult conversation to have with a regulator at this point in time. Organisationally, big data and big analytics needs to be part of plans for structured evolution.”

Jones adds data modernisation or industrialisation is another key focus. “Where we have lots of highly repeatable processes, it is commonplace to see lots of manual intervention and low levels of automation and maintainability,” he says. “But the cost of ownership of all these processes is very high and this is an opportunity.”

Risk aggregation and capital planning are key drivers of productivity push

Risk analytics is increasingly important for financial institutions as they cope with complex regulations as well as a competitive environment. But Jones says having in place better and faster risk processes is not just about complying with the new regulatory requirements.

“Risk processes are essential for competing successfully in today’s business environment,” he says. “Top of mind for all businesses is productivity and the key driver around achieving this is more efficient capital planning and management – and this relies heavily on having the right analytics approach in place.”


Financial organisations are facing a seismic shift following Basel III as well as the new regulatory regime. Many are looking at how analytics can help support the capital efficiency agenda.

The key challenge lies in the fact that tool sets and foundations have evolved in an unstructured way project-by-project, and are not mature enought to support future demand

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