Innovation in risk analytics

Amber Stokes talks to Microsoft’s Colin Kerr and Rupesh Khendry about how financial services organisations can combine modern cloud and big data solutions with traditional risk reporting tools to gain deeper risk insight

Amber Stokes
Amber Stokes
By Amber Stokes on 28 May 2014
Innovation in risk analytics

This article was first published in the Summer 2014 issue of Finance on Windows 

How have financial institutions traditionally viewed risk?
Colin Kerr, director of worldwide banking, Microsoft: Regulations are constantly changing. Organisations never really know what the next change might be and the impact it will have, and it has become a full-time job to ensure that they comply. It can therefore be very easy to be singularly focused on this. While it is of course important that organisations ensure they remain compliant, there may be other risks that they’re missing that can provide additional value. 

How else can they assess different kinds of risk?
Kerr: In financial services, data is the business. Banks that can best manage their data are those that become the most efficient, most profitable, develop the right kinds of products and solutions for their customers, and best manage their risk. 

As we all know, enterprises have access to huge amounts of structured and unstructured data, both on premise and externally, and the main challenge is gaining insight from it to help them understand their performance today and also predict their performance for the future. But this is also an opportunity now for organisations to redefine the way they look at risk. 

By harnessing the power of big data, financial institutions have the opportunity to gain deeper insight. By combining their current risk systems that build up a traditional risk profile of their business with big data and powerful business analytics solutions, they can have access to a higher level risk dashboard that introduces other tangential risk factors. That might be, for example, risk associated with brand perception, that can be analysed by checking what is said about an organisation in the media – not just social media. By scrutinising negative sentiment analysis, organisations can add an extra dimension to their risk analysis.

So how might a bank, for instance, harness big data to gain useful risk insight?
Kerr: After the worst of the financial crisis, many big banks lost the trust of their retail banking customers, and a social movement called Move Your Money was created, which influenced people to move their accounts to smaller and local banks. The campaign claims over four million accounts have been closed in major US banks in the first 18 months of their campaign. For many banks, this will almost certainly have had a negative impact on their risk profile, but such activity can now be forecasted and the risk mitigated if the right tools are used to analyse other sentiment data. 

Similarly, organisations can gain better insight into their corporate customers’ risk profile. For example, a bank managing a manufacturer’s cash and trade business could interpret weather data, macroeconomic data and even socio-political unrest in countries that form a vital part of a customer’s supply chain. Severe flooding could mean the customer’s physical supply chain is at risk, which impacts the financial supply chain, and in turn, could impact their profitability in the next quarter. Perhaps if they’re close to bankruptcy, this could push them over the edge. But aside from gaining deeper insight for the benefit of the bank’s own risk management, they can also use it to add value for their customers, providing risk information as a service, to help them run their business more effectively. The Royal Bank of Scotland recently deployed SQL Server 2012 Parallel Data Warehouse to do just this. Read the story here.

So is traditional IT architecture able to manage this kind of data processing?
Rupesh Khendry, head of worldwide capital markets industry solutions, Microsoft: The change in the landscape has had a huge impact. Until recently, it was easy to run legacy applications to manage risk on complex and departmental architectures, because financial services organisations had time on their side. Huge profits could allow them to have custom solutions and when an organisation experienced risk or a new regulation was introduced, they threw money at new software to solve it. But, this is of course not sustainable any longer, and with the speed of innovation with movement towards electronic trading, for example, organisations don’t have the time or the capacity to keep up.

The models for managing the kinds of risk that are widely known to us, such as standard market and credit risk, can no longer keep up with the speed and complexity of today’s world. Per market estimates, 80% of all trading today is algorithmic trading – extremely low latency trades that are automatically triggered in the marketplace – which affords organisations little time to deal with inherent risk. Organisations have to reinvent their architecture in order to scale up their capacity and reconsider how they value risk.

How might a cloud solution help?
Khendry: A huge business benefit is that business users don’t need to go through a business case to ask for and provision infrastructure over several months with large capital outlays. Instead, they can leverage Microsoft cloud solutions that offer flexible compute capacity and pervasive business insight.

One area Microsoft clients are delivering compelling benefits from is risk compute grids that are typically investment intensive, and are used to manage an organisation’s compute requirements for risk and compliance. However, capacity management is an issue, because usage obviously peaks in bursts when market-sensitive events occur. Typically, on-premise capacity is underused, many times as low as 20% of that capacity is used on average, but organisations must have that capacity invested and ready to be used 100% of the time. A cloud solution provides that flexibility.

With Microsoft Azure and the high performance computing pack, banks have the ability to run risk compute grids much faster and have the flexibility of sourcing it on demand. With Microsoft, banks can also ensure they remain compliant in terms of storing data in the cloud, which is a huge benefit. No other cloud provider can deliver the benefit of a private, public or hybrid cloud continuum. Our vision is to provide the flexibility so that institutions can keep the customer-sensitive information that they’re contractually and morally obligated to keep private on premise, while being able to burst only the compute needed into the cloud, leveraging in-house models and risk analytics or leveraging risk solutions from Microsoft partners. It also provides an end-to-end offering from data sourcing, all the way through data management, analytics, data consumption and monetisation.

Click here to read our feature about how insurance firms are starting to see the benefit of using the cloud to manage their mission-critical operations

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