Self-Service Risk Technology

By Srikant Ganesan | 17 August 2016

The fast-paced changes in the regulatory risk landscape are forcing risk managers to react with utmost urgency. Removing the roadblock of having to rely on a risk technology team during times of stress is now within reach.
 
Risk Technology – An Evolution
 
As regulatory reporting requirements have evolved from a batch mode to near time and on-demand reports, so have the demands placed by risk managers on their risk systems and IT infrastructure. Technology teams in turn have their own set of demands on the infrastructure which creates a web of interdependence between, the producer, consumer and infrastructure.
 
A self-service risk technology platform reduces this interdependence by providing targeted business value-add control points within the risk infrastructure. These control points allow business users to introduce change specific to their daily risk management function without relying on the next delivery from the technology team. As a consequence, technology teams will have bandwidth to focus on evaluating next generation cutting edge technologies that can improve the operational efficiency and supportability of their risk infrastructure.
 
Benefits
 
The benefits of a self-service risk architecture could be significant:
 
• Risk Managers can be provided with close control over the speed, flexibility and scalability of integrating analytical libraries and golden sources of data.
• Risk Managers can be provided with custom visualisations of risk calculations based on their individual preferences using a central aggregation layer.
• During times of market stress, Risk Managers can be provided with automatic burst capacity for risk calculations using a risk on cloud architecture
• Risk Managers can be provided with control over the frequency of their risk calculations whether in batch, near time or on-demand modes.
• The paradigm of technology teams being involved in every business change request is not sustainable in today’s technology dependent regulatory environment. This is not to say that technology teams should not own the risk architecture.
 
The self-service approach requires a clear separation between commodity components and business value add control points.
 
The commodity components can be defined as those that are core to the plumbing of a risk system. Data Connectors, Data Caches, Risk Engines, Aggregators and Scenario Tools are some of the commodity components controlled by the technology teams. Depending on the risk use case (Market, Credit, Liquidity), one or more instances of these components can be stitched together to provide a concrete risk solution. In a well architected risk system the commodity components change less frequently than the business value-add control points, thereby reducing the frequency of system deliveries.
 
Self-Service Business Value-Add Control Points for a Risk Manager
 
• Golden Source Integration: Currently, each time a new data source has to be integrated, technology teams have to be involved with a potentially long onboarding cycle. Allowing business users to self-service the integration can reduce the response time for business change requests.
• Analytical Library Integration: This control point enables Risk Managers to compute valuations, cash flows and stress tests on a wide variety of instruments using one or more analytical library of their choice. They can compare valuations and risk measures side-by-side between analytical models, which is useful for audits, evaluating new pricing models and comparing valuations for different regulatory regimes.
• Visualisation of Risk: Traders and Risk Managers like to use different visualisation tools — rarely does a “one size fits all” approach work. This control point allows users to select and customize their desired visual indicators and reports.  The risk technology environment should provide a centralised aggregation layer that can vend data to the tools supported by authentication and authorization to ensure appropriate access.
• Frequency of Computation: This control point allows Risk Managers to run computations in multiple modes; batch, near time and stress scenarios on demand. They have access to workflow tools that allow them to initiate these computations without constantly requesting assistance from their technology teams.
• Scalability with Risk On Cloud: When new demands are placed on Risk Managers during times of market stress, scalability can be a significant issue with a traditionally deployed risk infrastructure. In comparison, risk on the cloud provides scalability in a very short time period. The ability to access and control additional burst capacity contributes towards business cost efficiency and flexibility.
 
Conclusion
 
Financial firms are now continuously rebuilding their risk technology architecture in response to new business and regulatory demands.  A Self-Service, componentised architecture satisfies today’s requirements and ensures the architecture is open and scalable enough to meet future demands.
 
By Srikant Ganesan, Head of Risk and Trade Technology Solutions, Risk Focus.

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