The broad and thorny issue of operational risk is increasingly under the spotlight from institutional investors, regulators and the media. And no area of the financial services industry is exempt.
For example, the US Federal Reserve announced in February it will look more critically at banks’ operational risks as part of this year’s stress tests . Meanwhile, the Alternative Investment Management Association (AIMA) has just released a new best practice guide on managing operational risk for asset management firms.
According to AIMA: “Investment managers should strive to implement processes which can help them to effectively identify risks and sources of risk, and put in place procedures to enable control and mitigation of such risks in line with their respective risk appetites.”
It’s all about the data
While many elements contribute to controlling and reducing a firm’s operational risks, effective data management and governance is one of the cornerstones of the process.
As a recent KPMG/Aite report observed: “The post-crisis era of increased transparency has resulted in many firms stepping in to assess the quality and the management of the core reference data sets on which they are basing their trading, risk management, and operational decisions. Reporting requirements to regulators and clients have also escalated in this environment which, in turn, has increased firms’ internal data aggregation, storage, and management requirements.”
To reduce operational risk, said the report, firms are seeking better insights into the maturity of their key internal data sets. This includes focusing on:
- Data quality metrics such as accuracy, completeness, timeliness, integrity, consistency and appropriateness of individual data items.
- Business end users’ and clients’ satisfaction with data transparency and availability.
- How much manual reconciliation or data cleansing is required.
- How quickly the business can respond to internal and external data demands, and whether they face scalability issues.
- Consolidating data environments to eliminate legacy applications and systems.
Finding the silver lining
The big question is how can capital markets firms overcome any data quality and efficiency inadequacies they find, and reduce their operational risk? For a growing legion, the answer lies in cloud-based data management solutions.
The appeal of cloud technology, noted the KPMG/Aite report, is that it can offer:
- Rapid cost reductions by removing process duplication at an enterprise level, and the need to support internally-deployed software and hardware.
- Predictable ongoing costs.
- Fast scalability to deal with higher data volumes without requiring internal investment.
- A centralized point for metering and permissioning data vendor feeds, with increased transparency into enterprise-wide consumption to improve vendor management and rationalize feeds where appropriate.
The result is more efficient collection, distribution and storage of the accurate and timely data every capital markets firm needs in these testing times.
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