Industry
Banking
Banking on purpose-led ecosystems
Highlights
- Migrating risk processes and applications to the cloud presents banks with an opportunity to expand capabilities in portfolio analysis, risk modeling, and fraud prevention.
- Cloud infrastructure can handle real-time data to make risk models more accurate, improving analysis, and speeding decision making.
- Scalable cloud high performance computing makes it possible to process huge volumes of data for complex simulations and deep learning workloads.
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Emerging trends
More and more financial firms are putting their money on cloud-based risk applications.
Many large financial institutions are already running elements of their risk and compliance functions on the cloud, but more is becoming possible. Providers of cloud-based risk management solutions today offer a wide variety of user-friendly, out-of-the-box automation tools that can help financial organizations keep pace with rapid change in the operating environment.
Banks and financial companies that do not migrate risk systems and capabilities to the cloud are likely to find themselves on the backfoot, unable to innovate quickly and respond to competitive pressures.
Banks and financial institutions will spend $77 billion on cloud computing services by 2024, with these outlays growing 16% a year compared with a 4.5% annual increase in IT budget overall, according to IDC projections. Large banks are moving capabilities to the public and private cloud, giving them an opportunity to reap significant benefits from cloud-based risk processes and applications.
As banks migrate the risk function to the cloud, however, they need a plan to manage complexity. They must have a coherent, long-term strategy to gain the full benefit of cloud-based risk applications—and to ensure that necessary resources will be available to develop and support new capabilities.
Cloud migration of risk tools comes with up-front costs. While most cloud providers offer incentives for multiyear commitments that can offset near-term migration expenses, there may be a significant bottom-line impact. Planning should reflect this: strategy setting is the right time to gain buy-in for the costs and the benefits.
Cloud-based risk models are more accurate and help analysts, managers, and risk teams make faster, data-informed decisions.
Competitive edge
Be a front-runner with the cloud advantage.
The financial world increasingly operates in real time. Risk-related processes and analytics need to reflect this. When payments are real-time or near real-time, for example, anti-money laundering (AML) and fraud detection processes need to happen faster. Cloud migration makes this possible.
Cloud applications enable data analytics that can quickly aggregate exposure to counterparties, a capability that’s vital during periods of market stress. Cloud computing infrastructure makes it possible to dynamically rerun scenarios on loan, trading, and investment portfolios.
A private cloud is often the preferred option for risk and compliance functions. It helps companies meet their unique needs in terms of security and privacy without losing the efficiency, scalability, and agility that come with public cloud.
Cloud-based infrastructure can be continuously fed real-time data that risk management software used by banks today cannot accommodate. Real-time data makes risk models more accurate and helps analysts, managers, and risk teams make faster, data-informed decisions.
With cloud migration, banks can tap into the high performance, scalable infrastructure needed to process huge volumes of data. Cloud-based grid computing can handle complex simulations and deep learning workloads. With virtually unlimited computing capacity, high performance computing, and high throughput networking, it becomes possible to better identify portfolio risks and hedging opportunities.
Leveraging cloud
Risk function use cases for cloud computing are many.
Here are some:
Regulatory reporting: Banks can improve the accuracy and resiliency of the reporting process while reducing staff time and compliance costs. On-demand reporting is made possible with the use of interactive dashboards and embedded analytics, while auditors and regulators can continuously monitor, control and report compliance status. Moreover, higher volumes of data can also be processed for regulatory reporting. As a result, banks can generate regulatory returns accurately and quickly. They can also reduce regulatory compliance costs and the time taken to process returns.
Stress testing: Cloud infrastructure enables computationally complex modeling related to market movements, credit, or collateral events, enabling more dynamic risk management. A proposed loan, for instance, can be tested under stressful conditions in response to changes in the collateral prior to providing credit approval. Market risk managers and traders can churn larger volumes of data and gather insights to determine how to hedge their portfolios, allowing them to dynamically manage their risks in real time.
Climate risk management: Geospatial data and machine learning on the cloud can help financial companies monitor, predict, and analyze risks of flood, wildfire, drought, extreme heat, wind, and other climate hazards that may affect a trading book or credit portfolio. Years of geospatial data can be quickly collected and analyzed, deriving actionable insights, and assessing impacts on banks’ portfolios. Moreover, changes in ecosystems, water availability and quality, soil health, and air pollution can be tracked, helping institutions deliver government mandates.
Set your strategy
Implement a broad, strategic framework.
While planning for adoption of cloud-based risk applications, organizations need to think long term. They should avoid the temptation to focus on short-term cost savings. While cost savings may help sell the effort internally, a broader strategy is needed to achieve the most important advantages of cloud migration.
The three consistent features in any robust planning framework for cloud migration of risk processes and tools are:
Strategy and sponsorship: Develop a clear, firm-wide strategy. Siloed adoption in parts of the organization will not tap the full range of benefits that can come from cloud migration. Leadership should survey the entire technology landscape, and recognize data and technology dependencies. Starting with use cases that are most likely to capture value from the cloud can help provide momentum and leverage for wider adoption in a particular area such as market risk assessment or fraud prevention.
Prioritization: Identify risk domains that will benefit the most from cloud migration, and within each domain, determine the specific models, processes, and applications that should migrate to the cloud first. The use cases that are likely to capture value from cloud computing are processes that require heavy on-demand computing, speed, resiliency, and accuracy. Leaders of various risk functions across the organization need to talk to each other and know what other departments are doing to avoid costly errors and duplication of efforts.
Resources and operating model: Risk functions may need to tap significant technical talent to develop, migrate, test, maintain, and improve risk models and applications on the cloud. While the benefits are going to justify the costs in the long term, short-term expenses put a premium on a carefully planned strategy. Risk leaders need to understand the impact on their cost base and should be able to clearly articulate how cloud migration will transform their baseline operating model.
This long-term strategic framework for cloud-based risk applications and processes will enable banks and financial institutions to remain competitive.
