High performance computing was a tough task for many organizations. Now, that is no longer the case with the cloud. The move from owned systems to cloud-based computing gives users access to high computing power and storage. The cloud enables businesses to process vast amounts of data, run advanced analytics methods, and adopt flexible technology setups. The banking industry has been one of the slowest to adopt the cloud. Most banks find it tedious to leave their legacy on-premises applications. Still there are some few exceptions, such as the Capital One bank. This bank started migrating to the AWS cloud in 2012 and recently completed the migration in November 2020.
Slowly, the attitude of banking leaders is starting to change. Some in the banking community are taking an open view toward cloud, considering the monitoring tools, enhanced transparency, and security features. Some realize that ignoring the cloud may even introduce new security vulnerabilities as on-premises vendors withdraw product support. But some point out the need for cloud-fit risk management frameworks as a part of the cloud migration.
Here is an article on how cloud solutions help banks, how has the cloud journey been for banks (with examples), and how cloud enables better risk management.
Banking and cloud-based risk management
Cloud computing plays a vital role in the risk management functions of the banking industry. Risk management involves both financial risks (such as credit risks, market risks, operational risks, and liquidity risks) and nonfinancial risks (such as cybersecurity risks and weather events).
Banks leverage the cloud power to process great amounts of data in shorter time, despite staff constraints and budget limits. The cloud solutions help the risk teams react instantly to business changes. Consequently, it helps them to drill down into the analytics life cycle and understand the risk drivers easily.
Banks employ cloud-based solutions in both financial and nonfinancial risk management scenarios. For example, banks use solutions to run large and complex daily and intraday liquidity risk calculations, monitor mobile banking transactions and P2P payments, and identify money-laundering activities.
Cloud computing is economical since the pricing model is flexible and usage based. So, banks only pay for what they use. Consequently, they move their technology cost model from a capital expense model to an operating expense model. Besides, they can scale up anytime to do better risk analytics.
The role of cloud in banking system
The cloud solves the following four challenges in banks: the need to process large datasets, the need for powerful processing systems, highly complex analytics and computations, and challenges in developing these systems.
Cloud solutions help banks to integrate different data sources faster. The standardized web interfaces remove the need for custom configurations between the bank systems and third-party systems. For example, American Express started Cornerstone, a cloud-based data ecosystem to share data across different business functions.
Cloud power for data analytics in banks
Advanced analytics and machine learning models require high computing power to process large datasets. Banks and financial institutions rarely have access to high computing power. The organizations cannot simply keep adding more servers due to resource limitations.
The cloud is revolutionizing banking and risk management functions. Cloud-based banking solutions help to streamline upgrades without wasting time on configurations. Consequently, the operating costs and obsolescence risks reduce.
A major bank was able to harness high processing power and process Monte Carlo simulations with an Azure-based banking solution. The simulations take hours as opposed to days with legacy banking systems. Similarly, an investment bank upgraded from legacy systems to cloud systems to try new analytics models, such as modeling interest rate volatility.
A global bank ran an analytics model 14 hours every day to assess global liquidity. However, the time taken reduced to less than 3 hours after migrating to a cloud-based solution. This enabled the risk management teams to increase the analysis frequency and analysis iterations. Furthermore, the team added more data, formulated faster balance sheet strategies, and made faster business decisions.
Modern risk analytics require the cloud advantage
Cloud solutions provide automation tools, including misconfiguration alerts, data drift analysis, and digital forensics. The solutions help to save the risk analysts’ time rather than spending time on configurations. Meanwhile, the risk analysts can develop better risk management models. Barclays worked with a cloud solution vendor to enhance transaction risk analysis process and save the time of the company’s risk analysts.
Cloud-based risk management solutions
The cloud enables easier risk management model recalibration and faster model testing. Processing real-time data is possible with cloud computing, unlike legacy systems. Real-time data improves the model accuracy and precision, thereby enabling analysts to make quick decisions.
For example, HSBC uses cloud-based anti-money laundering solutions to find money laundering activities. The bank’s Global Social Network Analytics (GSNA) platform maps connections between consumers and businesses. Furthermore, the platform enables risk management teams to determine suspicious transactions with ease.
Cloud-based banking solutions help to detect data breaches and the source of the breach faster. A leading bank built on a Google Cloud based solution was able to find the data breach and its source within 2 weeks, rather than a year.
Cloud-based risk assessment and management tools are more accessible to risk departments. This enables better assessment of risks. For example, loan officers analyze the risk-return tradeoff insights and simulate the loan performance before approving the loan.
Modern banking solution depend on the cloud power. Are you a bank looking for specific cloud and data solutions? Check out Deevita’s cloud computing services and see how you can model your business data on the cloud better and gain business insights faster. Request a FREE demo today.