In the banking industry, the concept of risk is multifaceted. Banks deal with potential impacts on their operations every day, and these risks are often interconnected. For instance, banks constantly face security and compliance risks as financial crimes become increasingly sophisticated and regulators zero in on institutional practices.
Banks also face various types of financial risks. These include credit risks, which are tied to borrowers’ ability to pay back loans, and liquidity risks, which stem from the bank’s capacity to meet cash and collateral obligations. Banks also have to deal with business and market risks, which focus on meeting long-term strategic goals amid changes in interest rates, foreign exchange rates, equities, and commodity prices.
Thankfully, there are tools available to help banks continue running smoothly while facing these risks. By utilizing these novel capabilities, banks can effectively identify the risks, conduct comprehensive assessments, execute responses, implement action plans, and continuously monitor their overall position. Banks can use an array of tools to manage risks and prevent disastrous consequences, and here are a few of them.
Cloud-Based Risk Management Software
Some financial institutions already use integrated risk management (IRM) platforms for their front- and back-end operations, but sometimes, these are not enough. For example, bolt-on IRM tools may not seamlessly integrate with a bank’s enterprise resource planning (ERP) system or business applications. To ensure risk-intelligent operations, banks must move away from outdated tools and opt for the cloud-based financial services risk management solutions can offer.
A cloud-based enterprise risk management (ERM) platform offers a centralized suite of tools that banks can use for collaborative, real-time processing. These tools have artificial intelligence (AI) and machine learning (ML) capabilities built-in to analyze transactions, preventing cases such as theft, fraud, duplication, and cash leaks. Additionally, a cloud-native ERM platform can manage the separation of duties (SoD) to streamline workflow and automate manual tasks, freeing up time for high-value duties that require human interaction.
AI-Driven Risk Monitoring Tools
AI is a groundbreaking technology for banking because it serves as the foundation for real-time processing. Real-time monitoring is particularly important as potentially damaging scenarios can disrupt banking operations at any moment. Banks should consider investing in AI-driven tools that allow ongoing system analysis to prevent potential data breaches and data loss. Real-time audits, along with automated alerts and notifications, also help banks immediately uncover issues and coordinate responses at all levels.
One of the methods that AI-driven ERM solutions use to proactively improve risk posture is stress testing. These tools conduct intensive stress tests to assess an enterprise system’s resiliency and help IT teams manage their tech stack.
Risk Analytics
Risk analytics is a key aspect of risk management that must not be overlooked by banks seeking to modernize. Risk analytics serve as techniques for measuring, quantifying, and predicting risks throughout an enterprise. Lending institutions and credit unions can apply these techniques to properly assess credit scores and risk profiles. A good ERM platform uses analytics to determine, measure, and assess enterprise-wide vulnerabilities through various metrics that can easily factor in risk management strategies.
Another common use case for risk analytics is trend and variance analysis. Analytics tools are designed to analyze variances between market predictions and actual results to measure risks and uncertainties. In addition, analytics can support reserve analysis efforts and help financial managers create a risk management strategy. Through analytics, managers can get a clear overview of the enterprise’s position in terms of budget and contingencies.
Visualization and Reporting Techniques
While spreadsheets often come in handy, they can be cumbersome to use for enterprise-wide reporting. In contrast, automated reporting tools can generate valuable insights and present analyses in a clean, intuitive, and easily understandable way. These tools are built to eliminate irrelevant information and focus on the pertinent data that banks and other financial institutions need to improve their processes.
Next-generation visualization tools use data modeling techniques to process information from various data sources. For example, credit institutions can use data models to analyze credit applications in a more holistic way and to speed up decision-making. Well-prepared reports also add value to risk audits and reassessments that inform institutions on what they need to change.
A reliable ERM platform must offer a user-friendly interface that simplifies report generation at both the individual and organizational levels. Enterprises can use analytics-driven reporting tools to improve their risk management planning. At the same time, such tools can help borrowers and policyholders ensure transparency over their payments and transactions. A robust cloud-based software should be able to generate models, spot patterns, and provide meaningful insights to support the delivery of actionable results.
Manage Financial Risks with Ease
Nowadays, bare-minimum platforms are no longer enough to help banks manage their financial risks. Emerging capabilities like AI and cloud computing can take risk management a step further by preventing instances of human error from impacting all major and minor banking operations. Although human agents are still vital for managing these everyday risks, it pays to have the right tools to make the process faster, easier, and more accurate than before.