Why Financial Services Needs Big Data APM
Financial Services organizations operate in a challenging environment. As one of the most heavily regulated industries in the world, they are a constant target of hackers and fraudsters. At the same time, their applications and services are essential components of the global economy. These systems must be highly available and performance-optimized while generating investor and shareholder returns.
The primary big data use case for financial services is business analytics that run on Hadoop. Data-driven analytics are key to the current and future competitiveness of financial services companies. By capturing and leveraging massive volumes of data, financial services companies are capitalizing on new data-driven business opportunities. But the highly regulated nature of the financial services sector and concerns around uptime and data security make managing these applications difficult.
Proactively monitoring the performance of your critical applications and services with a big data Application Performance Management (APM) solution can help you avoid operational nightmares and enable you to find and fix application and infrastructure issues before they impact your organization. Pepperdata Big Data APM products like Application Spotlight and Platform Spotlight monitor and optimize business intelligence applications that analyze customer data, manage thousands of concurrent queries, automate business processes, optimize risk controls and business outcomes, and ultimately improve customer experience and drive growth.
Optimizing Performance of BI Applications and Workloads – Seven Use Cases
Here are seven examples of financial services BI applications and workloads that Pepperdata big data APM solutions monitor and optimize for performance. Each of these delivers tangible business benefits to the organization.
- Predicting the risk of churn for individual customers and recommending proactive retention strategies to improve customer loyalty. Banks and card issuers can identify at-risk customers and respond quickly to retain them.
- Providing early warning predictions using liability analysis to identify potential exposures prior to default. This enables proactive engagement with customers to manage their liabilities and limit exposure.
- Predicting risk of loan delinquency and recommending proactive maintenance strategies by segmenting delinquent borrowers and identifying “self-cure” customers. With this insight, banks can better tailor collection strategies and improve on-time payment rates.
- Detecting financial crime such as fraud, money laundering, or counter-terrorism financing activities by identifying transaction anomalies or suspicious activities using transactional, customer, black-list, and geospatial data.
- Predicting operational demand based on historical data and future events. With this insight, banks can anticipate call center traffic volumes or predict demand for cash at ATMs.
- Evaluating customer credit risk by analyzing application and customer data for automated real-time credit decisions based on information such as age, income, address, guarantor, loan size, job experience, rating, and transaction history.
- Managing customer complaints using data from various interaction channels to understand why customers complain, identify dissatisfied customers, find the root causes of problems, and rapidly respond to affected customers.
The applications and workloads that the Pepperdata big data APM solutions optimize in these analytics and BI use cases provide the “source of truth” that ultimately underlies customer-facing, transactional use cases. For example, banks and card issuers now deploy chatbots that address customer needs and inquiries, walk customers through process steps, provide predictive messages and behavior insights, and automate tasks such as money transfers or balance inquiries. Over time, the behavioral data that chatbots collect is analyzed in the Hadoop cluster to further develop and refine appropriate replies to user requests.
Big Data APM Scalability for Massive Deployments
Pepperdata big data APM solutions provide the scalability that makes them the choice of the world’s largest financial services organizations, with some customers running in excess of 1,000 nodes in their distributed computing environment. Customers with high node counts face unique operational challenges, including extremely high numbers of concurrent queries. They cannot afford any service or data loss. To reduce risks associated with potential downtime and data loss, some organizations have established data centers with triple-redundancy cluster architectures.
Financial services organizations with such huge physical infrastructure investments naturally want to maximize their workloads and utilize their infrastructure as efficiently as possible. For these customers, Pepperdata big data APM solutions automatically optimize infrastructure capacity and application performance to provide:
- 90% capacity utilization without manual application tuning
- Up to 50% improvement in throughput that results in significant savings in infrastructure spend
- 95% reduction in MTTR, with an average 5,200 hours per year saved on triage and troubleshooting time
Bridging the DevOps Communication Gap
Our financial services customers appreciate the ability of Pepperdata big data APM solutions to help bridge the communication gap that can exist between developers and IT operations, a situation that can negatively impact application development and the production workloads. Using Pepperdata Application Spotlight, customers can readily monitor an app as it transitions through the development cycle from pre-product to production. As the application evolves, issues like bottlenecks, CPU, and memory mismatches can be quickly detected and resolved using Pepperdata Platform Spotlight and Capacity Optimizer to ensure optimal performance in the production environment. Better communications enable ITOps to help the application team efficiently work through the development transitions. These benefits optimize application performance and uptime and help ensure that SLAs are met.
We don’t need to explain the significance of ROI to IT Operations leaders in the financial services industry. At a macro level, profitability is the function of stable and high performing analytics, applications and services that result in customer loyalty and retention. With an investment in big data APM solutions from Pepperdata, you can bulletproof your foundational analytics applications and workloads and not only avoid application performance issues but also increase revenue and customer satisfaction.
Other Things You Can Do
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