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StreamSets for Financial Services
Overview
Financial services organizations are increasingly stepping away from viewing their customers as a transaction and reshaping their business to a customer-centric model. In addition, data is growing at an exponential rate and financial services leaders want to understand and have full visibility into what is happening in their industry. As digitization becomes the new paradigm for business, organizations must also understand new and real-time data to accurately determine the state of their internal operations and customer behavior. Plus, they recognize the need to find ways to better serve specific customer segments, offering personalized services that are both more relevant and easier to use.
At the same time, the financial services industry remains heavily regulated, and protection of customer data is paramount. Regardless of their specific focus or business model, all financial services organizations need to identify and guard against real-time online threats. Financial services organizations must embrace new ways to integrate and analyze streaming data in both their front-end (i.e. customer-facing) and back-end processes
Challenges
Financial services companies often find themselves underserved and constrained by legacy data solutions. While these platforms come with many “safe” enterprise assurances, they lack the ability to leverage and scale to meet the needs of advanced analytics and big data. Financial companies also aim to enable self-service analytics capabilities; however, data protection often becomes a project blocker.
Additionally, pressures continue to mount to deliver users a smoother, superior banking experience. With the bulk of financial transactions and brand touchpoints happening online, real-time data can help guide personalized services which can help financial companies grow their customer bases.
To effectively navigate modern data challenges, financial services companies must:
- Modernize their enterprise environments.
- Establish comprehensive and real-time Customer 360 views.
- Prevent and respond to cybersecurity threats in real time.
Harnessing a world of new data, especially the streaming data that is increasingly key to financial transactions—is difficult because of:
- Legacy siloed technology
- The sheer scale required to aggregate and analyze financial and customer data, both historical and real-time data, breaks legacy data pipeline technology.
- Legacy solutions also lack the ability to handle the velocity of real-time data such as logs, website activity, usage reports, and ATM feeds.
- Inability to drive decisions or business from data insights
- Initiatives to drive improved customer segmentation and personalization depend on a growing array of data points, mostly from external sources.
- Increased complexity and changing ecosystems of data platforms cause pipelines to be in flux.
- Regulatory & cybersecurity concerns
- Customer information exists in a variety of formats and spans multiple enterprise solutions, with few areas of integration. To maintain customer privacy and compliance, financial services companies must add protections to their financial and customer data.
- Point solutions and traditional Security Information and Event Management (SIEM) systems cover only a portion of the threat area subject to cybersecurity breaches, and these systems often cannot share insights across targets.
Solution
StreamSets helps deliver advanced analytics across financial services organizations by enabling rapid, efficient movement of data, while protecting data in flight as well as in trusted analytics zones.
Modernize enterprise environments.
StreamSets helps companies harness the world of fast and abundant data by easily streaming data into popular data platforms and by scaling to meet the demands of increasing data volumes. Financial services organizations can use the streaming data that StreamSets delivers to cross-reference transactions and to analyze online behavior.
Establish comprehensive and real-time Customer 360 views.
Because StreamSets helps you integrate a variety of data sources, regardless of schema or format, financial services organizations can create a single 360-degree view of their customers—then design personalized services to appeal to particular target segments. StreamSets lets organizations blend data from internal systems with external data, without sacrificing security or speed. They can also track the use of customer information for governance, masking sensitive data so that it can still be used in analysis.
Prevent and respond to cybersecurity threats in real time.
Online attacks happen fast. As a result, data moving between systems must be monitored in real time to stay ahead of cybercrime incidents. StreamSets helps companies build complex topologies feeding data to online applications that detect fraud. Users can set up dataflows quickly with a drag-and-drop user interface to rapidly implement cyber capabilities.
StreamSets benefits
StreamSets lets organizations:
- Enable self-service analytics and data science without introducing new risks.
- Handle evolving fields of customer information with intelligent pipeline technologies.
- Protect customers’ personally identifiable information (PII) for expanded analysis without exposing customer information.
- Save hours by not having to hand-code data pipelines to feed data lakes.
- Scale data processing and detections for high-velocity data sources.
- Use common connectors for clickstream, Adobe HIT, SalesForce, and other destinations.
Use cases
Credit monitoring
To gain a clear picture of a customer’s credit score, companies are streaming in credit-affecting events. Drastic changes in these events—such as a person opening a line of credit or using someone’s name to open an account—are often the first indicators that someone has gained improper access to a user’s credit.
Regulatory compliance
Financial services organizations are held much more accountable for their actions than almost any other industry. They are required to respond to regulators’ requests for information by rapidly accessing years of historical data.
Real-time decision making
To minimize risk and enhance customer experience, organizations need the ability to analyze and make sense of full data sets in real-time across systems. To do this, they must build real-time data pipelines that enable frictionless transactions between customers and merchants while mitigating risk and cutting costs.
Fraud detection
Fraud is an unexpected or rare event that causes significant financial or other damage—the effective response to which can be categorized, from the enterprise perspective, by detection, prevention, and reduction.
Customer 360
Customer 360 refers to a complete, 360-degree view of an organization’s customers, encompassing all the channels of interaction between the business and its customers. Customer 360 views require the ingestion and analysis of multiple kinds of data and data sources.
Customer churn
Acquiring new customers is costly for financial organizations. Maintaining customer satisfaction can often be done at a lower cost than acquiring new customers. External data can provide better indicators of when a customer has the potential to become an ex-customer.
