Learn How Financial Services Organizations Can Use Big Data to Mitigate Risks
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Risk comes in a variety of forms including uncertainty in financial markets, legal liabilities, operational risk, fraud, and protection against external and internal attacks. Models are becoming increasingly granular and improving risk modeling is a high priority. Review this presentation from Splunk and MapR to learn how you can study months’ or years’ worth of raw data from disparate sources, without sampling, to understand and reduce risk.
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Learn How Financial Services Organizations Can Use Big Data to Mitigate Risks
- 1. © 2014 Splunk Inc. Data Infrastructure for Effective Risk Management
- 2. Today’s Agenda • Introductions • Current State of Risk Management • Value of Hunk & MapR • Demo • Q & A
- 3. Today’s Speakers Brett Sheppard – Director Big Data Product Marketing – Splunk – @zettaforce Sameer Nori – Senior Product Marketing Manager – MapR – @sameernori 3
- 4. Risk Management Challenges What are your bank’s biggest risk management challenges? Respondents were asked to select no more than three 4 Source: FIS, April 2014
- 5. Regulatory Costs are Rising 5 Source: NZZ (Switzerland)
- 6. Current Data Infrastructure Limits Risk Management 6 Liquidity Risk • Firm wide view of liquidity is inhibited by siloed systems and lack of actionable information Operational Risk • Need to link operational risk with requirements from Basel 2 and Basel 3 Credit Risk • Need to enhance credit risk models with external data sets to get a granular view
- 7. Hunk + MapR Data Infrastructure 7 Store • Archive large volumes of raw granular data • Store cost effectively for months or years • Secure non-public or regulated information Analyze • Explore, analyze and visualize data • Avoid fixed schemas that may miss data or limit flexibility • Search across both Hadoop and NoSQL data stores Iterate • Respond to changes on the fly • Preview results before MapReduce jobs are complete • Self-service analytics vs. months of programming Data infrastructure supporting risk management approaches that are dynamic, iterative and responsive to change
- 8. Explore, Analyze and Visualize Data Digital Intelligence Business Analytics Risk Mgt. Security & Compliance 360-degree Customer View Developer Platform (REST API, SDKs) Hadoop Client Libraries Hunk Apps Hadoop Clusters NoSQL and Other Data Stores Product and Service Analytics Internet of Things 8
- 9. Financial Services Firms Drive Results with Splunk Troubleshoot and monitor trading and settlement applications. Improve uptime and reduce MTTR. Monitor and manage online investment application and servers. Network security monitoring and rapid incident response to mitigate security risks. Ensures effective compliance while improving productivity of compliance team. End to end monitoring across trading applications –improving uptime and customer experience. Cross-tier visibility to improve dev ops coordination and accelerate MTTR. Index data across trading applications and FIX order processing to improve customer service. 9
- 10. Hunk Risk Management Analytics Preview results and interactively search across one or more clusters Provides more meaningful representation of underlying raw machine data Enables non-technical users to build complex reports without learning the search language Interactive Search Data Model Pivot
- 11. Interactively Question Data in Hadoop Pause means stop fetching results Stop means treat the current results as final and end the MapReduce job
- 12. Hunk Applies Schema on the Fly • Structure applied at search time • No brittle schema to work around • Automatically find patterns and trends
- 13. Dashboards for Self-Service Analytics Interactive Dashboards and Charts • Easy-to-use dashboard editor • Chart overlay • Pan and zoom • In-dashboard drilldown • Embed charts and dashboards in 3rd party apps • Reuse skills with Splunk Enterprise and Hunk
- 14. HQ MapR: WORLDWIDE HADOOP TECHNOLOGY LEADER 500+ PAYING CUSTOMERS
- 15. MapR: Best Product, Best Business, Best Customers Top Ranked Exponential Growth 500+ Customers Cloud Leaders 15 3X bookings Q1 ‘13 – Q1 ‘14 90% software licenses 80% of accounts expand 3X < 1% lifetime churn > $1B in incremental revenue generated by 1 customer
- 16. The Power of the Open Source Community Management APACHE HADOOP AND OSS ECOSYSTEM Streaming Storm* NoSQL & Search Solr Data Integration & Access Hue HttpFS Flume Knox* Falcon* Whirr MapR Data Platform Security SQL Drill* Shark Impala YARN Batch Spark Cascading Pig Spark Streaming HBase Provisioning & coordination Savannah* Juju ML, Graph GraphX MLLib Mahout MapReduce v1 & v2 Workflow & Data Governance EXECUTION ENGINES DATA GOVERNANCE AND OPERATIONS Tez* Accumulo* Hive Sqoop Sentry* Oozie ZooKeeper * Certification/support planned for 2014
- 17. Architecture 3 Matters for Success NEW APPLICATIONS SLAs TRUSTED INFORMATION LOWER TCO FOUNDATION Data protection & security High performance Multi-tenancy Operational & Analytical Workloads Open standards for integration
- 18. MapR Customers in Financial Services 18 Fraud Detection • Zions Bank can predict phishing behavior and payments fraud in real time and minimize their impact Counterparty Risk Management Analytics • A large bank is able to accurately understand the aggregate risk associated with all transactions with a specific counterparty
- 19. © 2014 Splunk Inc. Demo
- 20. Getting Started • Review the joint data sheet at http://bit.ly/1oDYD3M • Download the free sandboxes at mapr.com/sandbox and splunk.com/hunk • Talk with us at .conf2014 or Strata + Hadoop World NYC
- 21. © 2014 Splunk Inc. Thank You
Notas del editor
- Ineffective risk management is costly, in total dollar figures and as a percent of firm-wide profits. Shown here by the Swiss newspaper NZZ (in German) are fines ranging from $1.9 billion to $450 million. And the fine amounts dare rising. The JP Morgan Chase $13 billion settlement with the U.S. government regarding charges that the bank overstated the quality of mortgages it was selling to investors exceeds the total of these 12 fines combined.
- Financial Services is one of the key industries where Splunk has had tremendous success. Leading Financial Services firms around the world are using Splunk every day to gain operational intelligence for their business. Here are some examples of how different companies are using Splunk to drive value.
- Pause or stop Jobs in progress and revise queries interactively. We’re mindful of the resources we use in Hadoop. Pause in Hunk: This pauses in the Search Head. Hadoop jobs keep running until the TCP header runs out. If you abandon a search for more than 30 seconds it will kill the search.
- Hunk applies structure at search time Designed for data exploration across large datasets – preview data & iterate quickly No requirement to understand the data upfront No limit to the number of results returned or the number of searches No brittle schema to maintain or update Find patterns and trends across disparate data sets in a “grab bag” Hadoop cluster Use the Search Processing Language or create data models and pivot Unlike Splunk Enterprise, Hunk applies schema for all fields – including transactions and localizations – at search time.
- With interactive Dashboards and Charts, rapidly build custom dashboards with a new dashboard editor and deliver richer analytics experience with
- MapR is the technology leader in Hadoop – the innovations in our distro enable us to use Hadoop not only to power analytic use cases such as what we’ll talk about with HP Vertica today, but also operational use cases such as real-time recommendation engines or fraud detection apps. Our 500+ customers have had tremendous success in production with MapR, and we service many of the world’s largest organizations globally across 10 offices outside the US.
- The power of MapR begins with the power of open source innovation and community participation. In some cases MapR leads the community in projects like Apache Mahout (machine learning) or Apache Drill (SQL on Hadoop) In other areas, MapR contributes, integrates Apache and other open source software (OSS) projects into the MapR distribution, delivering a more reliable and performant system with lower overall TCO and easier system management. MapR releases a new version with the latest OSS innovations on a monthly basis. We add 2-4 new Apache projects annually as new projects become production ready and based on customer demand.
- This analogy applies as well to building a data platform – you have to architect for the future. This allows you to build higher, stronger, and faster, without retrofitting later down the road (anyone who has added a second story to their house can attest to the additional cost and construction delays if you have to reinforce a foundation which wasn’t designed to hold the stress) For business-critical applications you must have data protection and security (availability, data protection, and recovery), high performance (with random read-write system), multi-tenancy (to support multiple business units, isolate applications or user data,…), provide good resource and workload management to support multiple applications, and open standards to integrate with the rest of the enterprise data architecture This data foundation allows you to support new data-driven applications (both operational and analytical) , maintain service level agreements with the business, provide information you can trust and count on being there when you need it, and ultimately being the best TCO for the long-run. Supporting enterprise systems without retrofits or multiple clusters to work around platform deficiencies (e.g., to support operational/online applications in Hadoop today, you need a separate HBase cluster – separate from the rest of your Hadoop cluster/investment)