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Business white paper
Capitalize on Big Data in financial services
Table of contents
Understanding the four Vs that define Big Data
Prepare for the fourth wave of Big Data
The Big Data opportunity for financial services
Profit from 100 percent of your data with HP HAVEn
The HP HAVEn engines
The HAVEn ecosystem
HP HAVEn at work in financial services
What’s your next move? Consider these six questions
Business white paper | Capitalize on Big Data in financial services
Without question, data is the lifeblood of the financial services industry. From the earliest days, banks have collected data to assess the credit-worthiness of loan and credit applicants. Insurance companies have used data to develop sophisticated actuarial models in determining premiums. Investment companies have made multi-billion-dollar trading decisions based on data.
Data is growing at mind-boggling speed and volume. IDC predicts that the world’s digital universe will grow to 8 ZB by 2015.1 Shipments of PCs, tablets, and mobile phones exceeded 2.4 billion this year.2 And the number of personal client devices connected to the Internet will reach approximately 4.5 billion by 2015.3 These connected personal devices, along with sensors and smart devices (“Internet of Things”), will generate significant amounts and variety of data that, when harvested and leveraged, will bring about transformative changes.
Financial services firms and markets generate perhaps the highest volume of data of any industry segment. Consider, for example, that the NYSE creates 1TB of market and reference data per day, covering the use and exchange of financial instruments. Individuals complete an average of 10,000 payment card transactions per second.4 And worldwide mobile payment transaction values will reach $235.4 billion USD in 2013.5 And IDC declared in a recent financial Insights note, “2013 will be the year that banks leverage data gathering and reporting initiatives through increased analytics to maximize risk-adjusted returns on capital.”6
A network of sophisticated electronic systems underpins the operations of every financial services company. From capital market platforms that support trading activities to core banking software for daily transactions, each of these systems processes a growing amount and expanding variety of data. How well you understand the data you have and put it to effective use is now more crucial than ever. The key differentiator between the leaders and laggards in financial services today and in the future is how skillfully they turn data into useful information and use it to fuel success.
1 IDC, “Predictions 2012: Competing for 2020,” December 2011.
2 Gartner, “Forecast: Devices by Operating System and User Type, Worldwide, 2010–2017, 1Q13 Update,” June 2013.
3 IDC, “The Empowered IT User: How Individuals Are Using Technology & Redefining IT,” March 2012.
4 IDC, “The case for Big Data in Financial Services Industry,” September 2012.
5 Gartner, “Forecast: Mobile Payment, Worldwide, 2013 Update.” June 2013.
6 IDC Financial Insights, January 2013.
Business white paper | Capitalize on Big Data in financial services
The shift in the data landscape brings an enormous opportunity—but only to enterprises who can harness insight from all their data. This white paper looks at the opportunities and provides real-life examples where by financial services organizations are employing Big Data today. It describes how HP HAVEn, the industry’s leading Big Data platform, can help you securely capture, analyze, and act upon 100 percent of the data available to you.
Machine data Human information
Business data
10% of information
~10%
~100%
Annual growth
90% of information
• Temporal and location data
• Vehicle sensors (insurance)
• Biometric facial recognition (ATMs, vaults, etc.)
• Stock exchange tick data
• Call center agent notes• Web/social media feeds
• Financial transaction data
• Customer master data (birthdates, SSN, etc.)
Big Data landscape
Business white paper | Capitalize on Big Data in financial services
Understanding the four Vs that define Big DataWhile “big” is part of the data challenge, it doesn’t tell the whole story. Volume is just one part of the problem. Three additional Vs complete the picture: variety, velocity, and vulnerability. To manage Big Data effectively, you must be able to:
• Gather, store, and manage large amounts of data—up to millions of times more data than what you handle today (volume).
• Collect and store all relevant data, structured, semi-structured, and unstructured (variety).
• Analyze and react to it as quickly as it’s created (velocity).
• Keep it secure and compliant with regulatory requirements at all times (vulnerability).
Volume: Every day, we collectively create 41,000 times the amount of information in every book ever written. The digital universe doubles in size every two years.7 Our challenge lies not only in collecting and storing massive amounts of diverse data, but also managing and governing existing legacy data.
Variety: Around the world, at work and at home, we are connecting with each other through email, social media, websites, and freely sharing information and sentiments. Sensors, smart devices, Web feeds, and event logs all constantly generate data. Your enterprise needs a way to not only capture all of this diverse information in a common format, but also to interpret, synchronize, understand, and use it to make better business decisions.
Velocity: Thanks to technology, our world has become immediate and instantaneous. Your customers expect answers from you about your products and services faster than ever—ideally in real time. The goal is to harness insight from information at the speed of business.
Vulnerability: How do you secure a vast and growing volume of critical information? Protecting this data—and being able to search and analyze it to detect potential threats—is more essential than ever. As the platforms supporting this data move to hybrid IT environments, managing their security and availability becomes a Big Data challenge in and of itself, requiring continuous diagnostics and monitoring.7 “Extracting value from Chaos,” IDC, June 2011.
Business white paper | Capitalize on Big Data in financial services
Prepare for the fourth wave of Big Data
The Internetgigabytes
Client/servermegabytes
Mainframekilobytes
Mobile, social, Big Data, and the cloudpetabytes and yottabytes
TravelScribd.
Viber
Jive Software
Business
Photo & VideoYammer
Atlassian
Atlassian
Amazon
Answers.com
Tumblr
CYworld
MozyGamesPinterest
LimeLight
LinkedInPingMe
Qzone
Lifestyle
Sport
Taleo
TripItTwitter
MobilieIron
Yandex
Splunk
dotCloud
FedEx Mobile
BrainPOP
PingMemyHomework
box.net
SmugMug
YandexHeroku
RightScaleBeyondCoreEntertainmentZillabyte
Mixi
nebula
HP ePrintKhan Academy
Workbrain
YouTube
Amazon Web Services
salesforce.com
ProductivityAppFog
Bromium
Parse
AmazonPandora
Music
iHandy
kaggleSolidFire
DocuSign
GoGrid
Education
Reference
CloudSigmaScaleXtreme
Hootsuite
Foursquare
buzzd
UPS Mobile
Scanner Pro
Navigation
News
SuccessFactors
Workday
Zynga
Baidu
Renren
cloudability
Fring
Toggl
iSchedule
Flickr
ZyngaNew Relic
XactlySocial networking
Snapfish
MobileFrame.com
Dragon Diction
SuperCam
Rackspace
Paint.NET
Utilities
Finance
SmugMugAtlassian
Associatedcontent
Urban
MailChimpCookie Doodle
Ah! Fasion GirlAlterian
OpenText
Qvidian
Sage
Zoho
CCCCornerstone onDemand
CyberShiftSoftscape
Intacct
Sonar6NetSuite
PaperHost
SLI SystemsXerox
SugarCRM
Avid
Serif
Yahoo!Elemica
Kinaxis
SCM
Sonar6
Tata Communications
Hosting.comNetReach
SoftscapeFinancialForce.com
CyberShift
OpSource
PPM
Microsoft®
Adobe®
Corel
MicrosoftYahoo
Saba
QuadremADP VirtualEdge
Kenexa
Saba
IntraLinksWorkscape
HylandExact Online
NetSuite
Joyent
DatapipeNetDocuments
GoogleTM
Volusion
Ariba
DCC
Plex Systems
Quickbooks
eBay
Commissions
SCMOrder entry
Engineering
CostingManufacturing projects
Sales tracking & marketingPLMAccounts receivable
Fixed assets
CRMHP
Bills of material
SAP
Training
Billing
Time and attendance
RosteringERP
HCM
EMC
Cost management
InventoryQuality control
Cash management
Payroll
Time and expense
Product configurator
MRM
Activity managementService
Claim processingDatabase
Data warehousing
Every 60 seconds
IBM
Unisys
Burroughs
Hitachi
NECBullFijitsu
695,000 status updates
98,000+ tweets
698,445 Google searches
1,820TB of data created
11 million instant messages
168 million+ emails sent
217 new mobile Web users
Business white paper | Capitalize on Big Data in financial services
The Big Data opportunity for financial servicesThough challenged by an increasing volume and variety of data, financial services organizations have a huge opportunity to benefit from Big Data. Here we highlight six key use cases to bring to life the compelling opportunities Big Data presents in the industry.
1. Exercise good governance, risk, and compliance (GRC)—In financial services, you must ensure compliance and report on a plethora of regulations or face the consequence of an external audit or fines and disciplinary action for noncompliance. To exercise good governance, risk, and compliance (GRC), you need near real time visibility into your entire organization. However, gathering and integrating all your GRC data from disparate units and systems across your organization for continuous monitoring and management is a daunting and resource-intensive activity. Big Data technology can help you bring together all GRC-related data in a common format regardless of its source; analyze and retrieve precisely what you need; understand the data contextually; continuously monitor for changes; and quickly generate the reports you need.
2. Identify threats and prevent fraud—Financial institutions are top targets of cybercrime. While all types of businesses are vulnerable to attacks by malefactors, it’s the security breaches at financial firms that elicit the most media attention, public scrutiny and legislator ire. When threats occur, it’s more than financial loss at stake. Customers question their trust in your ability to provide security and protect their privacy. Hard-earned customer loyalty diminishes. According to Mandiant’s 2013 Threat Report, 63 percent of breaches are reported to the targeted organization by third parties, and the median number of days advanced attackers are on the network before being detected is 243.8 How can you detect fraud and stop attackers before they threaten you and your customers? Big Data technologies can help by enabling you to not only capture in near real time every event that occurs across your entire organization but also provide context to understand these events so information can be shared to better alert you of potential and actual threats.
8 Mandiant, “M-Trends: Attack the Security Gap,” 2013.
Business white paper | Capitalize on Big Data in financial services
3. Gain customer insight—Every minute of every day, customers provide valuable data to banks, credit card companies, and insurance firms in the course of conducting their financial services transactions. From unstructured call center audio data to machine-generated transactional and log data, financial services organizations handle large volumes, velocity and variety of data through their multi-channel networks. The volume is so great that storage, much less analysis, of the data can pose a real challenge. And even those who have managed to store the data struggle to efficiently and effectively access and analyze it gain valuable customer insight. Imagine the wealth of information contained in credit card transaction history that can inform on individual preferences, buying patterns and pricing strategies. Or the collective capture and analysis of all structured and unstructured data on a customer’s transactions and interactions with your bank to gain a more nuanced understanding of your relationship. Armed with a Big Data platform that can capture, process and make sense of not just machine data but human data, you’ll be able to gain true insight into individual customer behavior, preferences, and buying patterns.
4. Optimize customer engagement and services—Faced with the commoditization of traditional businesses and fierce competition, financial services companies are searching for new products and ways to distinguish themselves from their peers and win share of wallet. Being able to capture, analyze, and use data from a variety of sources (customer to context) allows you to create more targeted and innovative product and service offerings. For example, with advancement and availability of GPS technology embedded in the growing numbers of personal mobile devices, an insurance firm could optimize the marketing of its travel insurance products by gathering geospatial data to better identify and service this target audience. By capturing GPS data on their customers, insurers can send context-aware promotional offerings such as baggage loss insurance to them at the airport or provide better customer service by proactively sending pertinent emergency contact information for the city in which the policy holder has just arrived. Big Data technologies can help you to innovate and service your customers better by enabling you to mine data from many sources in order to gain insight and inspiration for the creation of more engaging and relevant services. As the example above illustrates, Big Data can help not only in the design but also in the actual delivery of the service.
Business white paper | Capitalize on Big Data in financial services
5. Optimize pricing—When trying to move the needle in a mature industry like financial services, the ability to optimize pricing offers major competitive advantage/differentiator. For example, being able to squeeze an extra basis point9 on a mortgage portfolio that is worth hundreds of billions of dollars can contribute millions to a bank’s bottom line. Similarly, when pricing insurance premiums, having information that better reflects the risk profile of the policy holder can mean the difference between profit and loss for the insurer. How do you use in-memory analytics to optimize price discovery for large portfolio trades? Or how do you capture and analyze customer preferences to determine acceptable target pricing? Big Data technologies can help you to capture, process, and analyze the data necessary to inform on the best pricing. Whether it is the use of in-memory analytics to optimize price discovery for a large portfolio trade or the capture of social media data for use in social analytics to determine target insurance pricing, Big Data technology can do so more cost effectively.
6. Improve operational efficiency and reduce cost—With continuing pressure on budgets, every financial services entity is looking for ways to increase operational efficiencies across people, processes, and physical assets. You must ensure appropriate processes are in place for maximum efficiency and that your employees have access to all resources for maximum productivity. How do you break down data silos and integrate essential information for centralized access so that your employees can get to what they need and share it faster? How can you better determine the right level of call center staffing to be able to provide fast, high-quality customer service while minimizing idle time? How do you reduce the overhead involved with post-trade processing and reporting?
9 One basis point equals one hundredth of a percentage point.
Business white paper | Capitalize on Big Data in financial services
Profit from 100 percent of your data with HP HAVEnHP HAVEn is the industry’s first comprehensive, scalable, open and secure platform for Big Data. Enterprises are drowning in a sea of data and need a trusted partner to help them. HP HAVEn has two primary components: a platform and an ecosystem.
• The HP HAVEn Big Data platform has three components: data collectors, engines, and “n” (any number of) applications. All these components are shipping today, and hundreds of customers are using them in mission-critical applications.
• The HP HAVEn ecosystem further extends the HAVEn Big Data platform by bringing together everything you need to profit from big data: hardware, software, services, and Big Data transformation.
Together, the platform and the ecosystem provide the capability to handle 100 percent of your enterprise data—structured, unstructured, and semi-structured—and securely derive actionable intelligence from that data in real time.
HP HAVEn Big Data platformEngines: HAVEn is built on engines that are designed to handle specific high-performance functions. These engines are purpose-built and complement one other. The Vertica engine, designed from the ground up at MIT, is ideally suited for large, highly scalable data analytics. The ArcSight engine is the recognized industry leader in security and events management, noted as such by Gartner’s Magic Quadrant for the past five years. Autonomy IDOL is protected by 170 patents covering proprietary statistical algorithms and computer science breakthroughs for processing unstructured human information. These engines are covered in detail in the next section.
Connectors: The HAVEn platform has 400 connectors from Autonomy as well as 300 connectors from ArcSight, which help you bring in all kinds of data from various sources. And you can use all your standard ETL tools from the SQL frameworks and the data collection frameworks from Hadoop. Each of these engines has an extensible framework to let you add custom connectors.
Learn more about how all enterprises can profit from Big Data.
Business white paper | Capitalize on Big Data in financial services
Applications: The combination of patented Big Data engines and over 700 connectors enables HAVEn to support a wide range of HP and third-party applications. ISVs, integrators and partners have adopted HAVEn to build new applications that to address both horizontal as well as industry-specific needs for data management and analytics. In addition, HP continues to enhance its own application portfolio to utilize the power of HAVEn.
HP HAVEn platform
HAVEn
Social media IT/OT ImagesAudioVideoTransactional
dataMobile Search engineEmail Texts
Scale
Hadoop/HDFS
Source
AutonomyIDOL
Speed
Vertica
Secure
Enterprise Security
Powering HP Software+ your apps
n Apps
Documents
Business white paper | Capitalize on Big Data in financial services
Recent HP research shows that by 2020 we can expect a significant shift in the benefits that organizations are seeking and deriving from Big Data projects. Today, the two benefits cited as most important for these projects are “improving operational efficiencies” and “tuning corporate strategy.” By 2020, however, we’ll see significant growth in areas such as tracking customer sentiment and needs and customer engagement.
HP HAVEn supports SQL, OBDC and JDBC so that you can preserve your existing investments in data warehouse technologies, business intelligence, and your existing staff. Think of the HAVEn engines as Lego blocks designed to click together and exchange data among themselves. For example, in building a customer experience monitoring app, the contextual analytics of Autonomy IDOL could become part of your application’s capabilities for analyzing consumer sentiment across social networks, where you can use the connectors to bring in the relevant information (blogs, tweets, etc.), integrate that with your CRM system via HP Vertica, and tie it all together with a BI or visualization tool.
Business white paper | Capitalize on Big Data in financial services
The HP HAVEn enginesHadoopHadoop complements HP technologies as a way to cost-effectively store massive amounts of data from virtually any source. The Hadoop distributed file system (HDFS) allows for the distributed processing of large data sets across clusters of computers using new programming models. It is designed to scale up from single servers to thousands of machines, each offering local processing and storage. Rather than rely on hardware to deliver high availability, HDFS is designed to detect and handle failures at the application layer, delivering a highly available service on top of a cluster of computers.
All of the HP HAVEn engines, including Autonomy, Vertica, and ArcSight, are able to interact with Hadoop for data collection and analysis. In addition to the engines, HP delivers an ecosystem with enterprise-strength features to help you harness Hadoop where appropriate. For example, Hadoop is well-suited for storing and cataloging large amounts of semi-structured data (like logs) and unstructured data (like audio, video, and email). For other high-value data, HP customers typically rely on the real-time engines of HAVEn to store data in an optimal format for analysis, meaning that HAVEn processes data up to 100 times faster than the batch-oriented data processing of Hadoop.
For more about HadoopVertica white paper on Hadoop
Business white paper | Capitalize on Big Data in financial services
AutonomyHP Autonomy’s Intelligent Data Operating Layer (IDOL) delivers a single processing layer that helps you unlock key ideas and concepts in your structured and unstructured information. You can understand and act upon documents, email, video, chat, phone calls, and application data simultaneously and quickly. IDOL streamlines information processing across networks, the Web, cloud, smartphones, tablets, and sensors. It helps you identify and understand your most meaningful data wherever it resides.
IDOL recognizes concepts and meaning in unstructured human information, which falls into two categories:
1. Unstructured text data: Includes content in blogs, news feeds, documents, and social media interactions.
2. Unstructured rich media: Includes photos, videos, sound files, and forms of information that do not include text beyond simple metadata.
IDOL forms a conceptual and contextual understanding of all content in an enterprise—automatically analyzing any piece of information from over 1,000 different content formats. IDOL can perform over 500 operations on digital content. These functions are available to build rich analytics applications for meaningful exploration of human data. They are organized in four categories to help guide the application builder:
• Inquire: “Search your data” functions
• Investigate: “Analyze your data” functions
• Interact: “Personalize your data” functions
• Improve: “Enhance your data” functions
Autonomy has a deep portfolio of applications designed for your specific data discovery needs. These include, for example, a Marketing Performance Suite of applications (for customer engagement and marketing optimization) and a Legal and Compliance Performance Suite (for litigation preparation and compliance).
For more about AutonomyAutonomy IDOL overview
Business white paper | Capitalize on Big Data in financial services
HP VerticaHP Vertica is a powerful, highly scalable analytics engine that drives down the cost of capturing, storing, and analyzing data while producing answers 50 to 1,000 times faster compared to traditional data warehouse technology. This enables you to take an iterative, conversational approach to analytics. Enterprise customers choose Vertica because it produces answers to business queries in record time, at a lower cost than alternative solutions.
Vertica’s high-performance analytics capabilities enable:
• Blazing fast analytics Gain insights into your data nearly in real time by running queries 50 to 1,000 times faster than legacy products.
• Massive scalability: Infinitely scale your solution by adding an unlimited number of industry-standard servers.
• Open architecture: Protect your investment in hardware and software, with built-in support for Hadoop, R, and a range of ETL and business intelligence tools.
• Optimized data storage: Store 10 to 30 times more data per server than row databases with patented columnar compression.
• Real-time loading and querying: Bring data into the analytics platform and give your users immediate access to rich analysis.
• Advanced in-database analytics: Conduct analytical computations closer to the data—and get immediate answers without extracting data to a separate environment for processing.
Enterprise security, powered by HP ArcSightThe HAVEn platform brings with it an entirely new level of enterprise security—allowing you to see not just if a breach will occur but also when it is likely to occur. HAVEn enables you to unify data in various formats from various sources into a simple common format, allowing members of your team to:• Search for compliance information and create reports, charts, and dashboards• Perform quick forensic investigations• Search through millions of events in seconds to quickly troubleshoot security concerns
For more about HP Vertica and Big Datavertica.com
Business white paper | Capitalize on Big Data in financial services
HP ArcSight Logger—an integral part of the HAVEn platform—unifies searching, reporting, alerting, and analysis across any type of enterprise log and machine data. It is unique in its ability to collect, analyze, and store massive amounts of machine data generated by modern networks. ArcSight supports multiple deployments such as an appliance, software, virtual machine, and within the cloud in both Windows® and Linux environments.
With ArcSight Logger, you can:• Collect: Collect any data from any device in any format from over 300 distinct log-generating sources. • Enrich: While the data is being collected, you can filter and parse it with rich metadata, helping to
unify the machine data.• Search: As the machine data is enriched during collection, you can search millions of events
using text-based keywords—no obscure commands or domain expertise required.• Store: The unified data can be stored in any format you have through a high compression ratio of
up to 10:1, eliminating the need for additional database administrators.
• Analyze anything: The rich content built into Logger helps you perform complex searches and create comprehensive drill-down reports. In addition, you can rely on real-time alerts to use machine data for IT security, GRC, IT operations, security information and event management (SIEM) solutions, and log analytics.
For more about HP Enterprise Security and Big DataBig Security for Big Data white paper
Business white paper | Capitalize on Big Data in financial services
The HAVEn ecosystemThe HAVEn ecosystem brings together everything you need to profit from Big Data: hardware, software and services. A rich ecosystem extends the HAVEn platform with a wealth of HP resources, partners, and integrators across the globe.
Three key differentiators help make the HAVEn ecosystem the industry leader in Big Data:
1. Openness: HAVEn makes connected intelligence a reality—while preserving customer choice in technologies and protecting existing investments. For example, HAVEn:
–Operates with all leading BI, ETL, and data visualization providers in the industry so that you can continue to use your existing investments.
–Supports APIs that include Vertica SQL/JDBC and R for analytics, IDOL interface, Map-Reduce/YARN, and REST APIs to allow deployment on mobile and cloud.
–Offers open standards-based support for multiple languages, frameworks, and support for open IDEs, including Eclipse.
–Incorporates 700 connectors to virtually any data source and file type.
–Ports to multiple virtual environments and clouds, including VMware, Amazon Web Services, and OpenStack.
–Supports all major Hadoop distributions.
2. Not just technology—business transformation: HP combined with our global IT partner ecosystem delivers on the full potential of Big Data-led business transformation. HAVEn extends that record of success and industry leadership to 100 percent of your meaningful data. And our global scale enables us to deliver innovations based on knowledge gained across industries worldwide.
For more about HAVEn hp.com/haven
Business white paper | Capitalize on Big Data in financial services
3. Vision and breadth: HP delivers the hardware, software, services, infrastructure, and business transformation consulting required for Big Data. We continue to enhance our Big Data software portfolio, including Autonomy, Vertica, and ArcSight.
HP HAVEn ecosystem
Cloud
Integrators Converged Infrastructure
Enterprise Services
Business Intelligence Partners
Data Partners
Social media IT/OT ImagesAudioVideoTransactional
dataMobile Search engineEmail Texts Documents
HAVEn
Resellers Technology Services
Business white paper | Capitalize on Big Data in financial services
HP HAVEn at work in financial servicesPerhaps the best way to see the opportunities that Big Data presents for financial services is to look at how some of the leaders in the industry are putting it to work today.
Scenario 1: Customer retention and serviceIn a service industry like financial services, there is probably nothing more important than knowing your customers. That information can help you know what products and services would be most appealing to them and how they should be presented to win your customers’ hearts and wallets. Even before the availability of Big Data technologies to help with the collection and analysis of the data, you invested in such methods as surveys, in-person interviews, and focus groups. But such efforts today are too slow—not to mention very costly. With the advent of social media and Big Data technologies you can capture and analyze a massive amount of human and machine data. If you can capture and understand 100 percent of this data, you will gain a truer, more complete picture of your customer and be better able to optimize your customer service.
Believe it or not, today nearly 85 percent of data goes untapped—primarily because it is unstructured (email, video, social media) and database systems in use cannot determine its useful value. One of the strengths of HP HAVEn is its ability to not only collect, store, and access data, but also help you understand the meaning and context of that data. A bank can use Autonomy IDOL, for example, to analyze the meaning of the customer feedback it collects, instead of having bank staff manually go through thousands of Twitter and Facebook feeds. In today’s fierce competitive environment, you can’t afford to ignore the 85 percent of your valuable customer data. Your customers expect you to understand them and for your customer service to reflect that understanding.
• Aflac used HP Autonomy to optimize customer experience by empowering its supervisors with information to track and monitor its call center agents. Aflac wanted to ensure that its agents, in providing the first point of customer contact, are exceeding their customer’s expectations. By enabling supervisors to gain full access and visibility into the interaction between an agent and the customer through automated recording of their conversations, supervisors can better assess the quality of service provided and manage agents as needed to ensure an optimized and consistent customer experience. Learn more
Business white paper | Capitalize on Big Data in financial services
Business white paper | Capitalize on Big Data in financial services
Scenario 2: Big Data for better decision makingGetting the right data to the right decision makers—precisely when they need it—can mean big money in financial services companies. In capital market institutions where money is made by making trades based on information this certainly rings true. The volume and variety of data capital market institutions have to handle continues to grow. Traders are bringing in more data points and at greater granularity into their models in order to optimize their pricing and investment strategies. A Big Data platform like HAVEn can help buy-side, sell-side, or exchange operators handle the volume, variety, and security of their data.
• BlueCrest Capital Management used the power of Vertica to instantly retrieve the Big Data it needed in real time to power its statistical trading models. Learn more
Scenario 3: Optimize operations and streamline bank processesThe demand to do more with less has spurred many large banks to seek solutions that decrease costs by increasing operational agility and productivity. Disparate transaction processing environments have been the cause of industry-wide vulnerability due to inefficient back office infrastructures. These infrastructures can create trade backlogs and transactional errors and generate the need for additional manual processes for trade negotiation, confirmation, and settlement. To address this challenge, many banks need a Big Data platform like HP HAVEn to help them fully integrate, store, access, analyze, and manage their diverse data.
• Scotiabank (the Bank of Nova Scotia) automated and streamlined workflow processes, reduced manual tasks, and transformed its online transaction processing. Autonomy helped the bank dramatically increase transaction capacity and integrity while decreasing operational cost and risk. Learn more
Scenario 4: Product and service innovation In financial services, traditional products and services are increasingly commoditized. There may be very little differentiation between mortgage rates and credit card offerings from one bank to another. Banks and other financial services organizations need to innovate to differentiate
and gain a competitive advantage. But where can they find the ideas to spark new innovation? A Big Data platform like HAVEn enables the capture and analysis of increasing amount and variety of data so that insightful information can be readily available to inspire new product and service ideas. Big Data can be used for data mining for ideas or in predictive modeling to understand market trends or customer preference. With a wealth of information waiting to be uncovered in the 85 percent of the data that hasn’t been tapped, financial services companies are finding new ways to innovate even in their traditional businesses.
• Cardlytics used the HP Vertica Analytics Platform to identify better marketing campaigns for leading financial companies. Being able to look into the huge volume of credit transaction data, Cardlytics was able to uncover innovative new ways for its FSI clients to design creative new offerings for their customers. Learn more
Scenario 5: Risk managementAccording to a recent IDC survey, the demands for financial reporting, risk management, and regulatory compliance are among the top drivers for financial institutions to implement Big Data analytics. Data security and fraud prevention are of tremendous concern to today’s financial services firms. With responsibility to regulators, customers, and shareholders, financial firms are responsible to safeguard not only the financial assets but also the data entrusted to them. Hackers and other malefactors are eager to exploit any chink in the armor of a bank or other financial firm. These predators have not only the desire but also in some cases the means to prey upon your vulnerabilities. In order to be one step ahead you need visibility into your entire business so as to identify, detect, and manage these risks before you suffer both financial and reputational loss. A Big Data platform like HAVEn can help you to access and analyze your environment for threats and vulnerabilities. Big Data analytics can quickly look for patterns across your organization to provide the intelligence needed for threat and fraud detection in real time.
• First National Bank of South Africa gained the ability to see the relationship among different data points in real time and drill down on suspicious activities. Using HP ArcSight, the bank has a single view of everything related to security across its network—insider activity as well as external cyberthreats—so that it can take immediate action. Learn more
Business white paper | Capitalize on Big Data in financial services
• Banca Intesa needed a way to correlate security information across its entire organization so that it can accurately identify the country of origin when suspicious activity is detected. Learn more
• A leading Latin American bank used HP Vertica Analytics to process and analyze billions of transactions to identify merchants and stores involved in credit card “skimming” (cloning). Learn more
Scenario 6: Regulatory compliance and auditFinancial services is a heavily regulated industry subject to ongoing oversight by various governing bodies. Financial services companies must comply with a plethora of regulations, guidelines, and requirements. To ensure compliance, reduce cost, and increase efficiency, they need a Big Data platform like HAVEn that allow them to readily and regularly gather, analyze and report on data from multiple sources across their organization. This is no small feat given the organizational and department silos that exist across most financial services companies, especially those who have undergone mergers and acquisitions. Aside from quick access to the data when required, financial services companies also need to confirm the accuracy, security, and discoverability of the data. An integrated Big Data platform like HAVEn can provide support for all your audit and compliance needs.
• Insurer TIAA-CREF used HP Enterprise Security ArcSight to stay on top of day-to-day security-related issues, including fraud, and get a handle on audit and compliance standards. HP ArcSight ESM equips TIAA-CREF with an effective storage of log data that meets compliance requirements and enables a quick response to auditors for detailed forensic evidence. Learn more
• A leading global financial services institution with over $2 trillion USD in assets and over 200,000 employees worldwide used HP Autonomy for archiving and compliance not only in its existing business but also when it had acquired the asset of a failing institution. This top 10 firm managed to handle and gain control over the acquired company’s vast quantities of structured and unstructured data in a timely fashion despite needing to meet with the strictest compliance guidelines. Learn more
Business white paper | Capitalize on Big Data in financial services
Only HAVEn delivers
100% of your data
700+ connectors
1,000,000+ machine events per second
30x lossless data compression
1000x faster answers
100%+ return on investment (ROI)
• Machine data
• Business data
• Human information
• Create better products/services
• Improve customer experience
• Defeat cybercriminals
• Protect your IT investments
• Protect your information
• Protect your applications
Business white paper | Capitalize on Big Data in financial services
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© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. The only warranties for HP products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. HP shall not be liable for technical or editorial errors or omissions contained herein.
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4AA4-8165ENW, August 2013
What’s your next move? Consider these six questionsOur customers and partners are rapidly embracing HAVEn for a wide variety of industry-specific uses, tailoring the platform to solve their specific Big Data challenges. The best way to get started on the road to addressing your unique data needs is to ask yourself these questions:
1. Are you able to process, store, and index all critical data across your organization, structured, unstructured, and semi-structured?
2. Do you have insights into customer behavior, sentiment, churn, and brand loyalty? And how easily and quickly can you gain these insights and act on them?
3. Do all components of your data management infrastructure work together? Or are data and applications siloed, with little or no centralized access?
4. Are you adequately addressing your industry-specific and government mandates for compliance monitoring and data retention?
5. Do you have the Big Data expertise in-house to efficiently handle explosive data growth and the increasing need to deliver meaningful analytics/insights to the business?
6. Can you draw connected, actionable intelligence from a combination of traditional transactional, new “network-of-things” machine data, and unstructured data such as social media and disparate knowledge worker documents and records?
Learn more athp.com/HAVEnhp.com/go/hpswfsi
To learn more about how to profit from Big Data with HP HAVEn: Profit from Big Data.
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Business white paper | Capitalize on Big Data in financial services