Big Data and Analytics The New Core of Financial Services Cloud Standards Customer Council March 18, 2013 Michael Versace, Global Research Director, Global Risk, IDC Financial Insights
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Topics Financial Services Business and Risk Trends Impact of the 3 rd Platform Big Data/Analytics Strategies in Practice
2013 Themes Driving Investment Transformation Matters With ongoing instability of economies and financial markets into 2013, the financial industry will continue to operate with increased regulatory oversight, expectations to improve governance, and persistent pressures to optimize capital and costs These factors play out across the financial services industry landscape as five key themes underpinning risk and technology investments through challenging times o o o o o Competitive Advantage and New Business Growth Strength in Channels Capital And Control Optimization Infrastructure Resilience Operating Efficiency
Re-Shaping the Value of IT in the Financial Services Marketplace Regulatory pressures, today s global business demands force financial firms to re-think the value of the technologies, data management, and business process used to operate effectively, compete, and manage risk. The convergence of intelligent devices, social business, pervasive broadband networking, and analytics has ushered in a new platform for financial services that for building and servicing relationships between bankers, customers, partners, and regulators Analytics, Intelligence is the new Core. It is increasingly vital for firms to harness information to make actionable, optimized, and timely decisions, keep risks at anticipated and acceptable levels, and uncover opportunities to stay ahead of the competition IT reliability and efficiency increases as a risk factor. The age and complexity of key systems, lack of resources and skills sets for legacy, the push to reduce costs and meet regulatory requirements means corners will be cut and create additional outages, errors, and missteps requires active management and attention!!
The 3 rd Platform Shift: From IT Productivity to Business Productivity Innovation Information Critical Infrastructure Smart Grid Smart Buildings BYOiD Omni channel Retail Connected Vehicles Connected Health UBI Smart Cities Mobile Payments Business Agility Intelligent Industries IT Agility Services Systems 8
The Only IT Destination Your New Hybrid IT Org SaaS PaaS IaaS Your IT Org Custom Application Custom Application Custom Application Custom Application Custom Application Your Datacenter
The Greater Cloud Opportunity Includes Cloud Services Cloud Services Deployment Models Customer site Managed Private Cloud Service provider site 2016 Hosted Private Cloud $26.0B (50%+ CAGRe) Community Cloud Virtual Private Cloud 2016 $98.4B (26.4% CAGR) Public Cloud Dedicated/Single-tenant delivery platform Shared/Multi-tenant delivery platform Source: Worldwide and Regional Public IT Cloud Services 2012 2016 Forecast, IDC #236552 Aug 2012)
Cloud Usage by Industry Average 2011 Cloud Usage = 38.5% Source: IDC 2011 Vertical View Survey. n= 3153 respondents in enterprises with 1000+ employees IDC Financial Insights Visit us at IDC-fi.com 10
Business Case for Cloud Services All Industries Banks Lower IT costs 59% 59% 57% Lower IT costs 49% 57% 74% Better and faster access to data and information 46% 48% 41% Ability to introduce new products/services faster 28% 42% 42% Operational savings (beyond IT) 39% 49% 46% Better and faster access to data and information 40% 51% 36% 2012 Increased flexibility in application development 33% 41% 36% Operational savings (beyond IT) 36% 43% 53% 2010 2009 Ability to introduce new products/services faster 32% 36% 36% Increased flexibility in application development 19% 31% 33% Standardization/automation of processes and/or systems 28% 36% 31% Standardization/automation of processes and/or systems 16% 35% 26% 0% 10% 20% 30% 40% 50% 60% 70% 0% 20% 40% 60% 80% Source: IDC, U.S. Cloud Professional Services Surveys IDC Financial Insights Visit us at IDC-fi.com 11
While Cloud Has Become Mainstream, There Are Still Many Hurdles To Overcome Security remains the greatest concern for cloud Banks are still developing their cloud roadmap and working through concerns in moving data across borders Source: 2012 Vertical IT & Communications Survey, IDC, May 2012 N= 229 Multiple Responses Allowed Will not equal 100% IDC Financial Insights Visit us at IDC-fi.com 12
5 Year CAGR Big Data/Analytics and Cloud Growing in Importance as Solutions for Managing Risk $74B WW Risk Investments, 7.1% CAGR $42B Banking and Insurance, WW, 7.3% CAGR $1-1.4B in Canada ~ 17% Total Spend on Risk IT Emerging Markets Outpacing WW by 2-3 basis points Insurance Capital Marke Banks 2010 2011 2012 2013 2014 2015 0.12 0.1 Credit Risk Financial Crimes Liquidity and Asset- Liability Management 0.08 0.06 Enterprise Risk Management Market Risk and Trading 0.04 Compliance and Controls Information Security 0.02 0
Enterprise Security and Risk Framework for Cloud Contracts IDC Financial Insights Visit us at IDC-fi.com 14
Total Worldwide Business Analytics Software Market for Financial Services : $6.10 billion Big Data / Analytic Targets in Financial Services Analytics is the new CORE Performance Management & Analytic Applications Business Intelligence Tools Financial Performance & Strategy Management Budgeting, Planning, Consolidation, Profitability, Performance Management CRM Analytic Applications Sales -, Customer Service -, Contact Center -, Marketing -, Web Site Analytics Query, Reporting, and Analysis Tools Dashboards, production reporting, OLAP, ad-hoc query Credit Risk Analytic Applications Credit Analytics, Default Probability, Loss Given Default Investment Management Analytic Applications Portfolio Modeling, Investment/Concentration Scenario Modeling Advanced Analytics Tools Data mining and statistics Capital Optimization Analytic Applications Liquidity Risk, Asset Liability Management Operational Controls Systems Audit, GRC, SIEM Fraud Management AML, Payment Fraud, Insider Content Analysis Tools Spatial Information Analytics Tools Event Discovery, Collection, Consolidation Layer Data Warehouse Common Infrastructure (compute, storage, networking, integration)
Sustaining IT Investment Value with Innovation Security and Governance Spans Strategic, Business IT, and Op Initiatives The CIO. CRO, and CSO Agenda Has Transformed from How to Keep the Lights On with IT to How to Innovate in the Business with Technology Effectively Working With the Business Cloud: Scaling Up for New Capabilities App/Dev Architecture and Strategies Data Mgmt, Governance & Information Security Innovation Strategies Big Data: Creating New Revenue Streams IT Enterprise Architecture IT Staffing & Organizational Strategies Maximizing IT s Performance Mobile: Increased Customer Intimacy Governance, Risk & Compliance Framework IT Sourcing & Procurement Strategies Social: Greater Workplace Collaboration Service Mgmt Strategies IT Financial Mgmt Strategies 1. Right Size IT Sourcing 2. Removing Layers of Infrastructure Security Complexity 3. Giving Integration Back to the Vendors 4. Acquiring Needed Capabilities from PARTNERS 5. Offloading Risk to Achieve POE 6. Specialized Skills Acquisition and Augmentation 7. Big Data Intelligence 8. Information Governance as a Service 9. Intellectual Property and Privacy Protections 10. Multi-jurisdictional Critical Infrastructure 8
What Does Big Data Mean to Your Business? Information driven tactical, operational, and strategic business decision-making Enabled by effective use of talent, processes, technologies, and business architectures Designed to economically extract value previously unknown, un-leveraged And of course: from large volumes of a wide variety and high velocity data IDC 2013 17
What Does Big Data Mean Your Business? Q. In your opinion what does Big Data it refer to? Value It s not only about large volumes of data 40% 34% 26% Volume Variety Velocity N = 4177 Source: IDC Vertical IT & Communications Survey, March 2012. IDC 2013 18
Drivers and Benefits Cross functional drivers/use cases Job opportunities Optimization (customer engagement, supply chain, pricing relationship) Innovation (business infrastructure, products/service) Control (compliance, security, intelligence, fraud management On executive agendas Data-driven companies: 5% more productive 6% more profitable 1 Quantifiable benefits ROI achieved 2 1/3 of organizations within 6 months 70% of organizations within 1 year 1 Source: Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? MIT Center for Digital Business 2 Source: IDC 2012 Vertical IT & Communications Survey. N = 2699 IDC 2013 19
Big Data Challenges It s not only about technology Deciding what data is relevant (what data to keep/store and what data to discard) Cost of technology infrastructure Not having enough or the right IT skills to manage Big Data projects Not having enough or the right analytics staff to analyze the data Deciding which technology is best/most appropriate for different use cases Lack of business support and/or understand of benefits by business units It s not only about analytics It s not only about social media data It s not only about data scientists 0% 5% 10% 15% 20% 25% 30% N = 2699 Source: IDC 2012 Vertical IT & Communications Survey. IDC 2013 20
Big Data Adoption Drivers It s not all about social media Analysis of operations related data 30.1% Analysis of online customer behavior related data 29.7% Analysis of transactional data from sales systems Service innovation i.e. we developed or plan to develop a new service to our clients based on analysis of big data Analysis of machine or device data 18.8% 17.0% 20.6% Non-analytic workload such as use of Big Data technology to run OLTP systems or web sites or email application. 11.0% Q. What are your organization's drivers for using big data technologies and approaches? Source: IDC 2012 Vertical IT & Communications Survey. N = 4177
Big Data Technology Stack Decision Support & Automation Interface Applications with functionality required to support collaboration, scenario evaluation, risk management, and decision capture and retention Analytics & Discovery This layer includes software for ad-hoc discovery, and deep analytics and software that supports real-time analysis and automated, rules-based transactional decision making. Data Organization & Management Refers to software that processes and prepares all types of data for analysis. This layer extracts, cleanses, normalizes, tags, and integrates data. Infrastructure The foundation of the stack includes the use of industry standard servers, networks, storage, and clustering software used for scale out deployment of Big Data technology
Technology View Workload optimized technologies Software selection Infrastructure considerations Configurations Components Appliances Reference Architectures Deployment method On-premise Cloud One size does not fit all NoSQL Databases Complex Event Processing Search RDBMS It s not only about Hadoop Predictive Analytics and Visualization Hadoop and MapReduce Text Analytics IDC 2013 23
Adoption/Investment Data Financial Industry 2012 Survey Data, Early Results Organization's anticipated spending on Big Data initiatives in 2012 Deployments/Penetration Hadoop/MapReduce $10 Million to $100 Million (17.4%) $100 Million or More (3.6%) $10,000 or Less (19.5%) Don't Know (22.6%) Currently using (11.1%) Planning implementation within next 12 months (19.3%) $1 Million to $10 Million (23.0%) $100,000 to $1 Million (20.0%) $10,000 to $100,000 (16.6%) Not evaluating or using (29.8%) Evaluating (17.2%) Deployments/Penetration - NoSQL Deployments/Penetration Relational Data Warehouse Don't Know (14.5%) Currently using (22.6%) Not evaluating or using (14.8%) Don't Know (12.2%) Currently using (26.0%) Not evaluating or using (22.7%) Evaluating (24.9%) Planning implementation within next 12 months (15.2%) Evaluating (25.5%) Planning implementation within next 12 months (21.5%) N = 229 Source: IDC Financial Insights, IDC Global Technology and Industry Research Organization IT Survey, 2012
Business Value (ROI, TCO, etc.) Make it a Multi-dimension Initiative Intent Strategy Sponsorship Justification Evaluation of the strategic intent, operational metrics, sponsorship, project and program justification Innovation (product, service) Data Relevance Quality Availability Evaluation of the quality, relevance, availability, trustworthiness, governance, security, and accessibility multi-structured data Optimization (cost control, efficiency) People Skills Org Structure Culture Evaluation of the technology and analytic skills, intra- and inter-group collaboration, as well as organizational structures and cultural readiness Control (compliance, security, fraud) Technology Adoption Performance Functionality Evaluation of the appropriateness, applicability, and performance of technology and IT architecture to the relevant workloads Process Tracking Analysis Decisioning Evaluation of the processes of data collection, consolidation, integration, analysis, information dissemination & consumption, and decision making
Big Data/Analytics Case Studies Who s Doing What in Financial Services Case European Hedge Fund Global Investment Bank Achievements In memory analytics to optimize price discovery and investment strategies for large portfolio trades and swaps Common operational data stores to speed post trade settlement, confirmation, and access to common data Retail Banking Innovation Leader Asia Pacific National Bank Expanding US Property Insurer Global European Institution Investment Research Institution Community Bank Using geo-location data to create merchant intelligence and assist in optimizing offers and pricing to retail customers; driving mobile banking growth. Tracking social media into finely-tuned market campaigns Granular micro-targeting of customer segments and individual with specialized pricing based on historical risk performance and forecast data Using social analytics to gauge sentiment toward key product and service initiatives Using satellite services of private-sector satellite companies to track parking lots and fill rates of major retailers. Fill rates and trends informed investment advice Analyzing transactional and unstructured data (voice) collected to anticipate workloads and staffing needs in call centers and branches
Chapter 2: Big Data Maturity In Financial Services Think Across Multiple Dimensions Business vision, strategic intent, operational metrics, sponsorship, project and program justification Technology and analytic skills, intra- and intergroup collaboration, organizational structures and cultural readiness, talent sourcing Long term 2 5 Years 1 2 Years Next budget cycle Now Quality, relevance, optimized availability, trustworthiness, governance, security, and accessibility multi-structured data Monitoring, collection, consolidation, integration, analysis, information dissemination & consumption, and decision making, visualization, reporting Appropriateness, applicability, and performance of technology and IT architecture to the relevant workloads, integration strategy IDC 2013 27
Timeline Roadmap Time frame By Now Next Budget Cycle Short Term 1 2 years Mid-Term 3 5 years Long term Recommendations Inventory potential opportunities. Assess business and IT as-is situation. Identify opportunity to use existing data, technology, and analytics in new ways. Identify relevant technology and analytics skills among existing staff. Engage peers and vendors. Experiment with proof-of-concept and prototype projects. Use early quantifiable wins to demonstrate potential and justify budget allocations. Evaluate existing technology and its shortcomings. Assess skills gaps and plan for hiring and/or external professional services. Identify business sponsors and champions who will support and promote BDA projects. Expand projects, begin to define architectural standards. Merge big data into security and governance policies. Incorporate new data sources. Budget for work-load specific technology. Hire or outsource as needed. Ensure that both performance management and experimentation and discovery use cases and supported with appropriate technology, staff, data, processes, and funding. Engage in business process reengineering in response to new insights from BDA solution(s). Assess progress and adjust internal investment priorities to match evolving requirements. Ensure balanced resource allocation across all dimensions of the solution. Maintain a closed-loop learning environment based on data-driven decision making and expert judgment. IDC 2013 28
Big Data/Analytics: Near Term Milestones In 2013, vendors increasingly provide not only technology but also analytic services and content (data as a service) Distinction between technology and services firms will increasingly blur (Deloitte acquires OCO) Business process consulting accelerates in importance Big Data technology and services market will reach $16 Billion by 2016 M&A activity will kick into high gear in 2014/2015 as infrastructure & app suppliers expand footprints Mid-sized query, reporting and data integration vendors likely targets Recognition of the need for new Big Data technologies, such as Hadoop, to coexist with existing data warehousing, search & discovery, and high end modeling/simulation products
Cloud: Near Term Milestones Public IT cloud services spending will reach over $40B in 2012, and will reach almost $100B in 2016 Key app providers such as (Oracle, SAP, IBM) go all in - $17B in deal in the past 20 months, $25B in the next 20 months Rise of Hybrid Dev Ops emerges as a new IT skill - sourcing components and building/maintaining workloads across hybrid environments in a continuous development environment Industry solutions built on cloud rise to over $200B by 2015 75% of banks globally have the infrastructure "already in production to support their consumption of public cloud services by 2016 Over 50% of governmental organizations at the state level and below will be using regional" government cloud by 2015
Questions Michael Versace Global Research Director, WW Risk Big Data and Cloud Industry Lead IDC Financial Insights 508-988-7812 mversace@idc.com, @versace57 IDC Financial Insights Visit us at IDC-fi.com 31