Information Economics & Investigation Management in the Digital Age
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1 Information Economics & Investigation Management in the Digital Age IBM Software Solutions Group INVESTIGATOR Paul Van Den Berg IBM Software Group Australia & New Zealand Investigation 1
2 2
3 Detection, Investigation & Management is even more complicated The information tidal wave is making it harder to apply analytics effectively, just when it matters most A deluge of data volume, variety, and velocity Volume of Digital Data 40 exabytes of data created in 2008 more than created in the previous 5,000 years combined Variety of Information Scope & Size of Data Sets Complexity, Connectedness and Growth Rates Context & Importance Of Integration Velocity of Decision Making Source: IBM Institute for Business Value 1 Gigabyte = 1,000,000,000 1 Terrabyte = 1,000,000,000,000 1 Petabyte = 1,000,000,000,000,000 1 Exabyte = 1,000,000,000,000,000,000 1 Zetabyte = 1,000,000,000,000,000,000,000 1 Yottabyte = 1,000,000,000,000,000,000,000,000 ALL the data that existed up IBM to CONFIDENTIAL 2003, we generate now every 2012 IBM Corporation 2 3 #ibmiod days! At the rate of 5 Exabytes a day.
4 Intelligent Investigation Management #ibmiod
5 Investigations have many unique challenges Pro-Active Investigation Identify high risk fraud and at risk internal controls within an organization. Policy and Process assessment and automation improving data governance strategy and automation of rules and internal controls to mitigate risk Reactive Investigations Automation of investigation procedures and the need to enable collaboration to co-ordinate all forms of evidence, decision to prosecute,prosecution documentation. Interviews and material management Pattern Identification Classification of fraud: Duplicate Fraud, Multi-payer; shell-game; defective goods; defective service need to use technology to be more flexible in identifying pattern and type in order to properly investigate activity. Evidence Evidence gathering and management is key. The need to assess data, transactions, terms, times, contracts, video, social media, audio, records is critical. Technical capabilities are needed to aggregate.. #ibmiod
6 Fraud & Incidents can be Reduced Across the Process Fraud and incidents no longer has to be discovered too late; we can examine massive amounts of data in real time to predict, prevent, and prove fraud and incidents Prevention Alerts Identification Discovery Investigation Monitoring Identify fraud risks at the source Flag & route fraudulent events at intake Help ID fraud during manual processing Perpetually analyze data to ID fraud Investigate, prosecute & recover fraud Report claim fraud outcomes and statistics Identity Behavior Exposures Timing Locations Identity Anomalies Patterns Prediction Identity Anomalies Patterns Text / Content Social Data Relationships Anomalies Patterns/Clusters Text / Content Social Data Case Management Unstructured data Entity Link Analysis Social Network Visualization Dashboard Reporting Geo-Spatial Trend Analysis Prediction Number of incidents within 30 days from this Actor, Team, Plant, Function Employees, Contractors, Suppliers involved in repeat incidents Twitter post identified and reported New pattern of data discovered - applied to entire information base Productivity to handle higher case load as more investigation is streamlined Geo-spatial analysis of ratio of incidents in specific area Intake Triage Review Optimise Monitor #ibmiod
7 Technology applied to fraud & incident management Solutions Fraud Incident Management Mergers & Acquisitions Lease Management Internal Audit Communication Management Research Reporting Automated Discovery Automated Detection Analyse & Manage Investigation & Remediation Reporting Identity Management Information Integration Predictive Analytics Operational Decision Management Content Analytics Case Management Intelligence Analysis Reporting & Business Intelligence Data Information Management & Life-cycle Governance #ibmiod
8 Click to edit Master title style Click to edit Master text styles Investigation for M&A Second level Third level Fourth level Fifth level Connecting Content Driving Performance 24
9 Investigation Use Cases in Oil & Gas Click to edit Master title style Automated document analysis and processing of Leases, Click Divisions to of edit Interest, Master Well Shut-ins, text Maintenance styles docs, etc. Second level State of the industry is still paper-based Digitize the paper content, analyze it and automate its processing Third level But highly regulated, legally-nuanced industry Merger and Acquisition centric industry Fourth level Oil & Gas Sector Tops in M&A This Year (Ref: WSJ Blog 7/23/2012) Companies size their staff for business-as-usual Fifth level But significant mergers cause multi-year backlogs Well production efficiency, problems and safety issues Machinery and operators generate huge amounts of data 27 27
10 Decommission Solution Overview Click to edit Master title style Content In The Wild Click to edit Master text styles Second level Third level Fourth level ECM Fifth level Information Classification, Ownership ECM Records Retention, ediscovery ECM Process documents, apply workflow Legacy or M&A Data Assessment Decommission Unnecessary Content Content Analytics enables content-based decision making and processing to: Determine document type and owner File and process the document automatically, route workflow Collect for Records Management and ediscovery Decommission for cost savings, selected content or entire data sources Reduce old and duplicate data 30 30
11 Click to edit Master title style Reduce the time to ingest and process data Click Expand to scope edit of due Master diligence text styles Identify what information is present or missing Second level Identify acquired rights that didn t know about Third level Timely action results in savings or preserving assets/rights Payments due to you - one client had unexpected $8M royalty payment Fourth level Payments/actions obligated to others Expirations, renewals Fifth level Accelerate keep/sell decision for newly acquired assets Additional business benefits Benefits for M&A Identify, organize, process and distribute M&A data to business owners Reduced manpower and enhanced productivity in locating and processing critical documents Automation of manual business processes Identify and manage information to prepare for divestiture 31 31
12 IBM Information Economics Manage Legal, Regulatory and Business Risk associated with your Data. Reduce and control your Data Storage. Paul Van Den Berg IBM Software Group Australia & New Zealand 38
13 Keeping Everything Forever from an IT perspective 1.8 zettabytes 1 (1.8 trillion gigabytes) exist in the digital universe 45% YTY growth 25% of data is unique; 75% is a copy Internet connected devices growing 25% per year 33.8 million servers worldwide 85% of data center compute cycles idle 15% of servers run 24/7 without being actively used on a daily basis Server image deployments growing 10% per year Virtual machines growing 42% per year US Data centers have doubled their energy use in the past five years 10% annual increase in data center energy costs over the past five years But IT budgets are growing less than 2% per year 40 Regulations 70% of CIO s say Regulations drive up storage demands. Businesses realising they must classify, manage, delete data - not just keep adding storage Source: IBM Survey & IDC IBM IT Trends Corporation
14 Global Oil Company case study 1 Many legal matters High employee turnover 1000s of servers and 1000s of IT staff Spreadsheet hold tracking No transparency in legal or IT Employees overlooked or their departure missed IT moves or retires data on hold Expensive, embarrassing recovery Hold-everything approach instituted to avoid recurrance Information volume and ediscovery cost rise sharply Risk increases with volume and complexity 2 3 Data Growth is Unmanageable CIO Crisis: Budget Eroded by Waste Federal evidence rules extended to electronic data; save everything Company data volume increases 875% in 5 years Data management costs exceed US$1B annually Target Actual Information growth will devour IT budget over time 53
15 Information Economics strategy reduces storage costs, lowers legal and business risks, and stops the root cause of growth rates Curbs storage growth, lowers run rate permanently Program leadership, process improvement and technology from IBM Run rate reduction and growth avoidance Run rate Projected Storage Costs (Petabytes) Information Lifecycle Governance Program Executive charter for enterprise initiative Processes, capabilities and accountability to achieve cost and risk reduction benefits through 8 $24M $21M $17.5M $14M $10.5M $7M $3.5M Process improvements, expertise and technology: Value-Based Archiving & Defensible Disposal Archive to shrink storage, align cost to value Dispose rather than store unnecessary data Extend and automate retention management Include electronic data that has business value in addition to records for regulatory requirements Automate retention schedules across all information to enable reliable, systematic disposal Automate the legal holds and ediscovery process Structure and automate legal holds process to lower risk, increase precision, enable disposal Analyze in place to reduce unnecessary collection, processing and review
16 IBM has a very simple savings proposition: Dispose of unnecessary data Enterprise Information %s based on CGOC Summit 2012 Survey 56
17 While these challenges sound like they are disconnected issues, they re not The silos are disconnected and that is the problem. Does legal holds by employee name, relies on IT to keep everything to mitigate risk. Thinks storage and IT are cheap anyway, but worried about risk. Struggling with cost of ediscovery on so much data. DUTY Matter Hold VALUE Department ASSET Retention schedule didn t cover the stuff they use daily. Fighting to drive profit up and back office costs down. 5,000 12,000 Retention Schedule DUTY Laws & Regs Put 100-page record schedule on intranet, hopes people follow it. Left out information with short term business value. Wants a record repository for records 5-10% of information Has the data but no idea what is really needed or why has to assume its all valuable. No idea that its responsible for legal holds and record retention. Struggling to reconcile 800% data growth with flat budget. Systems 500-2,000 Information 3PBs 100PBs No ability to dispose of garbage Too much data drives up IT and legal costs Retention schedule applies to very small data set A million choices for IT to triangulate laws, lawsuits, business value and data 57
18 Information Economics Applies to Structured & Unstructured Data Unstructured Data (files) Volume (in gigs) App & Mainframe Data (in gigs) 64
19 Information Economics assimilates the complex regulatory and legal requirements, and provides a rigorous implementation framework Identification of the Promulgating Agency Account for various retention period triggers Precise summary of the law at subsection level Legal and regulatory obligations Native Language Summary for Non-English Jurisdictions Global implementation and consistency with local usability Country Masters and exceptions based upon Global Master Specific Retention Period Information, including Trigger Event Identifying and accounting for retention outliers to avoid over retention Intelligent capture of the legal and regulatory breadth and true application Global Master Classification Schemes that reflect actual business processes Comprehensive, international law library for retention, privacy and security 65
20 Next steps: Identify & validate the possible savings and how to achieve them with Information Economics Conduct an opportunity analysis. And deliver fact-based assessment of total savings opportunity and a full plan to realize those savings 67 Compliance Governance & Oversight Council
21 68 Compliance Governance & Oversight Council 68
22 Compliance Governance & Oversight Council 69
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