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Banking on Big Data: Harnessing Big Data to drive valuable BigDecisions

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Banking on Big Data: Harnessing Big Data to drive valuable BigDecisions Ian West Head of Enterprise Information Management


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Key Discussion Points 2


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Cognizant From internal consulting unit to a market leading Global Services Provider 1223+ Active Customers $8.84 Billion 2013 178,600+ Employees Globally 20, 000+ Projects in 40 countries 25+ Regional Sales Offices 75+ Global Development Centres Financial Services: 42.3% Healthcare: 25.4% Retail, Manufacturing & Logistics: 21.1% 20.4% 3


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4 Emergence of Big Data and Analytics Increasing belief in its potential to create competitive advantage of banking organisations globally have invested in big data1 >34% Between 2012- 2017, the uptake of big data analytics amongst larger enterprises in the UK will more than double to ~30% of organisations 3 30% of large global companies will have adopted big data analytics for at least one Security or Fraud Detection Use Case by 2016 (up from 8% today) 2 25%


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5 Big Data and Analytics drive business value “Leveraging the power of big data & analytics to drive valuable big decisions” Business value Big Data & Analytics Traditional Analytics & BI Improved understanding of customer Information based business decisions Deeper insight into risk Increase revenue Reduce cost Mitigate risk and ensure compliance Additional data sources to enrich customer profiles Variety of unstructured information to better understand context Real time analysis Structured & transactional customer data Ad hoc & retrospective pattern analysis


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6 Corporate Listening - Voice of our customers Identify the right customer for the right product at the right price at the lowest risk to improve revenue and profitability Deal with aggressive and innovative non-bank competitors by leveraging data as an asset Develop new and reliable sources of revenue & increase business value of customer relationship through analytics Incorporate mobile banking as a regular delivery channel & develop a strategy around social media to personalise engagement with customers Achieve & monitor regulatory compliance across Line of Businesses and Business Functions


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7 Big Data & Analytics can be leveraged across multiple areas in the Financial services industry Improving branch & channel efficiency and effectiveness Helping to drive high value, high touch traffic back to branches Customer Centricity Improved targeting of customer segments Moving from a product to customer focus Better management of sales leads across channels Inclusion of customer incentives to influence behaviour Reduce Costs & Increase Revenues Branch, ATM Online, Mobile Omni-channel Channel management & integration Everyone’s Mobile Sentiment analysis Social media analysis Credit analysis Customer profitability & lifetime value Predictive analytics Customer Insight Ability to process increased volume & variety of data Cost effective technology Technology Advancement Risk & capital management, Risk adjusted pricing Portfolio risk management, Fraud/AML Risk & Compliance Management


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8 The Data You Need is Everywhere Around You! Big Data and Analytics Opportunity in Banking


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Big Data and Analytics Opportunity in Retail Banking Breaking Siloes and Analysing Raw Data from Multiple Sources 9 Example Outcomes Profile Contact History Transaction Models Big Data Analytics Customer View Integrated Web Intelligence The Web Visit What searches? How did they get you? Page navigation Research What do they look at? What do they search? Do they dig deeper? Purchase Path Which product? How far into the process? What’s looked at during purchase? Social Media Verbatim Blogs Tweets Postings Reviews Internal Text Data Research Verbatim Ad-hoc Longitudinal studies NPS/Satisfaction Other Direct Contact Branch interview Records Branch Enquiries Manger Notes E-Mails Call Center Queries Complaints Service issues Micro-segmentation Higher Quality Leads Better Fraud Detection More accurate Propensity Models Multi-channel Customer Sentiment


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10 Changing Regulatory Environment Financial organisations’ leverage Big Data Analytics Cost-reduction programmes, de-risking & price adjustments Manage ROI in the new environment Reduce capital and liquidity inefficiency Balance-sheet restructuring Business-model adjustments Achieving compliance with evolving regulatory norms Strategic planning for the BASEL III world Capital & risk strategy Implementation management Challenges Response


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Risk Management Office (RMO) 11 RMO - One stop shop for risk expertise through proactive risk identification, tracking & mitigation of program risk including financial, customer, execution, governance, solution and stakeholder management


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Risk Profiling Big Data Use Cases in Financial Services 12 Business Impact Big Data Capabilities Customer Churn Timely prediction and reduction of churn Include customer contact (e.g. call centre transcripts) & social media data Analyse customer sentiment Model and score churn propensity Cross and Up-selling Efficient and precisely targeted marketing Increased Cross- and Up-sell Analyse & model response behaviour Select campaign addresses based on micro-segmentation Data Offloading Performance & scalability Increased performance and storage Enabled power of analytics on wealth of data Segmentation Client lifestyle analysis and spend prediction Increased customer satisfaction Advanced analytics to enhance client lifestyle analysis and profiling Predictive analysis of spend Domain Comprehensive risk profiling Improved risk evaluation Refine risk profiling models frequently to adapt to dynamic business environment


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Introducing BigDecisions2.0TM 13


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BigDecisions2.0 Business Solution Platform Components providing agile delivery through focused business apps 14 Robust Core Platform Acquire, Manage and Use Any-Data Rapid Value Delivery Flexible, Agile & Economical Relevant Business Apps Intuitive, Focused and Bite-size BI & Analytics


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BigDecisions2.0 Business Solution Platform A new paradigm for seamless, end-to-end information management & analytics value 15 Sophisticated BI & Analytics Leverage Universal Data Select proven Technologies Agility for Business Change Easy to Build and Manage Spend time on BI & Analytics, where it matters most (not on building infrastructure) Manage all-structures of data with Universal Data Management Deliver subject areas in weeks, not in months or years Faster business value realisation with proven set of technology options Install, configure & customize, don’t develop


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Business App | Risk, Fraud & Compliance 16 Executive Dashboards around BASEL II/III and Adaptive Revenue Assurance Machine-learning modules for fraud detection and to strengthen entry to the real-time analytics market Predictive analytics and new features to cover areas in risk and governance prediction Smarter fraud detection capabilities reduce losses and improve recoveries Direct fulfillment of all CRO needs, providing them with business discovery tools and services Proactive risk management across LoBs and product lifecycles with stress testing and scenario analysis RFC Data and Analytics Platform Flexible systems and processes to accommodate changing regulatory requirement Holistic risk assessment, fraud detection and compliance application that ensures adherence to constantly changing regulatory requirement What? App Features Benefits


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Representative Experiences 17 Fraud Detection & Prediction @ Global Payment Processing Company The accuracy of the fraud detection process was improved (~15%) and the speed of >400 million transactions Detect frauds within seconds and predict frauds within 8/16/32/48/72 hrs Enhance fraud detection and prediction algorithm Historical data set was stored in a Hadoop cluster (100+ nodes) Ran several algorithms to prepare clustered data Neural network algorithm was developed Real-time Reporting @ Leading Financial Services Company Response time was significantly improved Substantial performance gains were realised in data service aggregation scenarios by reducing the number of data service calls from RTM PoC for conversion from Cognos to BOBJ Infrastructure – Installed Hadoop, HBase, MySQL Performance tuning NoSQL database for real-time service Big data archive management for cost effective archival and retrieval 20% improvement in lead conversion Operational cost savings of 10 – 20% Greater NPS and customer satisfaction Captured last 55 years of customer data involving 23 Million Customers, 13 Million Policies, 60 Million Claims, 8500 Active Products Segmentation of customers leveraging machine-learning techniques Churn analysis at each individual cluster level with combinations of net-worth, transaction volume and churn rate Customer Segmentation and Churn Prediction @ Leading insurance major


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In Summary 18 BigDecisions Business Solution Platform: A platform-based approach to Universal Data Management with a suite of business ready analytical apps ? ? Big Data and Analytics is a key driver in the financial services sector to help businesses run better & run different ? Start small, think big. ROI on Big Data and Analytics is often too big to ignore


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19 BigDecisionsTM Business Solution Platform http://www.cognizant.com/enterprise-analytics/big-data Thank You


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Big Data Solution Frameworks & Platforms 20 Pave the way to success


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