FNB is optimizing its retail banking product offers using real-time propensity models, rules, and events. Previously, FNB used a legacy mainframe rule engine with several limitations, including insufficient computing power to process customer information daily. FNB implemented IBM Operational Decision Manager and Netezza to aggregate customer data, apply predictive models daily, and produce propensity scores in real-time to filter customers and products and make timely, personalized offers. This new approach enables FNB to seize opportunities through situational awareness and make the right product recommendations to customers at the right time through the most appropriate channels.
Progress Corticon delivers the agility needed to move quickly and stay compliant, while serving the ever-changing needs of businesses.
Progress Corticon separates business rules from code, so both IT and business people can quickly create or modify rules using an intuitive interface. In collaboration with IT, business analysts can identify and deploy automated business rules, freeing IT to focus on innovation.
Accelerating Machine Learning Applications on Spark Using GPUsIBM
Matrix factorization (MF) is widely used in recommendation systems. We present cuMF, a highly-optimized matrix factorization tool with supreme performance on graphics processing units (GPUs) by fully utilizing the GPU compute power and minimizing the overhead of data movement. Firstly, we introduce a memory-optimized alternating least square (ALS) method by reducing discontiguous memory access and aggressively using registers to reduce memory latency. Secondly, we combine data parallelism with model parallelism to scale to multiple GPUs.
Results show that with up to four GPUs on one machine, cuMF can be up to ten times as fast as those on sizable clusters on large scale problems, and has impressively good performance when solving the largest matrix factorization problem ever reported.
ICT Cost Management And Savings General2control4IT
ICT costs are increasigly becoming an issue. This presentation shows option for getting most value out of your ICT at reasonable cost levels. Transparancy in costs and volumes are key.
Progress Corticon delivers the agility needed to move quickly and stay compliant, while serving the ever-changing needs of businesses.
Progress Corticon separates business rules from code, so both IT and business people can quickly create or modify rules using an intuitive interface. In collaboration with IT, business analysts can identify and deploy automated business rules, freeing IT to focus on innovation.
Accelerating Machine Learning Applications on Spark Using GPUsIBM
Matrix factorization (MF) is widely used in recommendation systems. We present cuMF, a highly-optimized matrix factorization tool with supreme performance on graphics processing units (GPUs) by fully utilizing the GPU compute power and minimizing the overhead of data movement. Firstly, we introduce a memory-optimized alternating least square (ALS) method by reducing discontiguous memory access and aggressively using registers to reduce memory latency. Secondly, we combine data parallelism with model parallelism to scale to multiple GPUs.
Results show that with up to four GPUs on one machine, cuMF can be up to ten times as fast as those on sizable clusters on large scale problems, and has impressively good performance when solving the largest matrix factorization problem ever reported.
ICT Cost Management And Savings General2control4IT
ICT costs are increasigly becoming an issue. This presentation shows option for getting most value out of your ICT at reasonable cost levels. Transparancy in costs and volumes are key.
We deliver self funding services in the areas of cost recovery, contract compliance, review and negotiation, and billing optimization for voice, data and wireless communications services.
Moving to the Cloud – Risk, Control, and Accounting ConsiderationsProformative, Inc.
Proformative presents Moving to the Cloud – Risk, Control, and Accounting Considerations. Special thanks to Jane Lin, Deloitte & Touche LLP.
To download full presentation, visit http://bit.ly/9jwNl2
Methodology and strategies for building successful telecom managed servicesParcus Group
Presentation to Juniper Networks Carrier Partners Summit in Bangkok on methodologies and strategies for building successful telecom managed services products.
Dell Direct Model & Virtual Integration
The Dell Direct Model
Dell's award-winning customer service, industry-leading growth and financial performance continue to differentiate the company from competitors. At the heart of that performance is Dell's unique direct-to-customer business model.
"Direct" refers to the company's relationships with its customers, from home-PC users to the world's largest corporations. There are no retailers or other resellers adding unnecessary time and cost, or diminishing Dell's understanding of customer expectations. Why are computer-systems customers and investors increasingly turning to Dell and its unique direct model?
Dell taking maximum benefits from various competitive strategies to counter act the competitive forces prevalent in the PC market.
• Price for Performance. By eliminating resellers, retailers and other costly intermediary steps together with the industry's most efficient procurement, manufacturing and distribution process Dell offers its customers more powerful, more richly configured systems for the money than competitors.
• Customization. Every Dell system is built to order. Customers get exactly, and only, what they want.
• Service and Support. Dell uses knowledge gained from direct contact before and after the sale to provide award-winning, tailored customer service.
• Latest Technology. Dell's efficient model means the latest relevant technology is introduced in its product lines much more quickly than through slow-moving indirect distribution channels. Inventory is turned over every 10 or fewer days, on average, keeping related costs low.
• Superior Shareholder Value. During the last fiscal year, the value of Dell common stocks more than doubled. In 1996 and 1997, Dell was the top-performing stock among the Standard & Poor's 500 and NASDAQ 100, and represented the top-performing U.S. stock on the Dow Jones World Stock Index.
eTOM framework as key component of process reengineering during implementatio...Comarch
E-plus and Comarch presentation during TM Forum Team Action Week in Paris in January 2011 titled: eTOM framework as key component of process reengineering during implementation of Network Planning system
We deliver self funding services in the areas of cost recovery, contract compliance, review and negotiation, and billing optimization for voice, data and wireless communications services.
Moving to the Cloud – Risk, Control, and Accounting ConsiderationsProformative, Inc.
Proformative presents Moving to the Cloud – Risk, Control, and Accounting Considerations. Special thanks to Jane Lin, Deloitte & Touche LLP.
To download full presentation, visit http://bit.ly/9jwNl2
Methodology and strategies for building successful telecom managed servicesParcus Group
Presentation to Juniper Networks Carrier Partners Summit in Bangkok on methodologies and strategies for building successful telecom managed services products.
Dell Direct Model & Virtual Integration
The Dell Direct Model
Dell's award-winning customer service, industry-leading growth and financial performance continue to differentiate the company from competitors. At the heart of that performance is Dell's unique direct-to-customer business model.
"Direct" refers to the company's relationships with its customers, from home-PC users to the world's largest corporations. There are no retailers or other resellers adding unnecessary time and cost, or diminishing Dell's understanding of customer expectations. Why are computer-systems customers and investors increasingly turning to Dell and its unique direct model?
Dell taking maximum benefits from various competitive strategies to counter act the competitive forces prevalent in the PC market.
• Price for Performance. By eliminating resellers, retailers and other costly intermediary steps together with the industry's most efficient procurement, manufacturing and distribution process Dell offers its customers more powerful, more richly configured systems for the money than competitors.
• Customization. Every Dell system is built to order. Customers get exactly, and only, what they want.
• Service and Support. Dell uses knowledge gained from direct contact before and after the sale to provide award-winning, tailored customer service.
• Latest Technology. Dell's efficient model means the latest relevant technology is introduced in its product lines much more quickly than through slow-moving indirect distribution channels. Inventory is turned over every 10 or fewer days, on average, keeping related costs low.
• Superior Shareholder Value. During the last fiscal year, the value of Dell common stocks more than doubled. In 1996 and 1997, Dell was the top-performing stock among the Standard & Poor's 500 and NASDAQ 100, and represented the top-performing U.S. stock on the Dow Jones World Stock Index.
eTOM framework as key component of process reengineering during implementatio...Comarch
E-plus and Comarch presentation during TM Forum Team Action Week in Paris in January 2011 titled: eTOM framework as key component of process reengineering during implementation of Network Planning system
Prediction of house price using multiple regressionvinovk
- Constructed a mathematical model using Multiple Regression to estimate the Selling price of the house based on a set of predictor variables.
- SAS was used for Variable profiling, data transformations, data preparation, regression modeling, fitting data, model diagnostics, and outlier detection.
What are the the main areas of analytics and how can they benefit your business? Learn the value of SAS analytics and how you can get better insight into your data to make more profitable decisions.
By getting a better understanding of your data you will know which part of the data can be reliably forecast using time series methods and which cannot. You will also gain an understanding of any hierarchical structure in the data that can be used.
Presentation at SAS Analytics conference 2014
Predictive analytics has been applied to solve a wide range of real-world problems. Nevertheless, current state-of-the-art predictive analytics models are not well aligned with business needs since they don't include the real financial costs and benefits during the training and evaluation phases. Churn modeling does not yield the best results when it's measured by investment per subscriber on a loyalty campaign and the financial impact of failing to detect a churner versus wrongly predicting a non-churner. This presentation will show how using a cost-sensitive modeling approach leads to better results in terms of profitability and predictive power – and is applicable to many other business challenges.
Credit card fraud is a growing problem that affects card holders around the world. Fraud detection has been an interesting topic in machine learning. Nevertheless, current state of the art credit card fraud detection algorithms miss to include the real costs of credit card fraud as a measure to evaluate algorithms. In this paper a new comparison measure that realistically represents the monetary gains and losses due to fraud detection is proposed. Moreover, using the proposed cost measure a cost sensitive method based on Bayes minimum risk is presented. This method is compared with state of the art algorithms and shows improvements up to 23% measured by cost. The results of this paper are based on real life transactional data provided by a large European card processing company.
How to embrace digital transformation in the Financial Services sectorBrandworkz
Digital has the power to transform business. Businesses in every sector are starting to go through a digital transformation. The Financial Services sector particularly is waking up to the potential of digital to integrate and streamline the entire business process. This slideshare offers insights from industry experts and tips for how to achieve digital transformation success if you are in Financial Services.
The Next Stage of Fraud Protection: IBM Security Trusteer Fraud Protection SuiteIBM Security
View on-demand webinar:
http://event.on24.com/wcc/r/1155218/416359D28E2D43ACB417A8C7C097B3B8
Introducing the Next-Generation Fraud Protection Suite
The financial services industry continues to be plagued by advanced fraud attacks. Sometimes the attacks are successful, resulting in tremendous fraud losses. Virtually always, financial institutions invest significant time and resources to address this continued cyberfraud risk. The fraud protection solutions cobbled together over the past decade suffer from several shortcomings:
Accuracy – statistical risk models generate high false positive alerts, often missing actual fraud
Adaptability – inflexible solutions cannot (or are slow to) react to new threats and new attack methods
Affordability – disparate systems do not leverage pricing incentives and system updates/modifications can be very expensive
Approval – customers are needlessly disrupted by inaccurate risk assessments and the online channel is sub-optimized due to risk concerns
View this on-demand webinar to learn the more about how IBM has taken a fundamentally different approach to fraud protection and management. The IBM Security Trusteer Fraud Protection Suite provides
Evidence-based fraud detection – reduce false positives and missed fraud, leading to better customer experience
Threat-aware authentication – based on actual risk for rapid enforcement
Advanced case management and reporting capabilities – streamline investigations and threat analysis
A powerful remediation tool – quickly remove existing financial malware from infected endpoints
The MUFG Union Bank (MUB) Transaction Banking Department undertook a multi-year initiative to shorten new customer onboarding time with the ultimate goal of business growth. During this initiative, MUB captured a myriad of data. Now that the initial foundation is set, the real fun begins. This data provides newfound visibility into MUB’s processes that will propel it from a position of catch-up to market leader. The solution fueling its accelerated growth puts relevant information in the palm of every user’s hand.
Complete Solutions in ECM using IBM, Internal and Third Party, Custom ComponentsPyramid Solutions, Inc.
Pyramid Solutions showcased how real-world customers have used IBM Content Navigator and IBM Case Manager to develop solutions that can be applied to the entire enterprise. Using the extendibility of Content Navigator has allowed customers to use custom components that were developed in-house in conjunction with third-party and OOTB components to develop complete solutions to meet the users’ needs. This session examines how custom components can be built and combined with third-party and IBM products. It also examines the flexibility of component design that enables flexible interfaces that can be used across content and case management solutions without the need to develop separate components.
Capgemini Connected Car Demo Using IBM Internet of Things Foundation on BluemixCapgemini
Does the buzz about IBM Internet of Things (IoT) and Bluemix makes you curious to see some real-world demos and implementations?
IBM and Capgemini are going to show you the future of vehicle technology, focusing on different ways in which vehicles can be connected using IoT and IBM Bluemix. We’ll demo an app named “Follow your Friend” that lets you connect with and exchange GPS positions with other vehicles.
We’ll also demo “Geofence” for location-based marketing: it knows about the drivers’ needs as they drive and informs retailers about potential customers, so they can push offers to their customer’s vehicle devices (or mobile devices) as they drive by.
Presented at IBM InterConnect 2015 by Capgemini's Avinash Vaidya.
Unifying the Silos: Optimize your Data Pipeline for Analytics and AIDataWorks Summit
Discover how to break apart the modern data analytics workflow to focus on the data challenges across different phases of the analytics and AI lifecycle. By taking an end-to-end data pipeline view while adopting storage technologies for AI and analytics, your organization can reduce costs, modernize your data strategy and improve data governance. By anticipating how Hadoop, Spark, Tensorflow, Caffe and traditional analytics like SAS can share data, IT departments and data science practitioners can not only coexist, but also speed time to insight. You'll also learn the tangible benefits of a reference architecture using real-world installations that span proprietary and open source frameworks.
Making People Flow in Cities Measurable and AnalyzableWeiwei Yang
Millions of people move to large cities every day. What if we make the people flow measurable and analyzable? This would be of great value for city traffic planning, real time monitoring of hot areas and for targeted advertising. This capability exists by leveraging and combining Apache Spark streaming, Spark SQL, Spark batch processing, plus DB2 with BLU Acceleration. Spark provides powerful stream and batch processing on big data, and BLU Acceleration enhances the ability of complex analytics on multiple dimensions. Learn how BLU Acceleration and Spark are integrated seamlessly into one solution. This session will also show a demo that is based on a large city in China.
World of Watson - Integrating IBM Watson IOT Platform and IBM BlockchainRahul Gupta
In this hands-on lab, you will deploy smart contracts for IoT in IBM Blockchain, and connect MQTT devices to send IoT data to the blockchain using the IBM Watson IoT Platform. In an IoT context, data comes from "things" to private blockchain ledgers for inclusion in shared transactions with tamper-resistant records. Attend this lab and start creating a more efficient business network with the IBM Watson IoT Platform and IBM Blockchain.
4515 Modernize your CICS applications for Mobile and Cloudnick_garrod
InterConnect 2015 session 4515 Modernize your CICS applications for Mobile and Cloud. There’s a lot more to mobile than JSON and REST and this session will take you on a tour of what else is needed to ensure a smooth ride when building, testing, and deploying CICS mobile workloads. Whether identifying mobile entry points, managing frequent configuration changes, planning and validating performance, or enabling mobile applications for world-wide usage, IBM z/OS Tools help all DevOps roles. You’ll also learn how the same tools can also help you to use the CICS cloud to meet the need for speed of mobile apps.
Pleasure to present this introduction to IBM cognitive business to business leaders in Hamilton, Ontario. Covers: what cognitive computing is, how businesses are using it to their advantage, and steps to getting started. Includes links to videos "IBM Today" and "IBM Woodside Energy".
Adapted from Nancy Pearson, VP Cognitive Business Marketing "Intelligent enterprise: Cognitive Business" presentation from World of Watson Oct 2016.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Fnb optimizes retail banking product offers using real-time propensity models rules and events - Avsharn Bachoo
1. FNB Optimizes Retail Banking
Product Offers
Using Real-Time Propensity Models, Rules and Events
Avsharn Bachoo – FNB
Vincent Baruchello - IBM
2. First National Bank
• The oldest bank in South Africa formed in 1838
• Listed on the South African Stock Exchange and the Namibian Stock Exchange
• One of the largest financial institutions in South Africa
• Providing banking and insurance to retail, commercial, corporate and public
sector customers
1
3. Product Sales Initiatives
• Proactive sales, service and prospecting system.
• Used to assess the eligibly customer base for a variety of
– product offers,
– value adds, and
– service related messages.
• The process caters for both a fully automated eligibility process via
– mainframe leads process,
– adhoc load capability.
2
4. Integrating decisioning capabilities
Domain with engine
3
Mainframe
Legacy
Rule
Engine
Business rules
Policy Rules
JCL call to DA
Java API
JMS
SOA/Web Service call
Enterprise Service Bus
Mainframe
5. Limitations
• Legacy rule engine not integrated into mainframe and no direct link to
warehouse
• Insufficient computing power to process information daily
4
Developers Mainframe
Legacy
Engine
Data
warehouse
30 day data gathering
2 day-long batch scoring
7. Limitations
• Customer needs change on a daily basis
• Updates to customer information takes place monthly
• Propensity scores derived monthly
• Missing the window of opportunity for getting offers to the customers at
the right time.
6
8. Business Expectations
• Enable decisions to be made
– real-time
– leveraging of
• internal models,
• advanced statistical models &
• predictive analytics
Right Product @ Right Place & Right Time
7
9. Technical expectations
• Aggregate large volumes of data and derive variables
• Adaptive to seamlessly fit into the existing complex FNB architecture
• Solution needed the capability for current and future integration into
FNB’s
– Warehouse’s
– Data mining systems
8
10. Selection Criteria
9
Product Technology environment Interface Seamless Integration with
FNB mainframe
FICO Blaze Advisor JVM or .NET Proprietary API or Web
Service
Message switch
IBM ODM zOS, JVM Cobol, XML and JAVA API Direct
Jboss Enterprise BRMS Jboss Middleware JAVA API Message switch
Apama JVM or .NET JAVA, C, C++, .NET Message switch
Experian Powercurve JVM JAVA, C Message switch
SAP NetWeaver JVM JAVA, ABAP Message switch
Oracle Business Rules Oracle Fusion Middleware XML, JAVA or Oracle Message switch
11. ODM and Netezza 2016-future
10
Find leads
using changes
in Customer
activity
(Events)
Optimise Leads
Right time
communication
to customer
12. Systems of Records
Systems of
Engagements
Delivering through an event-driven architecture
11
Web Social
Detect
Decide
Systems of Insights
Mobile IoT
ATM
Branch
Mail
Event
Situational
Awareness
Predictive
Models
13. Netezza
Analytics
Systems of Records
Operational Decisions
(z / cloud / distributed)
Combining rules and analytics
12
Instant decision
Predictive
Scores
Business
Interaction
event
transaction
Situational
Awareness
Automated
Services
Timely event
14. ODM and Netezza
Conceptual Architecture
13
Netezza
ODM
• Aggregate customer base information
• Cleans information
• Apply models to daily information
• Produces scores
• Dump scores
• Rules filter customers & products
• Makes recommendations, bundling
products
• Decide when & how (channels)
15. Seizing opportunities through situational awareness
14
Process
Rule
Servi
ce
Channels
High fidelity,
granular actions
Millions of Customers
Loan Applicant
…
Millions of
interactions
Hundreds of
Aggregates
Thousands
of Rules
Dozens
of Models
Applying Insights to simplify creating personalized,
customer-specific actions at the time of interaction
Decision Management in context
IBMDecisionServer Insights
16. Processes
System of Records
Social Media
Sensors
Data Warehouse
Business Events
Situation Detection & Action
Information Bus
Mobile Devices
System of Engagement
Four Steps toward decision making in context
18. Expected Benefits
• Make offers at the right time
• Improve relationship with customers
• Increase likelihood of sales by offering tailored products geared to
specific customer needs
– personalized offers to the customer
• Continuous improvement by
– analyzing customer data,
– monitoring transactions,
– determining patterns
– to make the right offer at the right time in a dynamic fashion
17
19. Lessons Learnt
• Technical:
– No major issues experienced
– Compatibility issue: ODM and Netezza ran different versions of Java
• Business:
– No yardstick to plan effort
– More focus on Java skill set for new recruits
18
21. Notices and Disclaimers Con’t.
20
Information concerning non-IBM products was obtained from the suppliers of those products, their published announcements or other publicly available sources. IBM has not
tested those products in connection with this publication and cannot confirm the accuracy of performance, compatibility or any other claims related to non-IBM products.
Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products. IBM does not warrant the quality of any third-party products, or the
ability of any such third-party products to interoperate with IBM’s products. IBM EXPRESSLY DISCLAIMS ALL WARRANTIES, EXPRESSED OR IMPLIED, INCLUDING BUT
NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
The provision of the information contained h erein is not intended to, and does not, grant any right or license under any IBM patents, copyrights, trademarks or other intellectual
property right.
IBM, the IBM logo, ibm.com, Aspera®, Bluemix, Blueworks Live, CICS, Clearcase, Cognos®, DOORS®, Emptoris®, Enterprise Document Management System™, FASP®,
FileNet®, Global Business Services ®, Global Technology Services ®, IBM ExperienceOne™, IBM SmartCloud®, IBM Social Business®, Information on Demand, ILOG,
Maximo®, MQIntegrator®, MQSeries®, Netcool®, OMEGAMON, OpenPower, PureAnalytics™, PureApplication®, pureCluster™, PureCoverage®, PureData®,
PureExperience®, PureFlex®, pureQuery®, pureScale®, PureSystems®, QRadar®, Rational®, Rhapsody®, Smarter Commerce®, SoDA, SPSS, Sterling Commerce®,
StoredIQ, Tealeaf®, Tivoli®, Trusteer®, Unica®, urban{code}®, Watson, WebSphere®, Worklight®, X-Force® and System z® Z/OS, are trademarks of International Business
Machines Corporation, registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM
trademarks is available on the Web at "Copyright and trademark information" at: www.ibm.com/legal/copytrade.shtml.
22. Thank You
Your Feedback is Important!
Access the InterConnect 2016 Conference Attendee
Portal to complete your session surveys from your
smartphone,
laptop or conference kiosk.
Editor's Notes
No computing power to process daily
Added propensity models, next best offer, next best action
IBM Decision Server Insights is new innovation we’re bringing into our ODM portfolio. It enables high fidelity, real-time granular and specific actions be taken given a very changing environment.
Whether your customer is a patient, a loan applicant or an insurance policy holder, Decision Server Insights has the ability to make sense of the millions of interactions that happen across channels and take specific action in real-time.
This is made possible by a really cool concept called Aggregates – it helps synthesize millions of interactions down into data that can be fed into scoring models in real-time. The result is a number of immediately actionable business rules that provide personalized, customer specific actions.
This is a great example of a case where a truly complex environment is drastically simplified, yet leading to customer-centric results.
Key points about Decision Server Insights:
Provides incremental capability for our ODM customers; it builds on skills that customers acquire as they work with ODM.
Addresses clients’ need for stateful real-time situational context for decision automation.
Allows clients to sense changing business conditions and respond to them with predetermined actions.
React at the right time and place to business opportunities and risks, such as
detecting and preventing fraud,
sending targeted marketing messages,
threats to people and equipment,
By aggregating events correlated with business entities across all channels
And applying policy rules and predictive models to trigger an appropriate response, such as
alerting people
triggering processes
opening cases
logging data for subsequent analysis.
Sense: Captures meaningful events across all channels, systems and devices
Build: Put data and events into context to understand and evaluate how everything relates
Decide: Apply the models, policies and best practices established by your subject matter experts
Act: Initiates and consistently Automates the next best action