Risk Scoring For A Loan Application On Ibm System Z

Author : Mike Ebbers,Keith Doan,Andrew Flatt,IBM Redbooks
Publisher : IBM Redbooks
Page : 102 pages
File Size : 46,7 Mb
Release : 2013-10-02
Category : Computers
ISBN : 9780738438849

Get Book

Risk Scoring for a Loan Application on IBM System z: Running IBM SPSS Real-Time Analytics by Mike Ebbers,Keith Doan,Andrew Flatt,IBM Redbooks Pdf

When ricocheting a solution that involves analytics, the mainframe might not be the first platform that comes to mind. However, the IBM® System z® group has developed some innovative solutions that include the well-respected mainframe benefits. This book describes a workshop that demonstrates the use of real-time advanced analytics for enhancing core banking decisions using a loan origination example. The workshop is a live hands-on experience of the entire process from analytics modeling to deployment of real-time scoring services for use on IBM z/OS®. In this IBM Redbooks® publication, we include a facilitator guide chapter as well as a participant guide chapter. The facilitator guide includes information about the preparation, such as the needed material, resources, and steps to set up and run this workshop. The participant guide shows step-by-step the tasks for a successful learning experience. The goal of the first hands-on exercise is to learn how to use IBM SPSS® Modeler for Analytics modeling. This provides the basis for the next exercise "Configuring risk assessment in SPSS Decision Management". In the third exercise, the participant experiences how real-time scoring can be implemented on a System z. This publication is written for consultants, IT architects, and IT administrators who want to become familiar with SPSS and analytics solutions on the System z.

Author : Mike Ebbers,Keith Doan,Andrew Flatt
Publisher : Unknown
Page : 102 pages
File Size : 53,7 Mb
Release : 2013
Category : Data mining
ISBN : OCLC:1105765751

Get Book

Risk Scoring for a Loan Application on IBM System Z by Mike Ebbers,Keith Doan,Andrew Flatt Pdf

When ricocheting a solution that involves analytics, the mainframe might not be the first platform that comes to mind. However, the IBM® System z® group has developed some innovative solutions that include the well-respected mainframe benefits. This book describes a workshop that demonstrates the use of real-time advanced analytics for enhancing core banking decisions using a loan origination example. The workshop is a live hands-on experience of the entire process from analytics modeling to deployment of real-time scoring services for use on IBM z/OS®. In this IBM Redbooks® publication, we include a facilitator guide chapter as well as a participant guide chapter. The facilitator guide includes information about the preparation, such as the needed material, resources, and steps to set up and run this workshop. The participant guide shows step-by-step the tasks for a successful learning experience. The goal of the first hands-on exercise is to learn how to use IBM SPSS® Modeler for Analytics modeling. This provides the basis for the next exercise "Configuring risk assessment in SPSS Decision Management". In the third exercise, the participant experiences how real-time scoring can be implemented on a System z. This publication is written for consultants, IT architects, and IT administrators who want to become familiar with SPSS and analytics solutions on the System z.

Author : Lydia Parziale,Oliver Benke,Willie Favero,Ravi Kumar,Steven LaFalce,Cedrine Madera,Sebastian Muszytowski,IBM Redbooks
Publisher : IBM Redbooks
Page : 214 pages
File Size : 54,8 Mb
Release : 2016-08-08
Category : Computers
ISBN : 9780738441863

Get Book

Enabling Real-time Analytics on IBM z Systems Platform by Lydia Parziale,Oliver Benke,Willie Favero,Ravi Kumar,Steven LaFalce,Cedrine Madera,Sebastian Muszytowski,IBM Redbooks Pdf

Regarding online transaction processing (OLTP) workloads, IBM® z SystemsTM platform, with IBM DB2®, data sharing, Workload Manager (WLM), geoplex, and other high-end features, is the widely acknowledged leader. Most customers now integrate business analytics with OLTP by running, for example, scoring functions from transactional context for real-time analytics or by applying machine-learning algorithms on enterprise data that is kept on the mainframe. As a result, IBM adds investment so clients can keep the complete lifecycle for data analysis, modeling, and scoring on z Systems control in a cost-efficient way, keeping the qualities of services in availability, security, reliability that z Systems solutions offer. Because of the changed architecture and tighter integration, IBM has shown, in a customer proof-of-concept, that a particular client was able to achieve an orders-of-magnitude improvement in performance, allowing that client's data scientist to investigate the data in a more interactive process. Open technologies, such as Predictive Model Markup Language (PMML) can help customers update single components instead of being forced to replace everything at once. As a result, you have the possibility to combine your preferred tool for model generation (such as SAS Enterprise Miner or IBM SPSS® Modeler) with a different technology for model scoring (such as Zementis, a company focused on PMML scoring). IBM SPSS Modeler is a leading data mining workbench that can apply various algorithms in data preparation, cleansing, statistics, visualization, machine learning, and predictive analytics. It has over 20 years of experience and continued development, and is integrated with z Systems. With IBM DB2 Analytics Accelerator 5.1 and SPSS Modeler 17.1, the possibility exists to do the complete predictive model creation including data transformation within DB2 Analytics Accelerator. So, instead of moving the data to a distributed environment, algorithms can be pushed to the data, using cost-efficient DB2 Accelerator for the required resource-intensive operations. This IBM Redbooks® publication explains the overall z Systems architecture, how the components can be installed and customized, how the new IBM DB2 Analytics Accelerator loader can help efficient data loading for z Systems data and external data, how in-database transformation, in-database modeling, and in-transactional real-time scoring can be used, and what other related technologies are available. This book is intended for technical specialists and architects, and data scientists who want to use the technology on the z Systems platform. Most of the technologies described in this book require IBM DB2 for z/OS®. For acceleration of the data investigation, data transformation, and data modeling process, DB2 Analytics Accelerator is required. Most value can be achieved if most of the data already resides on z Systems platforms, although adding external data (like from social sources) poses no problem at all.

Author : Jasmeet Bhatia,Ravi Gummadi,Chandra Shekhar Reddy Potula,Srirama Sharma,IBM Redbooks
Publisher : IBM Redbooks
Page : 40 pages
File Size : 41,6 Mb
Release : 2023-07-11
Category : Computers
ISBN : 9780738461069

Get Book

IBM Cloud Pak for Data on IBM Z by Jasmeet Bhatia,Ravi Gummadi,Chandra Shekhar Reddy Potula,Srirama Sharma,IBM Redbooks Pdf

Most industries are susceptible to fraud, which poses a risk to both businesses and consumers. According to The National Health Care Anti-Fraud Association, health care fraud alone causes the nation around $68 billion annually. This statistic does not include the numerous other industries where fraudulent activities occur daily. In addition, the growing amount of data that enterprises own makes it difficult for them to detect fraud. Businesses can benefit by using an analytical platform to fully integrate their data with artificial intelligence (AI) technology. With IBM Cloud Pak® for Data on IBM Z, enterprises can modernize their data infrastructure, develop, and deploy machine learning (ML) and AI models, and instantiate highly efficient analytics deployment on IBM LinuxONE. Enterprises can create cutting-edge, intelligent, and interactive applications with embedded AI, colocate data with commercial applications, and use AI to make inferences. This IBM Redguide publication presents a high-level overview of IBM Z. It describes IBM Cloud Pak for Data (CP4D) on IBM Z and IBM LinuxONE, the different features that are supported on the platform, and how the associated features can help enterprise customers in building AI and ML models by using core transactional data, which results in decreased latency and increased throughput. This publication highlights real-time CP4D on IBM Z use cases. Real-time Clearing and Settlement Transactions, Trustworthy AI and its Role in Day-To-Day Monitoring, and the Prevention of Retail Crimes are use cases that are described in this publication. Using CP4D on IBM Z and LinuxONE, this publication shows how businesses can implement a highly efficient analytics deployment that minimizes latency, cost inefficiencies, and potential security exposures that are connected with data transportation.

Author : Lydia Parziale,Joe Bostian,Ravi Kumar,Ulrich Seelbach,Zhong Yu Ye,IBM Redbooks
Publisher : IBM Redbooks
Page : 142 pages
File Size : 52,6 Mb
Release : 2016-08-13
Category : Computers
ISBN : 9780738414966

Get Book

Apache Spark Implementation on IBM z/OS by Lydia Parziale,Joe Bostian,Ravi Kumar,Ulrich Seelbach,Zhong Yu Ye,IBM Redbooks Pdf

The term big data refers to extremely large sets of data that are analyzed to reveal insights, such as patterns, trends, and associations. The algorithms that analyze this data to provide these insights must extract value from a wide range of data sources, including business data and live, streaming, social media data. However, the real value of these insights comes from their timeliness. Rapid delivery of insights enables anyone (not only data scientists) to make effective decisions, applying deep intelligence to every enterprise application. Apache Spark is an integrated analytics framework and runtime to accelerate and simplify algorithm development, depoyment, and realization of business insight from analytics. Apache Spark on IBM® z/OS® puts the open source engine, augmented with unique differentiated features, built specifically for data science, where big data resides. This IBM Redbooks® publication describes the installation and configuration of IBM z/OS Platform for Apache Spark for field teams and clients. Additionally, it includes examples of business analytics scenarios.

Author : Mike Johnson,Chris Backhouse,Stéphane Faure,David Griffiths,Yann Kindelberger,Ke Wei Wei,Hao Zhang,IBM Redbooks
Publisher : IBM Redbooks
Page : 44 pages
File Size : 48,8 Mb
Release : 2019-12-11
Category : Computers
ISBN : 9780738456928

Get Book

Machine Learning with Business Rules on IBM Z: Acting on Your Insights by Mike Johnson,Chris Backhouse,Stéphane Faure,David Griffiths,Yann Kindelberger,Ke Wei Wei,Hao Zhang,IBM Redbooks Pdf

This Redpaper introduces the integration between two IBM products that you might like to consider when implementing a modern agile solution on your Z systems. The document briefly introduces Operational Decision Manager on z/OS and Machine learning on z/OS. In the case of Machine Learning we focus on the aspect of real-time scoring models and how these can be used with Business Rules to give better decisions. Note: Important changes since this document was written: This document was written for an older release of Operational Decision Manager for z/OS (ODM for z/OS). ODM for z/OS 8.9.1 required the writing of custom Java code to access a Watson Machine Learning for z/OS Scoring Service (this can be seen in ). Since that time ODM for z/OS version 8.10.1 has been released and much improves the integration experience. Integrating the two products no longer requires custom Java code. Using ODM for z/OS 8.10.1 or later you can use an automated wizard in the ODM tooling to: Browse and select a model from Watson Machine Learning Import the Machine Learning data model into your rule project Automatically generate a template rule that integrates a call to the Watson Machine Learning scoring service Download and read this document for: Individual introductions to ODM for z/OS and Machine learning Discussions on the benefits of using the two technologies together Information on integrating if you have not yet updated to ODM for z/OS 8.10.1 For information about the machine learning integration in ODM for z/OS 8.10.1 see IBM Watson Machine Learning for z/OS integration topic in the ODM for z/OS 8.10.x Knowledge Center

Author : Samantha Buhler,Guanjun Cai,John Goodyear,Edrian Irizarry,Nora Kissari,Zhuo Ling,Nicholas Marion,Aleksandr Petrov,Junfei Shen,Wanting Wang,He Sheng Yang,Dai Yi,Xavier Yuen,Hao Zhang,IBM Redbooks
Publisher : IBM Redbooks
Page : 180 pages
File Size : 51,9 Mb
Release : 2018-09-11
Category : Computers
ISBN : 9780738457130

Get Book

Turning Data into Insight with IBM Machine Learning for z/OS by Samantha Buhler,Guanjun Cai,John Goodyear,Edrian Irizarry,Nora Kissari,Zhuo Ling,Nicholas Marion,Aleksandr Petrov,Junfei Shen,Wanting Wang,He Sheng Yang,Dai Yi,Xavier Yuen,Hao Zhang,IBM Redbooks Pdf

The exponential growth in data over the last decade coupled with a drastic drop in cost of storage has enabled organizations to amass a large amount of data. This vast data becomes the new natural resource that these organizations must tap in to innovate and stay ahead of the competition, and they must do so in a secure environment that protects the data throughout its lifecyle and data access in real time at any time. When it comes to security, nothing can rival IBM® Z, the multi-workload transactional platform that powers the core business processes of the majority of the Fortune 500 enterprises with unmatched security, availability, reliability, and scalability. With core transactions and data originating on IBM Z, it simply makes sense for analytics to exist and run on the same platform. For years, some businesses chose to move their sensitive data off IBM Z to platforms that include data lakes, Hadoop, and warehouses for analytics processing. However, the massive growth of digital data, the punishing cost of security exposures as well as the unprecedented demand for instant actionable intelligence from data in real time have convinced them to rethink that decision and, instead, embrace the strategy of data gravity for analytics. At the core of data gravity is the conviction that analytics must exist and run where the data resides. An IBM client eloquently compares this change in analytics strategy to a shift from "moving the ocean to the boat to moving the boat to the ocean," where the boat is the analytics and the ocean is the data. IBM respects and invests heavily on data gravity because it recognizes the tremendous benefits that data gravity can deliver to you, including reduced cost and minimized security risks. IBM Machine Learning for z/OS® is one of the offerings that decidedly move analytics to Z where your mission-critical data resides. In the inherently secure Z environment, your machine learning scoring services can co-exist with your transactional applications and data, supporting high throughput and minimizing response time while delivering consistent service level agreements (SLAs). This book introduces Machine Learning for z/OS version 1.1.0 and describes its unique value proposition. It provides step-by-step guidance for you to get started with the program, including best practices for capacity planning, installation and configuration, administration and operation. Through a retail example, the book shows how you can use the versatile and intuitive web user interface to quickly train, build, evaluate, and deploy a model. Most importantly, it examines use cases across industries to illustrate how you can easily turn your massive data into valuable insights with Machine Learning for z/OS.

Author : Chris Rayns,Neil Ashworth,Peter Beevers,Vesna Eibel,Fabrice Jarassat,Claus T Jensen,Alison Lucas,Anthony Papageorgiou,Alain Roessle,Nigel Williams,IBM Redbooks
Publisher : IBM Redbooks
Page : 210 pages
File Size : 52,6 Mb
Release : 2010-04-22
Category : Computers
ISBN : 9780738434124

Get Book

Smarter Banking with CICS Transaction Server by Chris Rayns,Neil Ashworth,Peter Beevers,Vesna Eibel,Fabrice Jarassat,Claus T Jensen,Alison Lucas,Anthony Papageorgiou,Alain Roessle,Nigel Williams,IBM Redbooks Pdf

It goes without saying that 2009 was a year of unprecedented change in global banking. The challenges that financial institutions are facing require them to cut costs but also to regain trust and improve the service that they provide to an increasingly sophisticated and demanding set of customers. In the past, siloed and rigid IT systems often inhibited banks in their attempts to re-engineer their business processes. The IBM® smarter banking initiative highlights how more intelligent software can be used to significantly improve the end-to-end integration of banking processes. In this IBM Redbooks® publication, we aim to show how software technologies, such as SOA, Web 2.0 and event driven architectures, can be used to implement smarter banking solutions. Our focus is on CICS® Transaction Server, which is at the heart of most bank's core banking implementations.

Author : Richard A. Brealey,Stewart C. Myers,Stewart Myers
Publisher : McGraw Hill Professional
Page : 498 pages
File Size : 49,9 Mb
Release : 2003
Category : Business & Economics
ISBN : 0071383786

Get Book

Financing and Risk Management by Richard A. Brealey,Stewart C. Myers,Stewart Myers Pdf

The features of this text include: the six lessons of market efficiency; patterns of corporate financing; stockholders' rights; convertible securities; duration and volatility of debt; hedging with futures; debt borrowing issues; and risk management, both domestic and international.

Author : Axel Buecker,Michael Cairns,Monique Conway,Mark S. Hahn,Deborah McLemore,Jamie Pease,Lili Xie,IBM Redbooks
Publisher : IBM Redbooks
Page : 494 pages
File Size : 47,5 Mb
Release : 2011-08-18
Category : Computers
ISBN : 9780738435886

Get Book

IBM z/OS Mainframe Security and Audit Management Using the IBM Security zSecure Suite by Axel Buecker,Michael Cairns,Monique Conway,Mark S. Hahn,Deborah McLemore,Jamie Pease,Lili Xie,IBM Redbooks Pdf

Every organization has a core set of mission-critical data that must be protected. Security lapses and failures are not simply disruptions—they can be catastrophic events, and the consequences can be felt across the entire organization. As a result, security administrators face serious challenges in protecting the company's sensitive data. IT staff are challenged to provide detailed audit and controls documentation at a time when they are already facing increasing demands on their time, due to events such as mergers, reorganizations, and other changes. Many organizations do not have enough experienced mainframe security administrators to meet these objectives, and expanding employee skillsets with low-level mainframe security technologies can be time-consuming. The IBM® Security zSecure suite consists of multiple components designed to help you administer your mainframe security server, monitor for threats, audit usage and configurations, and enforce policy compliance. Administration, provisioning, and management components can significantly reduce administration, contributing to improved productivity, faster response time, and reduced training time needed for new administrators. This IBM Redbooks® publication is a valuable resource for security officers, administrators, and architects who wish to better understand their mainframe security solutions.

Author : Richard A. Brealey,Stewart C. Myers
Publisher : Unknown
Page : 1132 pages
File Size : 45,7 Mb
Release : 1999-07
Category : Electronic
ISBN : 0072352353

Get Book

Priniciples of Corporate Finance by Richard A. Brealey,Stewart C. Myers Pdf

Author : Makenzie Manna,Erhan Mengusoglu,Artem Minin,Krishna Teja Rekapalli,Thomas Rüter,Pia Velazco,Markus Wolff,IBM Redbooks
Publisher : IBM Redbooks
Page : 128 pages
File Size : 55,6 Mb
Release : 2022-11-30
Category : Computers
ISBN : 9780738460925

Get Book

Optimized Inferencing and Integration with AI on IBM zSystems: Introduction, Methodology, and Use Cases by Makenzie Manna,Erhan Mengusoglu,Artem Minin,Krishna Teja Rekapalli,Thomas Rüter,Pia Velazco,Markus Wolff,IBM Redbooks Pdf

In today's fast-paced, ever-growing digital world, you face various new and complex business problems. To help resolve these problems, enterprises are embedding artificial intelligence (AI) into their mission-critical business processes and applications to help improve operations, optimize performance, personalize the user experience, and differentiate themselves from the competition. Furthermore, the use of AI on the IBM® zSystems platform, where your mission-critical transactions, data, and applications are installed, is a key aspect of modernizing business-critical applications while maintaining strict service-level agreements (SLAs) and security requirements. This colocation of data and AI empowers your enterprise to optimally and easily deploy and infuse AI capabilities into your enterprise workloads with the most recent and relevant data available in real time, which enables a more transparent, accurate, and dependable AI experience. This IBM Redpaper publication introduces and explains AI technologies and hardware optimizations, and demonstrates how to leverage certain capabilities and components to enable AI solutions in business-critical use cases, such as fraud detection and credit risk scoring, on the platform. Real-time inferencing with AI models, a capability that is critical to certain industries and use cases, now can be implemented with optimized performance thanks to innovations like IBM zSystems Integrated Accelerator for AI embedded in the Telum chip within IBM z16TM. This publication describes and demonstrates the implementation and integration of the two end-to-end solutions (fraud detection and credit risk), from developing and training the AI models to deploying the models in an IBM z/OS® V2R5 environment on IBM z16 hardware, and integrating AI functions into an application, for example an IBM z/OS Customer Information Control System (IBM CICS®) application. We describe performance optimization recommendations and considerations when leveraging AI technology on the IBM zSystems platform, including optimizations for micro-batching in IBM Watson® Machine Learning for z/OS. The benefits that are derived from the solutions also are described in detail, including how the open-source AI framework portability of the IBM zSystems platform enables model development and training to be done anywhere, including on IBM zSystems, and enables easy integration to deploy on IBM zSystems for optimal inferencing. Thus, allowing enterprises to uncover insights at the transaction-level while taking advantage of the speed, depth, and securability of the platform. This publication is intended for technical specialists, site reliability engineers, architects, system programmers, and systems engineers. Technologies that are covered include TensorFlow Serving, WMLz, IBM Cloud Pak® for Data (CP4D), IBM z/OS Container Extensions (zCX), IBM CICS, Open Neural Network Exchange (ONNX), and IBM Deep Learning Compiler (zDLC).

Author : Anonim
Publisher : Unknown
Page : 902 pages
File Size : 47,5 Mb
Release : 2007
Category : Housing
ISBN : UCLA:L0098876733

Get Book

Mortgage Banking by Anonim Pdf

Author : IBM Client Center Montpellier,Nigel Williams,Olivier Boehler,Philippe Bruschet,Francois Capristo,Alexis Chretienne,Stéphane Faure,Richard Gamblin,Fabrice Jarassat,Arnaud Mante,Irene Stahl,IBM Redbooks
Publisher : IBM Redbooks
Page : 78 pages
File Size : 47,5 Mb
Release : 2016-10-25
Category : Computers
ISBN : 9780738455501

Get Book

Using IBM z/OS WLM to Measure Mobile and Other Workloads by IBM Client Center Montpellier,Nigel Williams,Olivier Boehler,Philippe Bruschet,Francois Capristo,Alexis Chretienne,Stéphane Faure,Richard Gamblin,Fabrice Jarassat,Arnaud Mante,Irene Stahl,IBM Redbooks Pdf

This IBM® RedpaperTM publication discusses the need to monitor and measure different workloads, especially mobile workloads. It introduces the workload classification capabilities of IBM z SystemsTM platforms and helps you to understand how recent enhancements to IBM MVSTM Workload Management (WLM) and other IBM software products can be used to measure the processor cost of mobile workloads. This paper looks at how mobile-initiated and other transactions in IBM CICS®, IMSTM, DB2®, and WebSphere® Application Server can be "tagged and tracked" using WLM. For each of these subsystems, the options for classifying mobile requests and using WLM to measure mobile workloads are reviewed. A scenario is considered in which a bank is witnessing a significant growth in mobile initiated transactions, and wants to monitor and measure the mobile channels more closely. This paper outlines how the bank can use WLM to do this. This publication can help you to configure WLM mobile classification rules. It can also help you to interpret Workload Activity reports from IBM RMFTM Post Processor and to report on the CPU consumption of different workloads, including mobile and public cloud workloads.

Author : Nigel Williams,Richard Gamblin,Rob Jones,IBM Redbooks
Publisher : IBM Redbooks
Page : 100 pages
File Size : 52,7 Mb
Release : 2020-04-11
Category : Computers
ISBN : 9780738458625

Get Book

IBM Z Integration Guide for Hybrid Cloud by Nigel Williams,Richard Gamblin,Rob Jones,IBM Redbooks Pdf

Today, organizations are responding to market demands and regulatory requirements faster than ever by extending their applications and data to new digital applications. This drive to deliver new functions at speed has paved the way for a huge growth in cloud-native applications, hosted in both public and private cloud infrastructures. Leading organizations are now exploiting the best of both worlds by combining their traditional enterprise IT with cloud. This hybrid cloud approach places new requirements on the integration architectures needed to bring these two worlds together. One of the largest providers of application logic and data services in enterprises today is IBM Z, making it a critical service provider in a hybrid cloud architecture. The primary goal of this IBM Redpaper publication is to help IT architects choose between the different application integration architectures that can be used for hybrid integration with IBM Z, including REST APIs, messaging, and event streams.