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CRM for Financial and Insurance Markets
CRM for Financial and Insurance Markets
Customer relationship management (CRM) focuses on the retention of customers by collecting data from all customer interactions with a company from all access points (by phone, mail, or Web, or&n...
 

 insurance data model


InsFocus Releases Version 2.0 of BI Solution for Insurance
The Israeli software provider InsFocus Systems, producer of Insfocus Plus, a business intelligence (BI) solution targeted at the insurance industry, has

insurance data model  capabilities specific to the insurance industry. Uri Taiber, CEO of InsFocus Systems, remarked: We are truly excited about this new version. The combination of the new features, with the Web viewer and the greatly improved data model, will provide an even greater value to our customers and will further expand the true value of an insurance-specific solution. InsFocus is a solution worth looking at for an interesting mix of native BI capabilities and functionality for the insurance industry. You might wan

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CRM for Financial and Insurance Markets RFI/RFP Template

Insurance and Investment, Marketing Automation, Sales Force Automation (SFA), CRM Analytics, Call Center and Customer Service, Professional Services Automation (PSA), e-CRM, E-Mail Respons... Get this template

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CRM for Financial and Insurance Markets
CRM for Financial and Insurance Markets
Customer relationship management (CRM) focuses on the retention of customers by collecting data from all customer interactions with a company from all access points (by phone, mail, or Web, or&n...

Documents related to » insurance data model

Executive Brief: 3 Key Success Strategies for Insurance, Banks, and Financial Services


Financial services organizations are always looking for ways to improve business processes to implement tighter control—and improve the bottom line. But finding new ways to boost efficiency is challenging. One strategy for success is to improve the use and allocation of resources in order to eliminate errors from duplicate data entry. Discover more about this strategy and two others, as well as how they can benefit you.

insurance data model  Key Success Strategies for Insurance Banks and Financial Services If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader.   Established in 1993, Technology Evaluation Centers, Inc. (TEC) is the first web-native technology research enterprise. TEC provides decision support systems (DSS) that enable stakeholders to objectively identify the software products that best fit their company's unique business and systems requirements, and that contribut Read More

How Can Insurance Carriers Retain and Reward True Producers?


The enterprise incentive management and sales performance management market is evolving rapidly. Callidus Software remains the vendor of choice for some of the largest companies in the world. The vendor is aiming to cement its leadership within the insurance sector.

insurance data model  common occurrence in the insurance industry is duplication of data or effort, which leads to inconsistencies, difficulties in updating information, and a reduction in business agility. In addition, the inability to track submissions to government agencies often puts companies at risk of noncompliance. This is part one of the series How Can Insurance Carriers Retain and Reward True Producers? In part two, Callidus's TrueProducer EIM/SPM solution, designed to address problems specific to the insurance indus Read More

Data Mining: The Brains Behind eCRM


Data mining has emerged from obscure beginnings in artificial intelligence to become a viable and increasingly popular tool for putting data to work. Data mining is a set of techniques for automating the exploration of data and uncovering hidden truths.

insurance data model  companies seeking to predict insurance fraud should consider packages that use unsupervised learning, as there are typically no baselines to serve as predictors. Consumer products retailers can use unsupervised techniques to discover customer buying patterns in cash register receipt data in order to group items optimally in their stores. Supervised learning should be used where one wishes to measure the deviation from a known result. For example, a marketing department may know what product combinations ( Read More

16 Percent of BPM Seekers Agree with the SaaS Delivery Model


Recently, Rob Barry summarized some important points on the topic of delivering business process management (BPM) through the software-as-a-service (SaaS) model (see Choosing Business Process Management: SaaS BPM or On-premise BPM? According to this article, although managing business process in the cloud is in an early stage, this delivery model is becoming more noticeable. After reading this, I

insurance data model  health care, energy, and insurance are the industries that have a higher ranking in the “SaaS group”. Implementation: Number of Users and Timeframe After seeing the statistics on business size and structure, it’s not a surprise that in the “SaaS group”, organizations are planning to have more users for their future BPM systems than those in the “non-SaaS group”. Also, the “SaaS group” requires a shorter implementation time frame, which is a benefit that the SaaS model is supposed to Read More

MSI Data




insurance data model  Data Read More

Case Study: Celina Insurance Group


Celina Insurance Group, a mutual insurance carrier that serves eight states in the midwestern US, wanted to increase competitiveness against larger insurance carriers by integrating independent agents into business processes and providing superior services and support. Find out how a new collaborative extranet helped the company reduce policy turnaround times, improve service to agents and customers, and more.

insurance data model  Study: Celina Insurance Group Celina Insurance Group, a mutual insurance carrier that serves eight states in the midwestern US, wanted to increase competitiveness against larger insurance carriers by integrating independent agents into business processes and providing superior services and support. Find out how a new collaborative extranet helped the company reduce policy turnaround times, improve service to agents and customers, and more. Read More

Overall Approach to Data Quality ROI


Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI.

insurance data model  Approach to Data Quality ROI Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI. Read More

The Evolution of a Real-time Data Warehouse


Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine if your organization needs this type of IT solution.

insurance data model  Evolution of a Real-time Data Warehouse The Evolution of a Real-time Data Warehouse Jorge Garcia - December 23, 2009 Understanding Real-time Systems Today, real time computing is everywhere, from customer information control systems (CICSs) to real-time data warehouse systems. Real-time systems have the ability to respond to user actions in a very short period of time. This computing behavior gives real-time systems special features such as instant interaction: users request information from the system Read More

Making Big Data Actionable: How Data Visualization and Other Tools Change the Game


To make big data actionable and profitable, firms must find ways to leverage their data. One option is to adopt powerful visualization tools. Through visualization, organizations can find and communicate new insights more easily. Learn how to make big data more actionable by using compelling data visualization tools and techniques.

insurance data model  Big Data Actionable: How Data Visualization and Other Tools Change the Game To make big data actionable and profitable, firms must find ways to leverage their data. One option is to adopt powerful visualization tools. Through visualization, organizations can find and communicate new insights more easily. Learn how to make big data more actionable by using compelling data visualization tools and techniques. Read More

Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

insurance data model  Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses Read More

New Data Protection Strategies


One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets.

insurance data model  Data Protection Strategies One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets. Read More

Data Warehouse vs. Data Mart-Approaches to Implementing a Data Integration Solution


There continues to be a wide variety of different approaches to building a solid data management solution for your organization, and just as many consulting firms across the globe willing to help you build them. However, it’s imperative for each data management solution to specialize to the unique needs of your organization’s business users, across varying functional areas.

insurance data model  Warehouse vs. Data Mart-Approaches to Implementing a Data Integration Solution There continues to be a wide variety of different approaches to building a solid data management solution for your organization, and just as many consulting firms across the globe willing to help you build them. However, it’s imperative for each data management solution to specialize to the unique needs of your organization’s business users, across varying functional areas. Read More

Master Data Management: Extracting Value from Your Most Important Intangible Asset


In a 2006 SAP survey, 93 percent of respondents experienced data management issues during their most recent projects. The problem: many organizations believe that they are using master data, when in fact what they are relying on is data that is dispersed throughout the enterprise. Discover the importance of master data and how the ideal master data management (MDM) solution can help your business get it under control.

insurance data model  Data Management: Extracting Value from Your Most Important Intangible Asset Master Data Management: Extracting Value from Your Most Important Intangible Asset If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Founded in 1972, SAP has a rich history of innovation and growth as a true industry leader. SAP currently has sales and development locations in more than 50 countries worldwide and is listed on several exchanges, including the Read More

Data Quality Strategy: A Step-by-Step Approach


To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.

insurance data model  Quality Strategy: A Step-by-Step Approach To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality. Read More