Tag Archives: customer
How insurance software solutions are changing the way healthcare industry operates?
Insurance industries rely on the latest and updated information to conduct their insurance businesses. To maintain a strong foothold in the present day insurance market it is essential for insurance industries to have a strong online presence and a robust online network that facilitates time and cost saving.
To warrant excellent customer satisfaction, organizations are striving hard to introduce technologies and applications that are smart, efficient and at the cutting edge of latest technology. Web based insurance portals make it easy for insurers to update their official and consumer data in real time and from the remotest of locations.
The customers of insurance companies can also view their updated information online, thus encouraging more transparency and trust between the insurers and their customers. More and more insurance industries across the world are acknowledging the benefits of using insurance software solutions.
Insurance software solutions assist in increasing process efficiencies, reducing or containing administrative costs, enhancing customer experiences and maximizing marketing outreach and profit margins.
The U.S. healthcare industry landscape is abuzz with new applications and technologies that are taking customer experiences to new levels and are promoting transparency in financial dealings. Insurance software solutions are revamping the way insurers traditionally conducted their business.
There are a plethora of insurance software solutions available in the insurance industry. While some applications may assist insurers in quality analysis other applications may help in allaying projected market risks with the help of the inbuilt risk analysis and simulation tools.
U.S. healthcare IT firms are churning out comprehensive insurance software for insurers and state governments to aid them in servicing their clients better. Most of the insurance software includes applications that allow online eligibility checking, comparing and enrolling for health plans.
There are some health insurance software products that feature separate portals for groups, individuals, employers and employees for better management and customer experience. Deploying such applications on an insurers network does not affect the business continuity and doesnt require any additional investment in hardware or software.
Most insurance software solutions out in the insurance markets offer customization facilities wherein insurers can tailor the applications as per their business requirements and needs.
Insurance software solutions help insurers restructure and reorganize their critical businesses with simple yet brilliant processes which help in better risk analysis and assessment, thus dramatically reducing error instances and improving profits.
With cloud computing becoming a fast spreading rage across the entire U.S. healthcare industry, most benefits associated with it – scalability, flexibility, security, no upfront hardware and software investments are gaining traction.
Where efficiency and time effectiveness are primary concerns, automated insurance software solutions can come in handy as they are very fast, easily deployable and can aid in accurate data analysis.
Insurers are always on the lookout for smart, simple and easily understandable insurance solutions that not only help in improving business agility but also help in refining the customer services and strengthen relationships with customers. Insurance software solutions are becoming more of a necessity than a luxury because of their intelligent, automated processes.
File Processing Systems
Even the earliest business computer systems were used to process business records and produce information. They were generally faster and more accurate than equivalent manual systems. These systems stored groups of records in separate files, and so they were called file processing systems. Although file processing systems are a great improvement over manual systems, they do have the following limitations:
Data is separated and isolated.
Data is often duplicated.
Application programs are dependent on file formats.
It is difficult to represent complex objects using file processing systems. Data is separate and isolated. Recall that as the marketing manager you needed to relate sales data to customer data. Somehow you need to extract data from both the CUSTOMER and ORDER files and combine it into a single file for processing. To do this, computer programmers determine which parts of each of the files are needed. Then they determine how the files are related to one another, and finally they coordinate the processing of the files so the correct data is extracted. This data is then used to produce the information. Imagine the problems of extracting data from ten or fifteen files instead of just two! Data is often duplicated. In the record club example, a member’s name, address, and membership number are stored in both files. Although this duplicate data wastes a small amount of file space, that is not the most serious problem with duplicate data. The major problem concerns data integrity. A collection of data has integrity if the data is logically consistent. This means, in part, that duplicated data items agree with one another. Poor data integrity often develops in file processing systems. If a member were to change his or her name or address, then all files containing that data need to be updated. The danger lies in the risk that all files might not be updated, causing discrepancies between the files. Data integrity problems are serious. If data items differ, inconsistent results will be produced. A report from one application might disagree with a report from another application. At least one of them will be incorrect, but who can tell which one? When this occurs, the credibility of the stored data comes into question. Application programs are dependent on file formats. In file processing systems, the physical formats of files and records are entered in the application programs that process the files. In COBOL, for example, file formats are written in the DATA DIVISION. The problem with this arrangement is that changes in file formats result in program updates. For example, if the Customer record were modified to expand the ZIP Code field from five to nine digits, all programs that use the Customer record need to be modified, even if they do not use the ZIP Code field. There might be twenty programs that process the CUSTOMER file. A change like this one means that a programmer needs to identify all the affected programs, then modify and retest them. This is both time consuming and error-prone. It is also very frustrating to have to modify programs that do not even use the field whose format changed. It is difficult to represent complex objects using file processing systems. This last weakness of file processing systems may seem a bit theoretical, but it is an important shortcoming.
File Processing Systems
Even the earliest business computer systems were used to process business records and produce information. They were generally faster and more accurate than equivalent manual systems. These systems stored groups of records in separate files, and so they were called file processing systems. Although file processing systems are a great improvement over manual systems, they do have the following limitations:
Data is separated and isolated.
Data is often duplicated.
Application programs are dependent on file formats.
It is difficult to represent complex objects using file processing systems. Data is separate and isolated. Recall that as the marketing manager you needed to relate sales data to customer data. Somehow you need to extract data from both the CUSTOMER and ORDER files and combine it into a single file for processing. To do this, computer programmers determine which parts of each of the files are needed. Then they determine how the files are related to one another, and finally they coordinate the processing of the files so the correct data is extracted. This data is then used to produce the information. Imagine the problems of extracting data from ten or fifteen files instead of just two! Data is often duplicated. In the record club example, a member’s name, address, and membership number are stored in both files. Although this duplicate data wastes a small amount of file space, that is not the most serious problem with duplicate data. The major problem concerns data integrity. A collection of data has integrity if the data is logically consistent. This means, in part, that duplicated data items agree with one another. Poor data integrity often develops in file processing systems. If a member were to change his or her name or address, then all files containing that data need to be updated. The danger lies in the risk that all files might not be updated, causing discrepancies between the files. Data integrity problems are serious. If data items differ, inconsistent results will be produced. A report from one application might disagree with a report from another application. At least one of them will be incorrect, but who can tell which one? When this occurs, the credibility of the stored data comes into question. Application programs are dependent on file formats. In file processing systems, the physical formats of files and records are entered in the application programs that process the files. In COBOL, for example, file formats are written in the DATA DIVISION. The problem with this arrangement is that changes in file formats result in program updates. For example, if the Customer record were modified to expand the ZIP Code field from five to nine digits, all programs that use the Customer record need to be modified, even if they do not use the ZIP Code field. There might be twenty programs that process the CUSTOMER file. A change like this one means that a programmer needs to identify all the affected programs, then modify and retest them. This is both time consuming and error-prone. It is also very frustrating to have to modify programs that do not even use the field whose format changed. It is difficult to represent complex objects using file processing systems. This last weakness of file processing systems may seem a bit theoretical, but it is an important shortcoming.