Data Accuracy

Data accuracy is the closeness of the agreement between a set of data and the reality being represented. 

Accurate geospatial data can be used as a reliable source of information. It can provide new insights for companies, and optimize planning, operations, and customer experience, especially in the insurance, banking, and utility industries, where it helps mitigate risks for companies.

In the insurance industry, having the most accurate data enables a more precise determination of the risk associated with each potential policyholder, which is paramount to correctly price insurance policies. The underwriting process begins with obtaining an accurate address or location through address validation and geocoding. If a policy is priced too high, insurers risk losing the deal and if it is priced too low, they lose out in the long run by retaining a riskier policyholder.

In the banking sector, having the most current and accurate data on perils, such as fire hazards, flooding, and hurricanes, is essential to correctly underwrite mortgages, which directly improves customer satisfaction and reduces potential maximum losses for banks.

In the utility industry, current and accurate data provides the ability to mitigate risks associated with potentially hazardous situations in order to comply with current regulatory guidelines.

The data collection process can be made more efficient and accurate through the following methods:

1. Use of reliable data resources
2. Establishment of data quality objectives
3. Analysis of your key factors and parameters
4. Use of automated error reports and computerized programs
5. Maintenance of neutral perspectives
6. Review of the data

There are several factors that cause data inaccuracy, starting with plain data entry errors made by users. It is also possible that the data entry process is flawed, whether it is related to poorly designed forms, confusing fields, unclear instructions, etc. The NULL problem is also frequent and occurs when the requested information is unavailable.

In addition, data inaccuracy can happen when the person does not know the correct information, does not want to know it, or gains an advantage from entering the wrong information.

The effective use of accurate data is jeopardized when organizations choose to acquire heterogeneous data sets from various vendors. Not always in the same format, this data makes it difficult to synchronize in enterprise software. Integrating huge amounts of variable data then requires various strategies and resources to homogenize it. To ensure that all data is of the same quality, it must also be cleaned and filtered before conversion and integration. Without the skills to do this, the impurities in this legacy data will have a cumulative effect and negatively impact the organization that uses it.

Data silos also present a challenge in terms of data usage. This is a collection of raw data accessible by one department but isolated from the rest of the organization. The result of data silos is a serious lack of transparency, efficiency, and trust within that organization. Data silos occur when data is collected by a tool that is isolated from the rest of a business’ technology ecosystem.

Korem offers a wide range of hyper-accurate data from a vast network of partners. These include geospatial, demographic, consumer, map, parcel, point of interest, business point, location, building footprint, and boundary data. HERE Technologies also has a full range of road data, like real-time traffic, speed limit, and truck data.

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