Data Validation – Early Inclusion is Vital

Introduction

When organizations embark on conversion or data integration projects for new trading, performance, or accounting systems one crucial aspect often gets overlooked – data validation. In this blog post, we will emphasize the importance of addressing data validation from the very beginning of these projects. By understanding the significant challenges and delays that can arise from inadequate data validation, organizations can ensure a smoother, faster and more successful implementation.

Legacy Data Issues – The Hidden Problem

Many organizations mistakenly assume that their existing data is accurate and can be readily loaded into a new system. However, this assumption can lead to significant issues and delays. Data validation is a crucial step that needs to be prioritized right from the start of any project. By shining a light on this hidden problem, organizations can save time, resources, and prevent project setbacks.

Timely Identification of Challenges

One of the primary causes of delays in conversion and integration projects specific to money management firms is the presence of data that cannot be successfully converted or loaded into the new system. Unfortunately, this problem often goes unrecognized until the implementation phase. By addressing data validation as an early and essential step, money management firms can mitigate the following obstacles to success:

• Data Inconsistencies: Money management firms deal with vast amounts of financial data, including portfolio holdings, trades, and performance metrics. Inaccurate, incomplete, or inconsistent data can disrupt the conversion process. Discrepancies in data formats, missing fields, and data errors can lead to significant setbacks. For example, inconsistent data representations across different systemscan impact a plethora of functions including performance, attribution, risk analytics client and regulatory reporting. Employing effective data validation from the onset of system migrations can identify inconsistencies both early and prior to consumption into target environment.
• Mapping Complexities: Mapping data from the existing system to the new one is a complex task for money management firms. Each system may have its own unique data structures formats and data elements.. Without proper validation, incomplete or incorrect mapping can result in data misalignment. If for example source system has 50 transaction types versus 10 transaction types in target then mapping is required and validation is required to ensure all transactions are captured and behave accordingly within the target environment. Also differing data protocols have allowable values versus not allowable values which too can result in missing data or data reflected incorrectly. It is important to validate that mapping is working correctly and that required data protocols are followed as early as possible.
• Data Quality Issues: Data quality is paramount for money management firms. Poor data quality can stem from duplicate records, outdated information or inconsistent data entry practices. Neglecting data validation exacerbates these issues, compromising the data integrity in the new system. duplicate client records can result in doubling of transactions impacting positions in target systems and possible erroneous market values which can have wide stream impact from fee calculations, compliance issues, client reporting to performance errors.  
• Data Dependencies: Data within money management firms often relies on intricate relationships and dependencies. These dependencies need to be accurately maintained during the conversion or integration process. Neglecting these dependencies can lead to data inconsistencies and functional errors in the new system. For instance, failing to preserve the relationships between securities and their benchmarks can result in inaccurate benchmark results within performance and attribution. 

Value of Early Data Validation

To mitigate these challenges and ensure a successful conversion or integration for money management firms, it is crucial to prioritize data validation from the outset. By incorporating data validation as an integral part of the project plan, money management firms can experience significant benefits tailored to their specific needs:

• Proactive Issue Identification: Data validation helps uncover potential data quality issues early on, enabling money management firms to address them proactively. For example, validating the accuracy and completeness of portfolio holdings data can prevent errors in performance attribution calculations and ensure accurate reporting to clients. This approach minimizes the risk of discovering problems during the implementation phase, preventing costly delays and rework.
• Streamlined Mapping and Transformation: By validating data before mapping and transformation, money management firms can ensure accurate data alignment and reduce errors in the new system. For instance, validating the mapping of trades from the existing system to the new system helps maintain data integrity and ensures accurate transactional records. This streamlines the overall implementation process and minimizes discrepancies in data interpretation.
• Enhanced Data Integrity: Data validation allows money management firms to identify and rectify data quality issues, ensuring the integrity of the converted or integrated data. For example, validating the accuracy and consistency of historical performance data ensures that investment performance reports provide reliable insights to clients. This leads to more reliable and trustworthy information in the new system, enhancing decision-making capabilities.
• Improved Project Efficiency: By incorporating data validation as an integral step, money management firms can avoid time-consuming and costly setbacks caused by data-related issues. For instance, validating the quality and completeness of client data helps prevent errors in fee calculations and ensures accurate billing. This results in a more efficient and timely project completion, allowing firms to focus on delivering value to their clients.

Significance of Timely Data Validation

The success of conversion and integration projects for money management firms hinges on the critical timing of data validation. By recognizing the hidden problem of inadequate data validation and addressing it from the outset, organizations can prevent delays, mitigate challenges, and ensure a smoother implementation.

Data validation plays a pivotal role in identifying potential issues early on, allowing firms to proactively address data quality issues. By validating data before mapping and transformation, money management firms can ensure accurate data alignment, reducing errors in the new system. Furthermore, data validation enhances the integrity of converted or integrated data, providing more reliable and trustworthy information for informed decision-making.

Through early data validation, money management firms can improve project efficiency by avoiding costly time-consuming setbacks caused by data-related issues. By validating the quality and completeness of client data, for example, firms can prevent errors in fee calculations and ensure accurate billing, leading to a more efficient and timely project completion.

Conclusion

In conclusion, the comprehensive and timely validation of data is paramount in conversion and integration projects for money management firms. By prioritizing data validation from the very beginning, firms can overcome data inconsistencies, mapping complexities, data quality issues, and data dependencies on an early basis to allow for speeded up resolution for a faster and smoother implementation. This proactive approach helps firms to get to their target state on time, on budget and within their planned resourcing parameters.

Clean data is the foundation stone of the target state – it must be dealt with effectively from the very beginning or the project will be put at risk.