Avoiding Data Silos: Why Data Integration Matters

Software tools offering institutional investors better insights, faster operations, less manual work are proliferating and it is very tempting to keep adding new tools in the endless quest to get control of your data. But adding new tools in isolation can lead to data silos.

Data is most useful when it is reusable and can integrate with other systems, and this is particularly true of due diligence data. Due diligence has traditionally been a stand alone function, checking manager and fund information before an investment, then used at regular intervals to monitor risks during the lifecycle of an investment.

Due diligence data often sits in documents and spreadsheets, used only for the original purpose.

Are data silos holding you back?

We believe this siloed approach to data could be holding firms back and our goal is to set data free to improve:

Comprehensive decision-making: Due diligence involves gathering and analyzing various types of information, including quantitative data, qualitative assessments, legal and regulatory considerations, financial statements, market research, and more. If this data is stored in silos, it becomes challenging to access and integrate the complete picture necessary for making well-informed decisions. Avoiding data silos ensures that all relevant information is readily available and can be considered holistically.

Risk mitigation: Due diligence is primarily performed to assess risks associated with investment opportunities or business partnerships. Siloed data can lead to gaps in information, hindering the ability to identify and evaluate risks accurately. Integrated data allows for a comprehensive risk assessment by considering all available information, reducing the likelihood of overlooking crucial factors that could impact investment outcomes.

Efficient collaboration: Due diligence is often a collaborative effort involving multiple stakeholders, such as investment teams, legal experts, compliance officers, and executives. Silos can impede effective collaboration and knowledge sharing among these parties. By avoiding data silos, information can be easily shared and accessed by relevant team members, facilitating efficient collaboration, and enabling better decision-making through diverse perspectives.

Consistency and accuracy: Siloed data can lead to inconsistencies and inaccuracies in due diligence findings. When different teams or individuals work with isolated datasets, they may inadvertently duplicate efforts or miss out on updates or changes in the data. By integrating data and maintaining a centralized repository, consistency and accuracy can be ensured, reducing errors and enhancing the reliability of due diligence outcomes.

Regulatory compliance: Depending on the industry and jurisdiction, there may be specific regulatory requirements governing due diligence practices. These regulations often demand comprehensive documentation and the ability to demonstrate a thorough evaluation process. Data silos can make it challenging to meet these compliance requirements, potentially exposing organizations to legal and regulatory risks. Integration of due diligence data ensures compliance with applicable regulations and enables efficient auditing and reporting.

Future analysis and learning: Integrated data sets provide a valuable resource for future analysis and learning. By breaking down data silos, organizations can analyze historical due diligence data to identify patterns, trends, and insights. This retrospective analysis can inform future due diligence processes, improve decision-making frameworks, and facilitate continuous improvement in due diligence practices.

Avoiding due diligence data silos ensures that decision-making is based on complete, accurate, and up-to-date information, promotes collaboration, reduces risks, and supports compliance with regulatory requirements. It enables organizations to make informed decisions, optimize resource allocation, and enhance overall due diligence effectiveness.

Dasseti has robust API's

Dasseti's award-winning software platforms can integrate with many other software platforms, with minimal development work, due to its robust APIs. By integrating data from Dasseti into existing systems, such as a CRM, Research Management System or risk management system, users get ongoing and additional value from the quantitative and qualitative due diligence data they collect on managers and funds.

Dasseti's integration with eVestment

In particular, integrating NASDAQ eVestment data with qualitative due diligence data collected using Dasseti, is game changing for asset allocators and allows:

Comprehensive investment analysis: By combining quantitative data from eVestment with qualitative due diligence data, asset allocators can gain a more holistic view of investment opportunities. This allows for a deeper understanding of the investment landscape, including historical performance, risk metrics, and various qualitative factors.

Enhanced risk assessment: Quantitative data from eVestment can provide valuable insights into the risk profile of investment options. By integrating this data with qualitative due diligence collected using Dasseti, asset allocators can better assess the risk factors associated with specific investments. This comprehensive analysis enables them to make more informed decisions and mitigate potential risks.

Improved manager selection: eVestment offers a vast database of investment managers and funds, allowing asset allocators to evaluate performance metrics and track records. By integrating this quantitative data with qualitative due diligence, asset allocators can assess investment managers more thoroughly. They can consider factors such as investment philosophy, team experience, strategy alignment, and other qualitative aspects to make more effective decisions when selecting managers.

Data-driven decision making: Integrating eVestment data with qualitative due diligence enables asset allocators to make decisions based on a combination of objective metrics and subjective analysis. This data-driven approach can help eliminate biases and emotional decision-making, leading to more rational and potentially better investment decisions.

Efficiency and scalability: Leveraging eVestment's data integration capabilities, asset allocators can automate the collection and analysis of quantitative data. This automation saves time and resources, allowing them to focus more on qualitative due diligence. It also enhances scalability, as asset allocators can analyze a larger number of investment options efficiently.

Increased transparency: Integrating quantitative and qualitative data promotes transparency in the decision-making process. Asset allocators can clearly articulate the rationale behind their investment choices, providing stakeholders with a deeper understanding of the factors considered. This transparency can help build trust and credibility with clients, consultants, and other stakeholders.

Continuous monitoring and evaluation: Combining eVestment's quantitative data with qualitative due diligence enables ongoing monitoring and evaluation of investment performance. Asset allocators can track the performance of investments against their initial expectations and make informed decisions on portfolio rebalancing or reallocation based on a comprehensive assessment of both data types.

Find out more about Dasseti's Nasdaq eVestment integration

Or book a demo to see the two platforms working together

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