Nori Agentic Cuts Data Verification Time Amid Private Asset Surge
Discover how Nori Agentic's innovative approach has slashed data verification time from an hour to just five minutes, offering a game-changing solution for the burgeoning private asset market.
Key Facts
- Private asset volume surged to $240B in 2025, indicating a shift in investor focus and strategy.
- 95% automation with human review reduces data check time from 1 hour to 5 minutes, enhancing efficiency.
- Firms face rising operational costs as private assets lack standardized data, creating scalability challenges.
- Nori's cloud agents streamline data triage, saving hundreds of thousands of labor hours monthly for clients.
- The need for shared infrastructure among domain agents reveals vulnerabilities in current operational models.
Summary
Summary
Nori Agentic partnered with a Fortune 200 asset manager to address the inefficiencies in managing private asset data. The challenge involved manually triaging changes in a security master, which previously required an hour of human effort per change. By implementing a cloud agent solution, the asset manager reduced this time to just five minutes per change, achieving a 95% automation rate with human oversight.
Background
The Fortune 200 asset manager, based in New York, operates in the finance industry and has recently expanded its portfolio to include many private assets. This shift strained their existing data engineering team, which was responsible for maintaining the security master—a critical database that tracks all securities held by the firm.
Challenge
The primary challenge was the labor-intensive process of manually checking every change in the security master. With approximately 50,000 assets and 200 columns of data, even infrequent changes required significant human resources. Each change needed to be evaluated for accuracy, leading to hundreds of thousands of hours spent monthly on this task.
Solution
Nori Agentic introduced a cloud agent that automates the triage process for data changes. This agent operates in a remote environment and is programmed to identify the source of changes, gather necessary documentation, and recommend whether to keep or discard the change. The agent alerts the responsible human for final approval via Slack, drastically reducing the time required for each review from one hour to five minutes.
Results
The implementation of the cloud agent resulted in a 95% automation rate for the triage process. The time taken for human review of each data change was reduced from an hour to five minutes, significantly improving operational efficiency and allowing the asset manager to better manage its growing portfolio of private assets.
Key Insights
- Collaboration is essential for successful AI adoption; domain experts should work alongside engineers to create effective solutions.
- Aiming for 95% automation is often more practical than striving for complete automation, especially in complex fields like finance.
- Addressing accidental complexity—issues arising from inconsistent data practices—can free up valuable human resources for more critical tasks.
Customer Testimonial
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Key Concepts
Definitions
- cloud agent
- A coding agent that operates in a remote environment, enabling automation and auditability in data management tasks.
- security master
- The master database of all securities or instruments held by an asset manager, essential for risk management and compliance.
- accidental complexity
- Challenges arising from how a system was built rather than the problems it solves, often seen in inconsistent data recording practices.
- automation
- The use of technology to perform tasks with minimal human intervention, aimed at increasing efficiency and reducing errors.
- private assets
- Investments that are not publicly traded and often lack standardized identifiers, complicating data management.
Use Cases
- →Automating data checks for private assets
- →Using cloud agents to triage data changes
- →Reducing manual review time from one hour to five minutes
- →Implementing a shared cloud-agent infrastructure for various financial tasks
- →Enhancing data management in back-office finance
- →Facilitating collaboration between domain experts and engineers
Frequently Asked Questions
What is the role of cloud agents in data management?
Cloud agents automate the process of investigating changes in security master data, significantly reducing the time required for human review. They operate in a remote environment, ensuring auditability and transparency.
How does the security master function in asset management?
The security master serves as the central database for all securities held by an asset manager, crucial for risk management and compliance. It helps ensure that data quality and visibility are maintained.
What are the benefits of 95% automation with human review?
Achieving 95% automation allows for significant efficiency gains while still ensuring accountability through human oversight. This balance helps tackle complex financial tasks without overwhelming human resources.
Why is accidental complexity a concern in finance?
Accidental complexity arises from inconsistent data practices and can hinder effective data management. By addressing this complexity, firms can focus their resources on solving more critical issues.
What lessons can be learned from AI adoption in finance?
Key lessons include the importance of collaboration between stakeholders, aiming for high levels of automation without full autonomy, and recognizing that managing complexity can be more cost-effective than previously thought.