24K+ risks processed, 95% accuracy and efficiency achieved

Overview

The client needed to improve how oil and gas risks were matched with the assets they could affect. The existing database made it difficult to establish accurate connections between risks and assets, limiting the effectiveness of risk management.

We systematically matched identified risks with relevant assets, created new asset records where needed, and refined the database to eliminate inconsistencies. The result was a more structured and actionable dataset for risk assessment and asset management.

The challenge

Disconnected risk and asset data — the existing database did not effectively associate identified risks with their corresponding oil and gas assets.
Inaccurate risk management — weak connections between risks and assets created inefficiencies and increased the potential for inaccuracies in the overall risk management process.
Complex asset relationships — the client needed a structured way to identify, assess, and manage risks across a large and complex asset database.

What we did

1 Matched risks to assets — systematically linked identified risks with their corresponding assets in the client's database.
2 Created missing assets — added new asset records where gaps were identified based on the available risk information.
3 Checked the database for duplicates — reviewed records to identify and eliminate redundant entries.
4 Refined asset-risk associations — matched company names and reviewed relationships to ensure that risk-to-asset linkages were accurate and meaningful.

Results

24K+ risks processed — systematically connecting a large volume of identified risks with relevant assets.
95% accuracy and efficiency achieved — improving the reliability and efficiency of the risk-to-asset matching process.
More structured risk data — creating a cleaner and more actionable dataset for risk management.
Improved asset-risk visibility — giving the client a more integrated view of risks and the assets they affect.

Our methodology

How we structure risk-to-asset data

Effective risk management depends on accurate connections between identified risks and the assets they affect. A structured data process helps turn complex information into a more actionable dataset.

Risk-to-asset matching

Identified risks are systematically linked to the corresponding assets within the client's database.

Asset gap identification

Missing asset records are identified and created where required to establish complete risk relationships.

Database quality checks

Records are reviewed for duplicates and redundancies to maintain a clean and consistent dataset.

Relationship refinement

Company names and asset-risk associations are reviewed to ensure that the resulting linkages are accurate and meaningful.

Throughout the project, Tinkogroup team exhibited responsiveness to evolving needs. As challenges or additional requirements emerged, they proactively addressed them, ensuring that the project stayed on course. This adaptability is crucial in dynamic environments where project scopes may evolve over time. Regular updates, progress reports, and transparent communication channels were established, fostering a collaborative environment.

— Spokesperson, Technology Company