The creation of fin - our customised Finance Reporting Platform, reflects our expert understanding of the complexities and nuances of financial data and the need for fast, quality information that CFOs can trust.
fin demonstrates a commitment to providing a sophisticated, tailored reporting solution that enhances data integrity, improves operational efficiency, facilitates compliance and supports strategic decision-making in finance.
fin consolidates and standardises data from multiple sources and legacy systems and separate organisations.
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Having structured data is crucial to effectively use AI services (AI and machine learning algorithms typically require well-organised and formatted data to function correctly and provide valuable insights). Fin will structure, standardise and consolidate your data so you can effectively use AI.
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Typical internal data sources include legacy finance systems; ERP and CRM systems; Supply Chain Management Systems; Contract Management Systems; flat files (excel); APIs; Databases; Data Lakes and Warehouses. External Market Data includes data from external sources like market research firms, financial markets, economic reports, and industry benchmarks.
The design of fin is a collaborative approach among our accountants, analysts, and data engineers and our customers' teams. This approach leverages the expertise of each discipline for comprehensive understanding and ensuring data accuracy & integrity. Processes consider compliance & risk management, efficient data processing & reporting, scalability & adaptability and stakeholder engagement & satisfaction.
We're renowned for handling sensitive data for global brands with utmost trust and professionalism. We are certified and adhere to ISO27001 standards, establishing a foundation of trust and best practices in managing client information. Our methodologies are meticulously crafted to uphold the integrity and trustworthiness of our clients' data.
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Rigorous data reconciliation is a cornerstone of our approach, ensuring the accuracy of every dataset. In the design of data pipelines, we implement rigorous control checks to promptly identify any discrepancies or anomalies. Financial metrics are assigned a confidence score, reflecting our assurance in the data's accuracy. This innovative process includes pinpointing both expected and unexpected variances and we actively communicate these findings to our clients - aiding them in allocating and addressing these discrepancies effectively.
The fin Matching Engine will assign a unique ID to each supplier, customer or product across all organisations and entities and will ensure that all transactions and interactions are consistently tracked. This reduces errors and inconsistencies in the data, leading to more accurate reporting and analysis, eliminates duplicate records, improves data analysis and reporting with enhanced data integration. The fin Reconciliation Engine is a critical tool for ensuring that financial data is robust, enabling informed decision-making, ensuring compliance and fostering trust in the report consumers.
Automating the data workflows and reconciliation process saves time and resources, allowing Finance teams to focus on more strategic tasks rather than manual data reconciliation. As the volume of data grows, the reconciliation engine can scale to manage increasing data loads, maintaining the quality and integrity of financial data and reducing risks of human error.
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