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Auto Reconciliation Model
The CloFast auto reconciliation model leverages the CloRek algorithm, an advanced solution powered by Machine Learning (ML) and Artificial Intelligence (AI), to achieve high-accuracy data matching. This model classifies data into three distinct categories: reconciled, unreconciled, and special case. The CloFast solution architecture includes a comprehensive toolset pipeline that facilitates data ingestion, transformation, and classification.
The data ingestion process supports various input methods, including API, event-based, or file-based data inputs, and can handle images, PDFs, and structured data. Once ingested, data undergoes transformation, which includes extraction from PDFs and images using in-house or cloud solutions, followed by necessary transformations for internal processing.
The architecture integrates connectors for user authentication systems, data transformation processes, classification, clustering, and anomaly detection. It also includes ERP call-to-action mechanisms, supporting ERP data in relational formats and image data stored in file systems and vector formats. The system interfaces with SAP, Microsoft services, external systems, and MS Active Directory, ensuring seamless data flow and storage within the Clofast user system.
AI Chat Assistant
The AI Chat Assistant plays a crucial role within the unreconciled category of the CloFast auto reconciliation model. This intelligent assistant provides suggestions on the likelihood of matching transactions, offering percentage-based probabilities for potential matches. By analyzing transaction data, the AI Chat Assistant estimates the chances of transactions being reconciled, thereby guiding users towards possible matches.
These insightful suggestions significantly simplify the reconciliation process, enabling users to address unreconciled transactions more efficiently. With the AI Chat Assistant's recommendations, users can quickly identify potential matches, expediting the reconciliation process and enhancing overall productivity. This functionality ensures that even transactions initially classified as unreconciled can be resolved more swiftly, contributing to the timely and accurate completion of the reconciliation workflow.
Auto matching Model
The Auto Matching Model within CloFast is designed to streamline the reconciliation process by automatically identifying and matching transactions with high accuracy. Utilizing the advanced CloRek algorithm, powered by Machine Learning (ML) and Artificial Intelligence (AI), the system classifies transactions into reconciled, unreconciled, and special case categories.
The model employs sophisticated data matching techniques to analyze and compare transaction data, identifying potential matches based on various attributes and patterns. This automated process significantly reduces the manual effort required for reconciliation, allowing users to focus on exceptions and special cases that require human intervention.
Key features of the Auto Matching Model include: High Accuracy Matching, Classification, Reduction of Manual Effort, Improved Efficiency.
By incorporating the Auto Matching Model into the reconciliation workflow, CloFast enhances accuracy, efficiency, and productivity, ensuring a faster and more reliable reconciliation process.
