Accounting Bots with Scheduled Templates and Approval Review
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Solution Overview
Problem
Existing accounting systems require significant manual labor and expertise to process complex transactions, leading to increased processing time and error rates, especially as transaction volumes grow.
Innovation Solution
Automated accounting processes are encoded into templates that can be instantiated periodically, with runtime parameters, and executed to collect and process data, with intermediate results reviewed and approved before being written to a data store.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual processing methods are used for accounting transactions, then processing flexibility and expertise-based judgment are maintained, but processing time increases and error rates increase as transaction volumes grow
Solution Approach 1:
The system enables self-service automation where accounting processes execute themselves based on predefined templates and parameters. The automation framework allows processes to be defined once and then automatically instantiated and executed without continuous human intervention, reducing both error rates and processing time for high-volume transactions
Solution Approach 2:
The system uses parameter-driven process instantiation where template parameters are dynamically replaced with runtime parameters. This allows the same process template to handle varying transaction volumes and types efficiently, maintaining reliability while improving productivity through automated parameter substitution and execution
2Productivity
If automated processes are implemented to reduce manual labor, then processing speed and consistency improve, but system complexity and initial setup requirements increase
Solution Approach 1:
The automation framework provides universal process templates that can handle multiple accounting scenarios. A single template structure serves multiple functions by accepting different runtime parameters, reducing system complexity while maintaining high processing speed and consistency across various transaction types
Solution Approach 2:
The system uses template copying where a master process template is created once and then instantiated multiple times with different parameters. This eliminates the need to recreate processes manually for each transaction type, improving processing speed while keeping the underlying system structure simple and reusable
3Measurement precision
If comprehensive manual review is performed on all accounting data, then data accuracy is maximized, but processing time and resource consumption increase significantly
Solution Approach 1:
The system applies partial review by performing automated validation on all data and then selecting only certain items for manual review based on risk criteria. This maintains high data accuracy while significantly reducing the time required for manual review compared to reviewing all data comprehensively
Solution Approach 2:
The framework implements feedback loops where automated process execution results are evaluated and fed back into the system. This allows continuous improvement of data accuracy through automated learning while minimizing manual review time by focusing human expertise only on exceptional cases that require judgment
Data Source
AI summary
Aspects of the present disclosure relate to systems and methods for generating processes or bots for automatically processing accounting data. Some aspects of embodiments relate to defining templates specifying actions to be performed on a periodic basis (e.g., hourly, daily, weekly, or monthly). In some embodiments, the templates further include template queries for querying data stores or other data sources (e.g., data streams). The templates may be registered for scheduled execution, instantiating the templates with runtime parameters for execution, where executing the instantiated templates includes collecting and processing data collected from source data stores to generate output data. Some aspects relate to temporarily storing output data generated by executing the instantiated templates and requesting manual approval of the output data before the data is written to an output data store or sink data store. In some circumstances, the output data store may store a general ledger of a business.