Concurrent Data Loading and Rules Execution in Risk Evaluations
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Solution Overview
Problem
Conventional rule engines used for risk evaluations in online transaction requests become inefficient due to the need for large amounts of data, leading to delays and increased computational power usage, as they often retrieve and load all data before processing, even if not all data is necessary for the evaluation.
Innovation Solution
Implementing a system where risk evaluation sub-processes are performed concurrently with data retrieval, using multiple threads to load and process data in parallel, prioritizing data required for output-dependent sub-processes and eliminating unnecessary data paths to enhance speed and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the rule engine retrieves and loads all data before processing, then data completeness is ensured, but processing time increases and service performance deteriorates
Solution Approach 1:
The system performs preliminary actions by initiating data retrieval threads before the rule engine completes its data loading process. Multiple threads are started to retrieve different data sets concurrently, and data is loaded into the rule engine as soon as it becomes available, rather than waiting for all data to be ready. This allows the rule engine to begin processing with available data while other data is still being retrieved.
Solution Approach 2:
The system applies partial action by allowing the rule engine to process with a subset of available data rather than requiring complete data sets. The rule engine can evaluate transactions using data that has been retrieved so far, and continue processing as additional data becomes available. This prevents the system from waiting for excessive data that may not be immediately necessary for risk evaluation.
2Measurement precision
If the rule engine processes all data, then evaluation accuracy is improved, but computational power consumption increases
Solution Approach 1:
The system implements partial action by enabling the rule engine to perform risk evaluations using only the data that is available at any given moment, rather than processing all possible data sets. The engine continues to operate with partial data and refines evaluations as additional data becomes available, avoiding the computational overhead of processing unnecessary or redundant data sets.
Solution Approach 2:
The system performs preliminary data retrieval in parallel with rule engine processing, so that data preparation does not consume additional computational resources after the evaluation has begun. Multiple retrieval threads operate concurrently with the rule engine, utilizing idle computational capacity to gather data without interfering with the active evaluation process.
3Reliability
If the rule engine waits for data to be loaded, then data availability is ensured, but service performance to end users deteriorates
Solution Approach 1:
The system initiates data retrieval operations before the rule engine requires the data, using multiple concurrent threads to fetch different data sets. The retrieval process begins immediately when a transaction is submitted, and data is made available to the rule engine as soon as it is retrieved, rather than waiting for a complete data set to be prepared. This preliminary action ensures data availability while minimizing wait time for service delivery.
Data Source
AI summary
Methods and systems are presented for providing concurrent data retrieval and risk processing while evaluating a risk source of an online service provider. Upon receiving a request to evaluate the risk source, a risk analysis module may initiate one or more risk evaluation sub-processes to evaluate the risk source. Each risk evaluation sub-process may require different data related to the risk source to perform the evaluation. The risk analysis module may simultaneously retrieve the data related to the risk source and perform the one or more risk evaluation sub-processes such that the risk analysis module may complete a risk evaluation sub-process whenever the data required by the risk evaluation sub-process is made available.