Simulation Memoization for Fraud Detection Processing
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Solution Overview
Problem
Current computer simulation techniques for optimizing processing rules in electronic transactions are resource-intensive and time-consuming, making it difficult to predict and prevent fraudulent activities in real-time.
Innovation Solution
Implementing pre-computation and memoization methods to store and retrieve simulation results efficiently, using hash values to map simulation queries to pre-computed results, allowing for near real-time simulation processing without repeating computations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional simulation techniques are used to optimize processing rules, then accurate fraud detection can be achieved, but processing time and computational resources are excessively consumed
Solution Approach 1:
The system performs pre-computation of simulation results for various processing rule configurations before they are actually needed. By calculating and storing the outcomes of simulations in advance (in the fraud simulation database), the system eliminates the need to perform time-consuming simulations in real-time, thus resolving the contradiction between accurate fraud detection and processing time
Solution Approach 2:
The system creates and stores copies of simulation results in a database, mapping hashed simulation queries to their corresponding pre-computed results. When a simulation is needed, the system retrieves the pre-stored copy instead of recalculating, significantly reducing processing time while maintaining the accuracy of fraud detection
2Productivity
If comprehensive simulations are run to optimize processing rules, then better performance metrics can be achieved, but computational resources are excessively consumed
Solution Approach 1:
The system extracts and stores only the essential simulation results and their corresponding query hashes in a database. By separating the computation phase (pre-computation) from the retrieval phase (fast lookup), the system reduces computational resource consumption during actual operations while maintaining comprehensive simulation capabilities when needed
Solution Approach 2:
The system changes the state of simulation results from transient computational outputs to persistent stored data. By transforming simulation results into storable, retrievable objects with hashed identifiers, the system enables efficient reuse of computational results, reducing overall resource consumption while maintaining productivity
Data Source
AI summary
Systems and methods for pre-computing and memoizing simulations are disclosed. In an embodiment, a computer system may retrieve processing filters for running a simulation. The computer system may generate a simulation query based on the simulation filters and hash the simulation query. The computer system may determine whether a simulation result corresponding to the hashed simulation query has been pre-computed and stored. If the simulation result has been pre-computed and stored, the computer system may provide the simulation result in a user interface. If the simulation has not been pre-computed, the computer system may run a simulation and store the simulation results with a mapping to the hashed simulation query. If an identical simulation query is requested, the computer system may match a hash of the simulation query to a stored hash and provide the memoized simulation result without recomputing the simulation result, so simulation processing times can be reduced.