# ADVSUS09-BP01 Optimize fraud detection systems for resource efficiency
<a name="advsus09-bp01"></a>

 Fraud detection systems can perform efficiently and have a reduced carbon impact when using approaches such as intelligent sampling, scheduled analysis, and Regional detection. 

## Implementation guidance
<a name="implementation-guidance-advsus09-bp01"></a>
+  Use energy-efficient processing for continuous fraud monitoring. If running compute instances, select AWS Graviton processors. 
+  Implement intelligent sampling for fraud detection where appropriate to reduce computational overhead while meeting business requirements. 
+  Schedule intensive fraud pattern analysis during low-carbon periods. 
+  Use serverless architectures for variable detection workloads. 
+  Use efficient data storage patterns for fraud signals and patterns. Archive data that is not readily needed and remove data that is no longer required for compliance/security purposes. 
+  Use AWS Clean Rooms for measurement analysis across partners, with the ability to analyze data sets where they are, with no data movement. 
+  Implement caching for frequently accessed fraud detection rules. 
+  Configure Regional detection systems to minimize data transfer. 

## Key AWS services
<a name="aws-key-services-6"></a>
+  Amazon EC2 with Graviton processors 
+  AWS Lambda 
+  Amazon ElastiCache 
+  AWS Clean Rooms 
+  Amazon CloudWatch 

## Resources
<a name="resources-75"></a>
+  [Hardware and services](https://docs.aws.amazon.com/wellarchitected/latest/sustainability-pillar/hardware-and-services.html)