29th February, 2020
Ai Editorial: Astute infrastructure that facilitates capturing of real-time data and processing the same with minimal latency is key to setting up an apt risk assessment for legitimacy of transactions, writes Ai’s Ritesh Gupta
A key factor in sharpening a merchant’s fraud risk assessment for transactions relates to data infrastructure and its scalability. E-commerce players need to excel in this area, and ensure all of it is streamlined so that the experience of a travel shopper isn’t hindered. It is about conducting the check for the legitimacy in a fraction of a second, so that the evaluation doesn’t adversely delay the transaction/ payment. Travel merchants must be adept at probing and investigating data in real-time to sense fraudulent transactions or any other anomalous activity.
Fraud detection specialists acknowledge challenges associated with the performance of digital assets and the significance of a scalable application.
Some aspects that must be considered before looking at the infrastructure that support real-time fraud detection:
Key infrastructure-related areas for fraud detection
The turnaround comes from having the capability to analyze data via cloud-scale data ingestion and real-time analytics. To garner and examine a huge magnitude of transaction data calls for a vigorous database component for storage and management. Plus, a large-scale distributed computing component for running algorithms is also mandatory.
Also, from infrastructure perspective, one has to do away with managing individual servers.
Streaming data requires a data architecture that can handle rapid input and on-time output with efficient data processing. At the core of the entire exercise is to bank on a query established in advance and the objective is to alter the input stream and evaluate it based on a fraudulent-transaction algorithm. And in case there is anomaly detection, the same is conveyed to the output interface.
Some of the infrastructure-related requirements when it comes to ingestion, storage, processing, and analytics :
Key metrics, according to SecuredTouch, in this context are the time taken for a service to receive and respond to a request, and the time it takes to communicate with the end user.
In the whole exercise, the decisions that are related to right-sizing data, data processing method, the chosen database etc. are extremely important.
Keen on exploring fraud prevention and payment-related issues?
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