One of the projects I am most proud of while working on OSP is the fraud detection tool we’ve developed. OSP is an end to end platform providing retailers with complete solution to sell groceries online. within the commerce product, we offer a range of B2B tools to help clients provide optimal experience to their business and their customers. The fraud detection tool allows clients to easily detect and block any fraudulent activity on their site. Easy is the key work here.
In the early days of our problem discovery we learnt there are few challenges fraud agents face in their job:
We kicked off with a workshop to document the current flow. The simplest process required five different tools. Clearly the process can be made simpler and more reliable.
Next we looked at the payment process, mapped its staged, and flagged where do we currently detect suspected activity. We learned there are better ways to detect activities with higher degree of confidence, less manual work and implementation of AI.
So the project developed in 2 avenues: enhancing and simplifying the user experience, and creating new AI logic that will learn, over time, the detection agents carry and will start to automated the process in areas of higher confidence.
Our development process was truly iterative. Often we want to be agile but end up more waterfall. This was not the case here. After every major deployment, which was every 2 months on average, we carried out user validation and looked at the data. In the early days the product was lean and our users said its too basic. But it allowed us to gradually evolve it in the right direction.
The result, over just over a year, we had a product that eliminated the five tools previously required to carry out the detection of fraudulent activity. It had simpler and more intuitive interface that provide the agent only the relevant information they required to make a decision. We were able to add new data that made the detection more accurate while eliminating older data that turned out to be not a useful.
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