case study / fintech / Fraud Detection Solution For Crowdfunding Platform

Fraud Detection Solution For Crowdfunding Platform

Lohika helped the client to successfully enter new markets and gain a foothold there.


The motto of our client is to be one step ahead of the competition. As such, time spent reaching the market has been crucial for them.
The company was going to expand to new international markets, this required a platform that could speed-up integration with different third-party payment systems from different geographies. The existing platform was tightly coupled with the Skrill payment gateway. This didn’t provide a variety of options for payment system integration that the client needed to be successful in foreign markets. The architecture limitation was just a single payment provider integration per country. Another limitation and one of the main risks for our client was fraudulent activity. The existing fraud prevention solution was semi-automatic and required a lot of manual work. So, the company was aiming to reduce the amount of manual work required to identify and automatically block fraudulent transactions.
At the same time, the current architecture was on the edge in terms of scalability and performance. Our client had a high-level vision for their solution. It required clarification, verification, and, as a result, high-grade implementation. As such, they needed an expert engineering team to bring the idea to life.


Our client is legally certified in securing fundraisers for non-profit organizations. Their aim is to provide the easiest way to collect, fundraise, and sell with your community.


Lohika team has started with reviewing the functional and non-functional requirements. Which helped to crystallize the high-level vision of our client into the low-level architecture that met all criteria. The new architecture design was event-driven with the three main architecture qualities in mind:

  1. Scalability
  2. Performance and overall system efficiency
  3. Extendibility to minimize the degree of manual work incorporated
The first component that Lohika has built was a rule-based engine with a custom DSL, developed specifically for our client. This engine was the heart of the system, created to block potentially fraudulent transactions via a set of rules. Our solution allowed for the creation of new fraud-detection rules – without involving developers. This fraud-detection solution ensured the company was capable of reacting to a new type of threats faster than most of its competitors.
While the team was working on the rule-based engine, they also built a CI/CD pipeline using CircleCI to automatically build, test, and deploy the solution in AWS.
All services were dockerized and running inside ElasticBeanstalk environments leveraging SQS as a communication channel. The use of AWS services eliminated a lot of DevOps challenges related to infrastructure deployment, configuration, and support.
Lohika extended the integration with Skrill payment gateway, removed the architectural limitation for the number of payment providers per country, and by integrated other payment gateways including Stride, Adyen, and iDEAL.
Lohika integrated Trulioo to speed up the process of identity verification. This step allowed our client to reduce manual work performed during the uploading and analyzing of personal data.
There was a requirement for the platform to be PCI DSS compliant. In the scope of this goal Lohika team implemented data encryption with secret key rotation and secure logging adapter that prevented sensitive data leakage.


The client received a fraud prevention solution which proved the main idea of the automated fraud prevention approach. The company got an update and improvement of the platform architecture. It fulfilled all functional and non-functional requirements, including scalability, performance, extendability and an ability to work under high load. The number of payment gateway integrations allowed the client to enter successfully new markets and gain a foothold there.

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