The Results

{{stats-component}}

‍

The Execution

Our client is a prominent Indian fintech company specializing in comprehensive online payment services. Their platform enables effortless transactions through advanced features like payment gateways, direct links, customizable pages, and quick payment buttons, catering to a diverse commercial clientele.​

​
Our client grappled with challenges in securing their payment processes. The lack of strict validation rules has escalated fraud incidents, resulting in legal issues and significant financial losses. ​​

It became imperative to fortify compliance with regulatory benchmarks, thereby mitigating legal exposures, diminishing the frequency of chargebacks, and reducing ancillary expenses.​

‍

The Approach

Our approach to addressing the client's challenges encompassed the development and implementation of a sophisticated rule-based model for transaction validation. This model scrutinizes each transaction, discerning its legitimacy and deciding whether to approve or decline it based on a set of predetermined criteria. Our solution involved:​

1. Comprehensive analysis of transactional data to detect patterns indicative of fraud.​
2. Implementation of high-accuracy tracking metrics tailored to distinguish fraud on both domestic and international transactions.​
3. Identification of high-risk factors, including specific customers, IP addresses, devices, cards, or virtual payment addresses (VPAs), where the incidence of fraud was significantly higher.​
4. Integration of an automated fraud detection system, powered by our rules-based engine, which utilizes the metrics to issue alerts for suspicious transactions.​
5. Creation of dynamic workflows triggered by these alerts to enable swift and decisive actions against potentially fraudulent merchants or transactors.​

​Through the deployment of our rule-based engine, we significantly enhanced our client's defence against fraudulent activities. This not only protected their customers from potential fraudsters but also safeguarded the company from reputational damage and monetary losses, reducing financial impact for 80%.​

‍