pRODUCT

Analytic Tools

Fraud Detection System

The Fraud Detection System (FDS) is a comprehensive solution designed to protect businesses by identifying and preventing fraudulent activities within financial transactions. It acts as a vigilant guardian, continuously monitoring all transaction data from various sources such as Websites, Mobile Apps, Bank Systems, and ATMs.

FDS operates in two modes: Pre Mode, where it scrutinizes transactions as they are initiated to catch any early signs of fraud, and Post Mode, where it reviews completed transactions to detect suspicious patterns that may have slipped through.

Why Our System is Fast

Our fraud detection system is designed to deliver lightning-fast performance to keep up with today’s high-speed transactions. It achieves this through a combination of cutting-edge technologies and smart architecture. By using advanced data streaming tools like Kafka, the system can instantly process huge volumes of transaction data as it flows in, without delays. Meanwhile, Redis, an in-memory data store, allows the system to access critical information almost instantly, eliminating the wait times common with traditional databases.

The system’s components are built to work in parallel, meaning multiple layers of fraud checks happen simultaneously rather than one after another, speeding up the overall decision-making process. Additionally, the entire solution runs on a scalable platform that adjusts resources dynamically based on transaction volumes, ensuring consistent speed regardless of fluctuations in activity.

This combination of real-time data processing, in-memory caching, parallel evaluation, and scalable infrastructure empowers our system to analyze transactions quickly and reliably, so suspicious activity is detected and acted upon without delay. In turn, this fast response time helps protect your business and customers effectively while supporting smooth and uninterrupted operations.

Campaign Editor

A marketing automation platform designed to help businesses create, schedule, and manage targeted campaigns across multiple channels. It was developed to simplify campaign execution by providing a unified interface for crafting and delivering personalized messages.

Voucher Management System

Voucher Management System (VMS) is a system designed to manage the generation and redemption of vouchers, enabling organizations to distribute promotional, discount, or digital incentive vouchers to users efficiently.

Analytic Services

dr Pipe

A marketing automation platform designed to help businesses create, schedule, and manage targeted campaigns across multiple channels. It was developed to simplify campaign execution by providing a unified interface for crafting and delivering personalized messages.

Analytic Product

Recency Frequency Monetary (RFM)

Complex Event Processing (CEP) for Fraud Detection Systems In the context of a fraud detection system, CEP plays a critical role by continuously monitoring transactional data and other relevant event streams to detect suspicious activity rapidly and accurately.

Profitability

Provides a unified view of bank profitability by consolidating income and expense data across products, branches, time, and customers down to the CIF level, with integrated forecasting and simulation capabilities.

Segmentation

Segmentation groups customers into groups, or segments, using machine learning (ML)-powered clustering algorithms. These algorithms enable a data-driven search for clusters among customers that avoids arbitrary and insignificant segments that may be generated by non-ML segmentation.

Cross Selling

Cross-selling analytics is a machine learning technique used to increase company revenue by identifying and recommending related or complementary products, based on customers' purchase histories and the transactional behavior of similar customers.

Up Selling

Up Selling analytics is a machine learning technique used to increase company revenue by identifying products where customers can be encouraged to grow their balances, based on insights from similar customer profiles.

Next Best Offer

Next Best Offer uses a machine learning algorithm to predict the most relevant alternative product or service for each customer based on past purchasing patterns, current stock, eligibility, and recent offers to ensure recommendations are both timely and actionable. Combining personalization with business rules makes the offer more attractive and satisfying to customers, while also continuously self-improving by learning from new customer behaviors.

Churn Analysis

Segmentation groups customers into groups, or segments, using machine learning (ML)-powered clustering algorithms. These algorithms enable a data-driven search for clusters among customers that avoids arbitrary and insignificant segments that may be generated by non-ML segmentation.