Machine Learning & Data Analytics
HQ: Hamburg / Germany
RISK IDENT offers anti-fraud solutions to tier one companies in e-commerce, telecommunications and financial sectors. We are experts in data analytics and machine learning. Our key products are DEVICE IDENT, FRIDA and EVE. Use cases include payment fraud, account takeovers, fraud within existing accounts, and loan applications.
- Financial Services
- Fraud Platform
- Payment Fraud
- Account Takeover
- New Account Fraud
- Machine Learning
- Rules Engine
The Otto Group
Please see further customers at www.riskident.com
Fraud Solution Profile
What we do:
We stop fraudsters and devices from placing illegitimate orders through web and mobile channels. Using our extensive domain knowledge and the latest technology around device fingerprinting and machine learning, we conduct linkage analysis of transactions – taking into account factors such as geo-proximity and the time of transactional occurrence. We have over 5 years of experience operating under the second largest global retailer in the world, as well as an abundance of experience working with a variety of e-commerce, telecom and financial companies across Europe.
Fraudsters are always looking for new ways to remain undetected, which means that fraud prevention software needs to be able to adapt to the changing technology and behaviors of fraudsters. Our self-developed software couples traditional rule sets with technically advanced machine learning algorithms which adapt, and learn to perform in the unique environment of each client.
We allocate a risk score to cross-channel devices and millions of transactions and specifically label the type of fraud present. This is helping our global clients better utilize their fraud teams by allowing them to focus their efforts on the right areas, classify 6% more instances, reduce false-positive-rates to ~0.4%, and save all important time.
- Identifies devices through unique characteristics.
- Compares devices to Risk Ident’s global pool of fraudulent transactions/devices.
- Allocates a risk score to devices based on the fraudulent characteristics.
- Push email and API access to device assessment in real time.
- Easy and quick integration.
- Combines traditional rule sets with machine learning to create a complete, self-learning fraud analysis platform.
- Includes all components of Device Ident, while taking into account other transactional components.
- Analyses patterns between transactions and performs linkage analysis – looking at factors such as geo proximity of transactions and the time of transactional occurrence.
- For each transaction, we specifically label the type of fraud that is present and allocate a risk score.
- Intuitive user interface that updates in real-time as orders are placed.
- On-premise or off-premise installation available.
- Tailored to perform in the unique environment of each client.
- Highly scalable machine learning risk engine.
- Detects connections between transactions and prior fraud scenarios.
- Can be installed locally or run as a cloud application.
- Versatile for use across a variety of industries.