Advanced Fraud Detection with Partisia Platform

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Stay Ahead of Sophisticated Fraud with Partisia's Advanced Detection Platform

The discussion around fraud and its detection in finance has gained significant importance, especially in recent years, as those committing fraud have become increasingly sophisticated.

Fraudsters are well-versed in their methods, constantly innovating and finding new ways to bypass security measures. Each time one loophole is closed, they find another, making it challenging to catch them, particularly given the current regulatory landscape.

Regulations are primarily designed to protect customers, with a significant focus on safeguarding client identities.

However, these regulations pose challenges for banks in detecting fraud, as they prevent effective communication between institutions. In Denmark, for instance, current laws only permit the SØIK (the Danish special police department for economic and international crimes) to access and share this information.

Alexandra Institute
ICRC
Danmarks statistik
Aarhus University
Danish Quantum Community
Cyber Peace Institute
Rigshospitalet
Copenhagen Fintech
Bosch
Trust Stamp
Sundhedsdatastyrelsen
dfg
DIREC
Global fund
Partisia blockchain
Oscar
kin
Security Tech Space
Tora
Innovations fonden
Provable labs
Royal Danish Embassy
Alexandra Institute
ICRC
Danmarks statistik
Aarhus University
Danish Quantum Community
Cyber Peace Institute
Rigshospitalet
Copenhagen Fintech
Bosch
Trust Stamp
Sundhedsdatastyrelsen
dfg
DIREC
Global fund
Partisia blockchain
Oscar
kin
Security Tech Space
Tora
Innovations fonden
Provable labs
Royal Danish Embassy

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The definition of Fraud in the financial industry:

When talking about fraud in relation to the financial industry, it often involves Anti-Money Laundering (AML) and fraud detection. This type of fraud typically operates through a complex network of various banks, where the perpetrators use numerous accounts to obscure their activities. This makes it challenging not only to detect the fraud but also to identify the individuals responsible once it is discovered.

One of the primary difficulties is that banks are currently prohibited from sharing information with each other. Doing so would constitute a data breach and violate European GDPR laws.

As a result, the responsibility falls to SØIK (the State Prosecutor for Serious Economic and International Crime). However, SØIK also lacks a comprehensive database of all the necessary data, which hampers their ability to proactively detect and prevent fraud. A single entity alone faces significant challenges in identifying the systems, patterns, and digital fingerprints left by these sophisticated fraudsters.

Consider a scenario where all banks can securely share data about transfers, accounts, and transactions without leaking any personal information about their customers. By using multiparty computation technology, The Partisia platform can enable data sharing across different banks in a massive, secure network, preserving individual identities.

This approach not only makes it easier to detect and prevent fraud in real-time, but it also allows for predictive analysis. By leveraging this data, banks can proactively identify potential fraud and money laundering activities before they occur.

Moving away from today's very silo divided bank world, where connecting the dots and mapping the possible fraud and AML is a very tricky and almost impossible job. 

In other words: Partisia is making it possible to create a co-called fraud detection map, where all the banks that have been flagged with a ‘possible exposure to fraud’ mark, will be caught before the fraudster has a chance to ”leave with the money” and delete all tracks. 

It will be a network/map where all the banks in the network can share their data in a secure and fully protected way, still making it possible to enable and compute on the data.

Gaining knowledge through the feedback loop

When talking about the feedback loop we’re talking about the iterative process connecting and sharing this data in the fraud detection map on different stages:

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1

First step in this loop is the collection of data from the banks. This data will include transaction overview, customer information, account details and also things like behavioural patterns. 

2

Using different approaches and technologies such as rule based risk models it is possible to take all this data mentioned above and analyse it in order to understand the different patterns and flag possible abnormalities.

3

The system alerts upon detecting anomalies and can block accounts or freeze transactions promptly. Banks analyze flagged transactions to differentiate between fraudulent and legitimate ones, enhancing the system's proficiency by understanding money launderers' methods and behaviors.

Join the feedback loop and unlock a sophisticated AML solution

Choose Partisia for unparalleled security and efficiency in fraud detection. Our platform leverages cutting-edge technology to stay ahead of sophisticated fraud, ensuring your financial transactions remain safe and compliant with regulatory standards.

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Why work with Partisia?

Partisia was founded in 2008 by global pioneers within Multi-Party Computation and advanced cryptography. While our core mission is to integrate Privacy Enhancing Technologies with the aim of improving decision-making and product development, we also pride ourselves on being one of the best in the industry.

We are an innovative software company and a trusted partner empowering companies to operate and compute encrypted data. Providing a platform where data from individuals, governments and private companies are able to stay encrypted and protected, and still fully enabled, creating the perfect balance between transparency and privacy. Choose Partisia and get a partner based on expertise and knowhow, but most importantly trust.

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