First AI Operating System for Risk Management
How we helped BlackSwan upgrade their core products Element and CAIOS thus securing $28m in funding and getting PepsiCo, J&J, Kraft Heinz, and P&G as its customers.
$28m+
Funding secured
89%
Accuracy prediction
50-fold
Reduced deployment time
55%
Decrease in cost per alert
BACKGROUND
About Blackswan
BlackSwan Technologies is a pioneering company in the field of artificial intelligence, particularly known for its ELEMENT™ platform, which is described as the world's first AI operating system designed for enterprise-level applications. Here are some key details and numeric insights about BlackSwan and its products:
ELEMENT Platform
AI Capabilities: ELEMENT integrates multiple AI technologies, including machine learning, deep learning, natural language processing, and knowledge graphs.
Data Processing: The platform can analyze millions of data points about entities, categorizing their significance in terms of fraud and anti-money laundering (AML) sensitivity.
Compliance Efficiency: ELEMENT has been recognized as an end-to-end solution for AML, anti-fraud, and client lifecycle management, significantly improving compliance processes for financial institutions.
ELEMENT Platform
AI Capabilities: ELEMENT integrates multiple AI technologies, including machine learning, deep learning, natural language processing, and knowledge graphs.
Data Processing: The platform can analyze millions of data points about entities, categorizing their significance in terms of fraud and anti-money laundering (AML) sensitivity.
Compliance Efficiency: ELEMENT has been recognized as an end-to-end solution for AML, anti-fraud, and client lifecycle management, significantly improving compliance processes for financial institutions.
9
Team size
65%
Reduction in alert volumes
16
New customers in 1 year
PepsiCo and J&J
Acquired as customers
Financial Technology (FinTech)
Market domain
REQUESTS
Blackswan's initial requests
1
Scale
their in-house tech team with 9 engineers and cloud devs to speed up the ELEMENT's upgrade and development by times.
2
Solve
the pain points of high deployment complexity and failing security checks to simplify deployment for customers by times and make them confident of data privacy and security.
3
Refactor
the deployment architecture making it easier for customers and make the operating system secure and compliant to pass checks thus increasing data privacy and security.
Solutions
Solutions we delivered
Transaction Monitoring Module
As BlackSwan had no transaction monitoring before to prevent money laundering risks, we've developed the complex intelligent system that now includes 4 core blocks:
- Event management
- Backtracking
- Error handling
- Error management.
With their help, BlackSwan's customers now can process millions of transactions per second, identify and prevent money laundering.
- Event management
- Backtracking
- Error handling
- Error management.
With their help, BlackSwan's customers now can process millions of transactions per second, identify and prevent money laundering.
AWS to Azure Migration
As BlackSwan had mature issues with data leakage in terms of tokens and passwords, we helped to upgrade the ELEMENT operating system's infrastructure by migrating from AWS to Azure and Google Cloud Platform (GCP).
This helped achieve a high-security grade among the organization's structure and eliminate customers' sensitive data theft and leakage by times.
This helped achieve a high-security grade among the organization's structure and eliminate customers' sensitive data theft and leakage by times.
CAIOS Implementation with Azure
We helped BlackSwan migrate most structures of the CAIOS operating system to Azure for higher performance, cost efficiency, and security due to the markets it's now operating on.
High Performance with 6 Mln Transactions per Hour
As BlackSwan customers previously struggled with high processing hours to analyze their transactions, we helped implement intelligent and highly accurate optimization builds to boost performance by times.
Now, ELEMENT's customers can process up to 6 million transactions per hour compared to several days of workloads before.
Now, ELEMENT's customers can process up to 6 million transactions per hour compared to several days of workloads before.
Credentials-Free Docker Images Implementation
As BlackSwan faced user identification issues while building up their customers' projects, we've implemented credentials-free Docker images and integrated The Artifactory libraries.
This way, brand-new project runtimes, and environments help eliminate having sensitive user data with credentials, tokens, and passwords inside the project builds.
In turn, this greatly boosts data privacy and security among clients.
This way, brand-new project runtimes, and environments help eliminate having sensitive user data with credentials, tokens, and passwords inside the project builds.
In turn, this greatly boosts data privacy and security among clients.
Reliable, Robust, and Abstract System Implementation
As BlackSwan's ELEMENT software is about processing large volumes of data, we helped implement an abstract architecture for the product leading to these benefits:
- Less time for application development
- Optimized support and maintenance
- More efficient use of data structures
- Easier integration of data from disparate sources
- Faster construction of data-loading jobs.
- Less time for application development
- Optimized support and maintenance
- More efficient use of data structures
- Easier integration of data from disparate sources
- Faster construction of data-loading jobs.
Results
Business results achieved
$28m
Funding secured with Riseapps helping upgrade their intelligent operating system thus improving the way customers utilize the product saving their time, funds, and lowering money laundering risks.
6 Mln
transactions per hour compared to several days before by implementing intelligent and highly accurate optimization builds.
50%
Reduction in false positives related to anti-money laundering (AML) alerts, significantly improving compliance efficiency.
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