Banking

Stored-value cards are a popular payment method that uses a magnetic strip or RFID chip to store value. They are typically used for one-time purchases and are not associated with a financial institution or credit limit. Stored-value cards are projected to reach a global market size of $5.51 trillion by 2027, driven by the demand for alternatives to cash and cheques, the growth of e-commerce, and the increasing number of internet users. However, the industry is also vulnerable to fraudulent attacks.

Fraud is difficult to detect because it is rare, planned and well-executed, concealed, and time-evolving. Fraudsters often operate in large teams and use sophisticated techniques to conceal their activities. As fraudsters evolve their techniques, fraud detection systems must also evolve to keep up.

Traditional rule-based fraud detection systems are becoming difficult to maintain and manage as the number of vendors and business rules increases. Machine learning (ML) techniques offer several advantages in fraud detection, including:

Adaptability: ML models can learn from historical data and adapt to new fraud patterns over time, without the need to manually update rules.
Accuracy: ML models can be trained to achieve high accuracy in fraud detection, even when dealing with complex and evolving fraud schemes.
Efficiency: ML models can automate the fraud detection process, freeing up fraud analysts to focus on more strategic tasks.

ML fraud detection systems offer several advantages over traditional rule-based systems, including:

Volume scalability: ML systems can analyze large volumes of data quickly and efficiently.
Processing efficiency: ML models can pre-filter, pre-process, and analyze transactions rapidly.
Lower cost: ML systems are more efficient and require less maintenance than rule-based systems.
Multi-modal support: ML systems can utilize multiple data sources, making them more difficult to spoof or circumvent.

ML fraud detection approach uses supervised learning techniques to train classifiers that can identify fraudulent transactions with high accuracy. The approach also incorporates unsupervised learning to handle concept drift, ensuring that the model remains effective over time.

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The Indian Defence Research Development Organization, one of our principal clients, and IVA have been collaborating closely to handle theoretically challenging and cross-disciplinary challenges in the areas of signal processing, computer vision, and machine learning

IVA is a business that specializes in providing engineering software solutions and services that assist in the automation of industries through the use of Digital Twin technology, which produces virtual replicas of physical systems. Digitalization also places an emphasis on helping businesses with the integration, aggregation, and analysis of enormous amounts of data from numerous sources, including industrial IoT sensors.

Our team's primary areas of expertise are machine learning and signal processing, and the study is focused on creating an entirely automatic data analysis system. One of the essential things that set us apart from the competition is our great R&D team, which has experienced fellows in the field and expertise in signal processing, pattern recognition, and computer vision. IVA has strong partnerships with prestigious universities like the Indian Institute of Technology to maintain its technological edge and domain expertise. These partnerships enable IVA to handle high-frequency data competently using ensemble modeling, no-code hyperparameter tuning, and domain expertise in aviation gas turbine engine systems and subsystems.

The Indian Defence Research Development Organization, one of our principal clients, and IVA have been collaborating closely to handle theoretically challenging and cross-disciplinary challenges in the areas of signal processing, computer vision, and machine learning.

We appreciate our own no-code interactive platform, DataCivet, which enables rapid ML pipeline development with signal processing and machine learning toolbox support. DataCivet enables us to assist our clients in the development of digital twins for process automation and diagnostic and prognostic analysis. IVA's virtual sensor is an out-of-the-box solution for addressing many sensor failure issues in industries including aerospace, oil, gas, etc.

Partnerships

We have a close collaboration with the Indian Defense Research Development Organization, one of our principal clients, to handle theoretically challenging and cross-disciplinary challenges in the areas of signal processing, computer vision, and machine learning.

IVA is a business that specializes in providing engineering software solutions and services that assist in the automation of industries through the use of Digital Twin technology, which produces virtual replicas of physical systems. Digitalization also places an emphasis on helping businesses with the integration, aggregation, and analysis of enormous amounts of data from numerous sources, including industrial IoT sensors.

Our team's primary areas of expertise are machine learning and signal processing, and the study is focused on creating an entirely automatic data analysis system. One of the essential things that set us apart from the competition is our great R&D team, which has experienced fellows in the field and expertise in signal processing, pattern recognition, and computer vision. IVA has strong partnerships with prestigious universities like the Indian Institute of Technology to maintain its technological edge and domain expertise. These partnerships enable IVA to handle high-frequency data competently using ensemble modeling, no-code hyperparameter tuning, and domain expertise in aviation gas turbine engine systems and subsystems.

The Indian Defence Research Development Organization, one of our principal clients, and IVA have been collaborating closely to handle theoretically challenging and cross-disciplinary challenges in the areas of signal processing, computer vision, and machine learning.

We appreciate our own no-code interactive platform, DataCivet, which enables rapid ML pipeline development with signal processing and machine learning toolbox support. DataCivet enables us to assist our clients in the development of digital twins for process automation and diagnostic and prognostic analysis. IVA's virtual sensor is an out-of-the-box solution for addressing many sensor failure issues in industries including aerospace, oil, gas, etc.

Who are we ?

IVA is a data analytics research firm that provides industrial digitalization products, integration, and support services to the aeronautics, aerospace, and defense industries, as well as predictive analytics tools and strategic insights for informed decision-making and innovation. We specialize in helping businesses with the integration, aggregation, and analysis of enormous amounts of data from various sources, including industrial IoT sensors

Expertise

We specialize in machine learning and signal processing, with a focus on creating a fully automatic data analysis system. They have an experienced R&D team with expertise in signal processing, pattern recognition, and computer vision. IVA has established strong partnerships with prestigious universities like the Indian Institute of Technology to maintain their technological edge and domain expertise

Solutions

We create digital twins using their automation solutions and Digital Twin technology, utilizing their expertise in machine learning, signal processing, and domain expertise in aviation gas turbine engine systems and subsystems. We use ensemble modeling, no-code hyperparameter tuning, and domain expertise to handle high-frequency data competently. Our solutions assist clients in developing digital twins for process automation and diagnostic and prognostic analysis

Partnerships

We have a close collaboration with the Indian Defense Research Development Organization, one of our principal clients, to handle theoretically challenging and cross-disciplinary challenges in the areas of signal processing, computer vision, and machine learning

Products

We have developed our own no-code interactive platform, DataCivet, which enables rapid ML pipeline development with signal processing and machine learning toolbox support. DataCivet enables us to assist our clients in the development of digital twins for process automation and diagnostic and prognostic analysis. IVA's virtual sensor is an out-of-the-box solution for addressing many sensor failure issues in industries, including aerospace, oil and gas, etc.