Improve your existing processes and develop new business models by combining professional data management and AI.<\/span><\/div><\/h2><\/div><\/div><\/div><\/div><\/div><\/div>Improve your existing processes and develop new business models by combining professional data management and AI.<\/span><\/div><\/h2><\/div><\/div><\/div><\/div><\/div><\/div>Data&<\/span>Analytics<\/span><\/strong><\/h1>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/i><\/div>SMART DATA<\/h2><\/div><\/div>\nQuick Check.<\/strong> Analysing potential in order to identify suitable AI projects in your company. Defining the use case and the objective and acquiring and exploring the right data.<\/p>\n<\/div><\/div><\/div><\/i><\/div>FAIL FAST, LEARN FAST<\/h2><\/div><\/div>\nProof-of-Concept.<\/strong> A quick and efficient review of the AI project\u00b4s feasibility and the identification of necessary adjustments in terms of data quantity and quality.<\/p>\n<\/div><\/div><\/div><\/i><\/div>ITERATE FASTER<\/h2><\/div><\/div>\nMinimum Viable Product (MVP).<\/strong> Creating a technical breakthrough under realistic conditions. Collecting valuable feedback from users through a pilot project and adjusting the direction of the AI-based solution.<\/span><\/p>\n<\/div><\/div><\/div><\/i><\/div>MAKE YOUR DATA USEFUL<\/h2><\/div><\/div>\nProduction.<\/strong> Supporting the transition of the MVP into production, including the design for for monitoring and maintaining the custom AI solution in the operation environment.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>We cover all key data areas for the securities business <\/span><\/b><\/h2>\n<\/div><\/i><\/div>MASTER DATA<\/h2><\/div><\/div>\nInformation on securities, companies and organizational structures as well as descriptive information, such as rating or ESG.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>MARKET DATA<\/h2><\/div><\/div>\nSuch as key figures, volumes and indicators or index and benchmark data as well as corporate actions.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>COURSE DATA<\/h2><\/div><\/div>\nData for the valuation of securities and portfolios, e.g. market prices or theoretical valuation prices for various types of securities.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>ESG<\/h2><\/div><\/div>\nESG-related information concerning companies, issuers and securities.<\/p>\n<\/div><\/div><\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Processes, technology and strategy <\/strong><\/h2>\n<\/div><\/i><\/div>DATA STRATEGY<\/h2><\/div><\/div>\nDevelopment of data strategies to support and achieve your business goals.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA ARCHITECTURE<\/h2><\/div><\/div>\nDesign of data architectures for efficient data management and implementation of the data strategy.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA GOVERNANCE<\/h2><\/div><\/div>\nProcesses, guidelines and procedures as well as definition of responsibilities for ensuring the quality, integrity, security and availability of data.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA ENGINEERING<\/h2><\/div><\/div>\nDevelopment and management of data infrastructures and systems for the efficient collection, processing, storage and analysis of data.<\/p>\n<\/div><\/div><\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Classification<\/span><\/h2><\/div>Classification<\/span><\/h2><\/div><\/div><\/div><\/div><\/div>Classification is the task of automated prediction of a discrete class label (e.g. fraud yes\/no).<\/p>\n<\/div>
Company-specific examples:<\/span><\/p>\n<\/div>- <\/i><\/span>\n
Plausibility check of transaction data<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Credit scoring check<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Classification of customer groups based on similar behavior patterns<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Churn prediction<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>![\"IP-Vertragsmanagement-und-NDA-Management\"](\"https:\/\/concedro.com\/wp-content\/uploads\/2021\/05\/01b_UseCase-Klassifikation-1024x820.jpg\" "\\"01b_UseCase-Klassifikation\\"")
<\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Regression<\/span><\/h2><\/div><\/div><\/div><\/div><\/div>Regression is the task of automated prediction of a continuous value (e.g. stock price).<\/p>\n<\/div>
Improve your existing processes and develop new business models by combining professional data management and AI.<\/span><\/div><\/h2><\/div><\/div><\/div><\/div><\/div><\/div>Data&<\/span>Analytics<\/span><\/strong><\/h1>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/i><\/div>SMART DATA<\/h2><\/div><\/div>\nQuick Check.<\/strong> Analysing potential in order to identify suitable AI projects in your company. Defining the use case and the objective and acquiring and exploring the right data.<\/p>\n<\/div><\/div><\/div><\/i><\/div>FAIL FAST, LEARN FAST<\/h2><\/div><\/div>\nProof-of-Concept.<\/strong> A quick and efficient review of the AI project\u00b4s feasibility and the identification of necessary adjustments in terms of data quantity and quality.<\/p>\n<\/div><\/div><\/div><\/i><\/div>ITERATE FASTER<\/h2><\/div><\/div>\nMinimum Viable Product (MVP).<\/strong> Creating a technical breakthrough under realistic conditions. Collecting valuable feedback from users through a pilot project and adjusting the direction of the AI-based solution.<\/span><\/p>\n<\/div><\/div><\/div><\/i><\/div>MAKE YOUR DATA USEFUL<\/h2><\/div><\/div>\nProduction.<\/strong> Supporting the transition of the MVP into production, including the design for for monitoring and maintaining the custom AI solution in the operation environment.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>We cover all key data areas for the securities business <\/span><\/b><\/h2>\n<\/div><\/i><\/div>MASTER DATA<\/h2><\/div><\/div>\nInformation on securities, companies and organizational structures as well as descriptive information, such as rating or ESG.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>MARKET DATA<\/h2><\/div><\/div>\nSuch as key figures, volumes and indicators or index and benchmark data as well as corporate actions.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>COURSE DATA<\/h2><\/div><\/div>\nData for the valuation of securities and portfolios, e.g. market prices or theoretical valuation prices for various types of securities.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>ESG<\/h2><\/div><\/div>\nESG-related information concerning companies, issuers and securities.<\/p>\n<\/div><\/div><\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Processes, technology and strategy <\/strong><\/h2>\n<\/div><\/i><\/div>DATA STRATEGY<\/h2><\/div><\/div>\nDevelopment of data strategies to support and achieve your business goals.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA ARCHITECTURE<\/h2><\/div><\/div>\nDesign of data architectures for efficient data management and implementation of the data strategy.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA GOVERNANCE<\/h2><\/div><\/div>\nProcesses, guidelines and procedures as well as definition of responsibilities for ensuring the quality, integrity, security and availability of data.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA ENGINEERING<\/h2><\/div><\/div>\nDevelopment and management of data infrastructures and systems for the efficient collection, processing, storage and analysis of data.<\/p>\n<\/div><\/div><\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Classification<\/span><\/h2><\/div>Classification<\/span><\/h2><\/div><\/div><\/div><\/div><\/div>Classification is the task of automated prediction of a discrete class label (e.g. fraud yes\/no).<\/p>\n<\/div>
Company-specific examples:<\/span><\/p>\n<\/div>- <\/i><\/span>\n
Plausibility check of transaction data<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Credit scoring check<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Classification of customer groups based on similar behavior patterns<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Churn prediction<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Regression<\/span><\/h2><\/div><\/div><\/div><\/div><\/div>Regression is the task of automated prediction of a continuous value (e.g. stock price).<\/p>\n<\/div>
Data&<\/span>Analytics<\/span><\/strong><\/h1>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/i><\/div>SMART DATA<\/h2><\/div><\/div>\nQuick Check.<\/strong> Analysing potential in order to identify suitable AI projects in your company. Defining the use case and the objective and acquiring and exploring the right data.<\/p>\n<\/div><\/div><\/div><\/i><\/div>FAIL FAST, LEARN FAST<\/h2><\/div><\/div>\nProof-of-Concept.<\/strong> A quick and efficient review of the AI project\u00b4s feasibility and the identification of necessary adjustments in terms of data quantity and quality.<\/p>\n<\/div><\/div><\/div><\/i><\/div>ITERATE FASTER<\/h2><\/div><\/div>\nMinimum Viable Product (MVP).<\/strong> Creating a technical breakthrough under realistic conditions. Collecting valuable feedback from users through a pilot project and adjusting the direction of the AI-based solution.<\/span><\/p>\n<\/div><\/div><\/div><\/i><\/div>MAKE YOUR DATA USEFUL<\/h2><\/div><\/div>\nProduction.<\/strong> Supporting the transition of the MVP into production, including the design for for monitoring and maintaining the custom AI solution in the operation environment.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>We cover all key data areas for the securities business <\/span><\/b><\/h2>\n<\/div><\/i><\/div>MASTER DATA<\/h2><\/div><\/div>\nInformation on securities, companies and organizational structures as well as descriptive information, such as rating or ESG.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>MARKET DATA<\/h2><\/div><\/div>\nSuch as key figures, volumes and indicators or index and benchmark data as well as corporate actions.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>COURSE DATA<\/h2><\/div><\/div>\nData for the valuation of securities and portfolios, e.g. market prices or theoretical valuation prices for various types of securities.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>ESG<\/h2><\/div><\/div>\nESG-related information concerning companies, issuers and securities.<\/p>\n<\/div><\/div><\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Processes, technology and strategy <\/strong><\/h2>\n<\/div><\/i><\/div>DATA STRATEGY<\/h2><\/div><\/div>\nDevelopment of data strategies to support and achieve your business goals.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA ARCHITECTURE<\/h2><\/div><\/div>\nDesign of data architectures for efficient data management and implementation of the data strategy.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA GOVERNANCE<\/h2><\/div><\/div>\nProcesses, guidelines and procedures as well as definition of responsibilities for ensuring the quality, integrity, security and availability of data.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA ENGINEERING<\/h2><\/div><\/div>\nDevelopment and management of data infrastructures and systems for the efficient collection, processing, storage and analysis of data.<\/p>\n<\/div><\/div><\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Classification<\/span><\/h2><\/div>Classification<\/span><\/h2><\/div><\/div><\/div><\/div><\/div>Classification is the task of automated prediction of a discrete class label (e.g. fraud yes\/no).<\/p>\n<\/div>
Company-specific examples:<\/span><\/p>\n<\/div>- <\/i><\/span>\n
Plausibility check of transaction data<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Credit scoring check<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Classification of customer groups based on similar behavior patterns<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Churn prediction<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Regression<\/span><\/h2><\/div><\/div><\/div><\/div><\/div>Regression is the task of automated prediction of a continuous value (e.g. stock price).<\/p>\n<\/div>
SMART DATA<\/h2><\/div><\/div>\nQuick Check.<\/strong> Analysing potential in order to identify suitable AI projects in your company. Defining the use case and the objective and acquiring and exploring the right data.<\/p>\n<\/div><\/div><\/div><\/i><\/div>FAIL FAST, LEARN FAST<\/h2><\/div><\/div>\nProof-of-Concept.<\/strong> A quick and efficient review of the AI project\u00b4s feasibility and the identification of necessary adjustments in terms of data quantity and quality.<\/p>\n<\/div><\/div><\/div><\/i><\/div>ITERATE FASTER<\/h2><\/div><\/div>\nMinimum Viable Product (MVP).<\/strong> Creating a technical breakthrough under realistic conditions. Collecting valuable feedback from users through a pilot project and adjusting the direction of the AI-based solution.<\/span><\/p>\n<\/div><\/div><\/div><\/i><\/div>MAKE YOUR DATA USEFUL<\/h2><\/div><\/div>\nProduction.<\/strong> Supporting the transition of the MVP into production, including the design for for monitoring and maintaining the custom AI solution in the operation environment.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>We cover all key data areas for the securities business <\/span><\/b><\/h2>\n<\/div><\/i><\/div>MASTER DATA<\/h2><\/div><\/div>\nInformation on securities, companies and organizational structures as well as descriptive information, such as rating or ESG.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>MARKET DATA<\/h2><\/div><\/div>\nSuch as key figures, volumes and indicators or index and benchmark data as well as corporate actions.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>COURSE DATA<\/h2><\/div><\/div>\nData for the valuation of securities and portfolios, e.g. market prices or theoretical valuation prices for various types of securities.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>ESG<\/h2><\/div><\/div>\nESG-related information concerning companies, issuers and securities.<\/p>\n<\/div><\/div><\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Processes, technology and strategy <\/strong><\/h2>\n<\/div><\/i><\/div>DATA STRATEGY<\/h2><\/div><\/div>\nDevelopment of data strategies to support and achieve your business goals.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA ARCHITECTURE<\/h2><\/div><\/div>\nDesign of data architectures for efficient data management and implementation of the data strategy.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA GOVERNANCE<\/h2><\/div><\/div>\nProcesses, guidelines and procedures as well as definition of responsibilities for ensuring the quality, integrity, security and availability of data.<\/p>\n<\/div><\/div><\/div>
<\/i><\/div>DATA ENGINEERING<\/h2><\/div><\/div>\nDevelopment and management of data infrastructures and systems for the efficient collection, processing, storage and analysis of data.<\/p>\n<\/div><\/div><\/div>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Classification<\/span><\/h2><\/div>Classification<\/span><\/h2><\/div><\/div><\/div><\/div><\/div>Classification is the task of automated prediction of a discrete class label (e.g. fraud yes\/no).<\/p>\n<\/div>
Company-specific examples:<\/span><\/p>\n<\/div>- <\/i><\/span>\n
Plausibility check of transaction data<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Credit scoring check<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Classification of customer groups based on similar behavior patterns<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div>- <\/i><\/span>\n
Churn prediction<\/p>\n<\/div><\/li><\/ul>
<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>Regression<\/span><\/h2><\/div><\/div><\/div><\/div><\/div>Regression is the task of automated prediction of a continuous value (e.g. stock price).<\/p>\n<\/div>
Quick Check.<\/strong> Analysing potential in order to identify suitable AI projects in your company. Defining the use case and the objective and acquiring and exploring the right data.<\/p>\n<\/div><\/div><\/div> Proof-of-Concept.<\/strong> A quick and efficient review of the AI project\u00b4s feasibility and the identification of necessary adjustments in terms of data quantity and quality.<\/p>\n<\/div><\/div><\/div> Minimum Viable Product (MVP).<\/strong> Creating a technical breakthrough under realistic conditions. Collecting valuable feedback from users through a pilot project and adjusting the direction of the AI-based solution.<\/span><\/p>\n<\/div><\/div><\/div> Production.<\/strong> Supporting the transition of the MVP into production, including the design for for monitoring and maintaining the custom AI solution in the operation environment.<\/p>\n<\/div><\/div><\/div> Information on securities, companies and organizational structures as well as descriptive information, such as rating or ESG.<\/p>\n<\/div><\/div><\/div> Such as key figures, volumes and indicators or index and benchmark data as well as corporate actions.<\/p>\n<\/div><\/div><\/div> Data for the valuation of securities and portfolios, e.g. market prices or theoretical valuation prices for various types of securities.<\/p>\n<\/div><\/div><\/div> ESG-related information concerning companies, issuers and securities.<\/p>\n<\/div><\/div><\/div> Development of data strategies to support and achieve your business goals.<\/p>\n<\/div><\/div><\/div> Design of data architectures for efficient data management and implementation of the data strategy.<\/p>\n<\/div><\/div><\/div> Processes, guidelines and procedures as well as definition of responsibilities for ensuring the quality, integrity, security and availability of data.<\/p>\n<\/div><\/div><\/div> Development and management of data infrastructures and systems for the efficient collection, processing, storage and analysis of data.<\/p>\n<\/div><\/div><\/div> Classification is the task of automated prediction of a discrete class label (e.g. fraud yes\/no).<\/p>\n<\/div> Company-specific examples:<\/span><\/p>\n<\/div> Plausibility check of transaction data<\/p>\n<\/div><\/li><\/ul> Credit scoring check<\/p>\n<\/div><\/li><\/ul> Classification of customer groups based on similar behavior patterns<\/p>\n<\/div><\/li><\/ul> Churn prediction<\/p>\n<\/div><\/li><\/ul> Regression is the task of automated prediction of a continuous value (e.g. stock price).<\/p>\n<\/div>FAIL FAST, LEARN FAST<\/h2><\/div>
ITERATE FASTER<\/h2><\/div>
MAKE YOUR DATA USEFUL<\/h2><\/div>
We cover all key data areas for the securities business <\/span><\/b><\/h2>\n<\/div>
MASTER DATA<\/h2><\/div>
MARKET DATA<\/h2><\/div>
COURSE DATA<\/h2><\/div>
ESG<\/h2><\/div>
Processes, technology and strategy <\/strong><\/h2>\n<\/div>
DATA STRATEGY<\/h2><\/div>
DATA ARCHITECTURE<\/h2><\/div>
DATA GOVERNANCE<\/h2><\/div>
DATA ENGINEERING<\/h2><\/div>
Classification<\/span><\/h2><\/div>
Classification<\/span><\/h2><\/div>
<\/span><\/div><\/div>Regression<\/span><\/h2><\/div>