Cardano Foundation Selects Coinfirm for ADA Crypto Compliance
- The company has integrated Coinfirm’s AML for the security of the crypto and blockchain economy.

Cardano Foundation, an independent organization based in Switzerland, announced recently that it has selected Coinfirm, a leading Blockchain Blockchain Blockchain comprises a digital network of blocks with a comprehensive ledger of transactions made in a cryptocurrency such as Bitcoin or other altcoins.One of the signature features of blockchain is that it is maintained across more than one computer. The ledger can be public or private (permissioned.) In this sense, blockchain is immune to the manipulation of data making it not only open but verifiable. Because a blockchain is stored across a network of computers, it is very difficult to tamper with. The Evolution of BlockchainBlockchain was originally invented by an individual or group of people under the name of Satoshi Nakamoto in 2008. The purpose of blockchain was originally to serve as the public transaction ledger of Bitcoin, the world’s first cryptocurrency.In particular, bundles of transaction data, called “blocks”, are added to the ledger in a chronological fashion, forming a “chain.” These blocks include things like date, time, dollar amount, and (in some cases) the public addresses of the sender and the receiver.The computers responsible for upholding a blockchain network are called “nodes.” These nodes carry out the duties necessary to confirm the transactions and add them to the ledger. In exchange for their work, the nodes receive rewards in the form of crypto tokens.By storing data via a peer-to-peer network (P2P), blockchain controls for a wide range of risks that are traditionally inherent with data being held centrally.Of note, P2P blockchain networks lack centralized points of vulnerability. Consequently, hackers cannot exploit these networks via normalized means nor does the network possess a central failure point.In order to hack or alter a blockchain’s ledger, more than half of the nodes must be compromised. Looking ahead, blockchain technology is an area of extensive research across multiple industries, including financial services and payments, among others. Blockchain comprises a digital network of blocks with a comprehensive ledger of transactions made in a cryptocurrency such as Bitcoin or other altcoins.One of the signature features of blockchain is that it is maintained across more than one computer. The ledger can be public or private (permissioned.) In this sense, blockchain is immune to the manipulation of data making it not only open but verifiable. Because a blockchain is stored across a network of computers, it is very difficult to tamper with. The Evolution of BlockchainBlockchain was originally invented by an individual or group of people under the name of Satoshi Nakamoto in 2008. The purpose of blockchain was originally to serve as the public transaction ledger of Bitcoin, the world’s first cryptocurrency.In particular, bundles of transaction data, called “blocks”, are added to the ledger in a chronological fashion, forming a “chain.” These blocks include things like date, time, dollar amount, and (in some cases) the public addresses of the sender and the receiver.The computers responsible for upholding a blockchain network are called “nodes.” These nodes carry out the duties necessary to confirm the transactions and add them to the ledger. In exchange for their work, the nodes receive rewards in the form of crypto tokens.By storing data via a peer-to-peer network (P2P), blockchain controls for a wide range of risks that are traditionally inherent with data being held centrally.Of note, P2P blockchain networks lack centralized points of vulnerability. Consequently, hackers cannot exploit these networks via normalized means nor does the network possess a central failure point.In order to hack or alter a blockchain’s ledger, more than half of the nodes must be compromised. Looking ahead, blockchain technology is an area of extensive research across multiple industries, including financial services and payments, among others. Read this Term Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Read this Term provider, for ADA crypto compliance.
According to an official announcement, the deployment of Coinfirm’s advanced AML will ensure that Cardano is able to be in full compliance with the FATF’s (Financial Action Task Force) guidelines, 6AMLD, and other supranational and national regulations.
Cardano Foundation supervises the advancement of Cardano, a proof-of-stake blockchain platform. According to Coinmarketcap, Cardano (ADA) is the world’s third-largest cryptocurrency with a market cap of more than $85 billion. ADA saw substantial gains this year as the digital asset jumped from $0.18 on 1 January 2021 to an all-time high of $2.95 on 24 August. Currently, ADA is trading near $2.65.
Through the latest integration of Coinfirm’s AML platform, Cardano Foundation is planning to enhance the security of the crypto and blockchain economy.
Commenting on the recent partnership, Mel McCann, Head of Technical Integrations at Cardano Foundation, said: “AML/CFT analytics is essential for a cryptocurrency to receive mass adoption within regulated markets. The tools and services provided by Coinfirm enable every exchange, custodian and all other third parties to clearly track the history of ADA held in their wallets. We are proud to work with Coinfirm due to their high-quality results and product offerings as the first analytics solution lives on the Cardano blockchain, the partnership with Coinfirm represents our continued dedication to supporting the adoption of the Cardano blockchain.”
AML Compliance Solutions
Due to the recent surge in the popularity of blockchain technology and cryptocurrencies, the need for AML compliance solutions has increased substantially. Blockchain companies have formed several partnerships with leading AML compliance solutions providers in 2021 to increase the security of their respective protocols.
“Coinfirm is excited to integrate the Cardano protocol with our AML Platform to ensure that counterparties using the ADA cryptocurrency and other assets created on Cardano are not tainted by illicit funds. This provides a seamless transition for financial institutions to uptake the protocol with scale, reducing the concern of AML/CFT compliance,” Sachin Dutta, Head of Marketing at Coinfirm, said.
Cardano Foundation, an independent organization based in Switzerland, announced recently that it has selected Coinfirm, a leading Blockchain Blockchain Blockchain comprises a digital network of blocks with a comprehensive ledger of transactions made in a cryptocurrency such as Bitcoin or other altcoins.One of the signature features of blockchain is that it is maintained across more than one computer. The ledger can be public or private (permissioned.) In this sense, blockchain is immune to the manipulation of data making it not only open but verifiable. Because a blockchain is stored across a network of computers, it is very difficult to tamper with. The Evolution of BlockchainBlockchain was originally invented by an individual or group of people under the name of Satoshi Nakamoto in 2008. The purpose of blockchain was originally to serve as the public transaction ledger of Bitcoin, the world’s first cryptocurrency.In particular, bundles of transaction data, called “blocks”, are added to the ledger in a chronological fashion, forming a “chain.” These blocks include things like date, time, dollar amount, and (in some cases) the public addresses of the sender and the receiver.The computers responsible for upholding a blockchain network are called “nodes.” These nodes carry out the duties necessary to confirm the transactions and add them to the ledger. In exchange for their work, the nodes receive rewards in the form of crypto tokens.By storing data via a peer-to-peer network (P2P), blockchain controls for a wide range of risks that are traditionally inherent with data being held centrally.Of note, P2P blockchain networks lack centralized points of vulnerability. Consequently, hackers cannot exploit these networks via normalized means nor does the network possess a central failure point.In order to hack or alter a blockchain’s ledger, more than half of the nodes must be compromised. Looking ahead, blockchain technology is an area of extensive research across multiple industries, including financial services and payments, among others. Blockchain comprises a digital network of blocks with a comprehensive ledger of transactions made in a cryptocurrency such as Bitcoin or other altcoins.One of the signature features of blockchain is that it is maintained across more than one computer. The ledger can be public or private (permissioned.) In this sense, blockchain is immune to the manipulation of data making it not only open but verifiable. Because a blockchain is stored across a network of computers, it is very difficult to tamper with. The Evolution of BlockchainBlockchain was originally invented by an individual or group of people under the name of Satoshi Nakamoto in 2008. The purpose of blockchain was originally to serve as the public transaction ledger of Bitcoin, the world’s first cryptocurrency.In particular, bundles of transaction data, called “blocks”, are added to the ledger in a chronological fashion, forming a “chain.” These blocks include things like date, time, dollar amount, and (in some cases) the public addresses of the sender and the receiver.The computers responsible for upholding a blockchain network are called “nodes.” These nodes carry out the duties necessary to confirm the transactions and add them to the ledger. In exchange for their work, the nodes receive rewards in the form of crypto tokens.By storing data via a peer-to-peer network (P2P), blockchain controls for a wide range of risks that are traditionally inherent with data being held centrally.Of note, P2P blockchain networks lack centralized points of vulnerability. Consequently, hackers cannot exploit these networks via normalized means nor does the network possess a central failure point.In order to hack or alter a blockchain’s ledger, more than half of the nodes must be compromised. Looking ahead, blockchain technology is an area of extensive research across multiple industries, including financial services and payments, among others. Read this Term Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Read this Term provider, for ADA crypto compliance.
According to an official announcement, the deployment of Coinfirm’s advanced AML will ensure that Cardano is able to be in full compliance with the FATF’s (Financial Action Task Force) guidelines, 6AMLD, and other supranational and national regulations.
Cardano Foundation supervises the advancement of Cardano, a proof-of-stake blockchain platform. According to Coinmarketcap, Cardano (ADA) is the world’s third-largest cryptocurrency with a market cap of more than $85 billion. ADA saw substantial gains this year as the digital asset jumped from $0.18 on 1 January 2021 to an all-time high of $2.95 on 24 August. Currently, ADA is trading near $2.65.
Through the latest integration of Coinfirm’s AML platform, Cardano Foundation is planning to enhance the security of the crypto and blockchain economy.
Commenting on the recent partnership, Mel McCann, Head of Technical Integrations at Cardano Foundation, said: “AML/CFT analytics is essential for a cryptocurrency to receive mass adoption within regulated markets. The tools and services provided by Coinfirm enable every exchange, custodian and all other third parties to clearly track the history of ADA held in their wallets. We are proud to work with Coinfirm due to their high-quality results and product offerings as the first analytics solution lives on the Cardano blockchain, the partnership with Coinfirm represents our continued dedication to supporting the adoption of the Cardano blockchain.”
AML Compliance Solutions
Due to the recent surge in the popularity of blockchain technology and cryptocurrencies, the need for AML compliance solutions has increased substantially. Blockchain companies have formed several partnerships with leading AML compliance solutions providers in 2021 to increase the security of their respective protocols.
“Coinfirm is excited to integrate the Cardano protocol with our AML Platform to ensure that counterparties using the ADA cryptocurrency and other assets created on Cardano are not tainted by illicit funds. This provides a seamless transition for financial institutions to uptake the protocol with scale, reducing the concern of AML/CFT compliance,” Sachin Dutta, Head of Marketing at Coinfirm, said.