Beeks Posts Solid Annual Growth, Revenue Jumped 27%
- The firm’s acquisition of Velocimetrics has increased its Tier 1 client’s list.

Beeks Financial Cloud Group plc, a financial markets connectivity provider, has published its yearly financial results ending on June 30, 2020, showing solid growth in its business as well as profits.
When it comes to the incomes, the company posted an underlying gross profit of £4.75 million for the period, a jump of 30 percent from the previous year’s £3.65 million. Furthermore, the underlying gross profit margin went to 51 percent from 50 percent recorded last year.
Though the underlying EBITDA increased by 34 percent to £3.33 million, which included the IFRS 16 adjustment of £0.52 million, the profits before taxes increased by 8 percent to £1.43 million.
Expected Growth
As Finance Magnates reported earlier, Beeks already anticipated this solid jump in its business for the financial year that goes in line with the market forecasts.
“While the ongoing Covid-19 pandemic may continue to cause a delay in corporate decision making, and in spite of the wider economic uncertainties, we are confident the long-term growth drivers in our market remain intact - with financial services organizations increasingly looking to take advantage of the benefits of Cloud infrastructure,” Beeks’ CEO, Gordon McArthur, said in a statement.
The company also accomplished significant operational milestones this year. It acquired UK-based network monitoring and trade 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 software firm Velocimetrics Limited in a £1.3 million cash and equity deal, along with a contingent earn-out.
The number of Tier 1 clients of the company also humped to five as it on-boarded two such clients this year. The Velocimetrics acquisition further added to this number.
“I am pleased to report on a year of considerable progress, in which the Group has delivered against its strategic objectives; increasing the number of Tier 1 customers, expanding its geographic presence and offering and completing the strategic acquisition of Velocimetrics,” McArthur added.
Beeks Financial Cloud Group plc, a financial markets connectivity provider, has published its yearly financial results ending on June 30, 2020, showing solid growth in its business as well as profits.
When it comes to the incomes, the company posted an underlying gross profit of £4.75 million for the period, a jump of 30 percent from the previous year’s £3.65 million. Furthermore, the underlying gross profit margin went to 51 percent from 50 percent recorded last year.
Though the underlying EBITDA increased by 34 percent to £3.33 million, which included the IFRS 16 adjustment of £0.52 million, the profits before taxes increased by 8 percent to £1.43 million.
Expected Growth
As Finance Magnates reported earlier, Beeks already anticipated this solid jump in its business for the financial year that goes in line with the market forecasts.
“While the ongoing Covid-19 pandemic may continue to cause a delay in corporate decision making, and in spite of the wider economic uncertainties, we are confident the long-term growth drivers in our market remain intact - with financial services organizations increasingly looking to take advantage of the benefits of Cloud infrastructure,” Beeks’ CEO, Gordon McArthur, said in a statement.
The company also accomplished significant operational milestones this year. It acquired UK-based network monitoring and trade 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 software firm Velocimetrics Limited in a £1.3 million cash and equity deal, along with a contingent earn-out.
The number of Tier 1 clients of the company also humped to five as it on-boarded two such clients this year. The Velocimetrics acquisition further added to this number.
“I am pleased to report on a year of considerable progress, in which the Group has delivered against its strategic objectives; increasing the number of Tier 1 customers, expanding its geographic presence and offering and completing the strategic acquisition of Velocimetrics,” McArthur added.