Financial services organizations of all sizes must remain one step ahead of financial crime, NICE said in a statement today.

To enable this, the firm announced this week that it has entered a definitive agreement to acquire Guardian  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, an AI cloud-based financial crime  Risk Management  Risk Management One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class, most brokers employ a risk management department tasked with analyzing the data and flow of the broker to mitigate the firm’s exposure to financial markets moves. Why Risk Management is a Fixture Among BrokersTraditionally the company is employing a risk management team that is monitoring the exposure of the brokerage and the performance of select clients which it deems risky for the business. Common financial risks also come in the form of high inflation, volatility across capital markets, recession, bankruptcy, and others.As a countermeasure to these issues, brokers have looked to minimize and control the exposure of investment to such risks.In the modern hybrid mode of operation, brokers are sending out the flows from the most profitable clients to liquidity providers and internalize the flows from customers.This is deemed less risky and are likely to incur losses on their positions.This in turn allowing the broker to increase its revenue capture. Several software solutions exist to assist brokers to manage risk more efficiently and as of 2018, most connectivity/bridge providers are integrating a risk-management module into their offerings. This aspect of running a brokerage is also one of the most crucial ones when it comes to employing the right kind of talent. One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class, most brokers employ a risk management department tasked with analyzing the data and flow of the broker to mitigate the firm’s exposure to financial markets moves. Why Risk Management is a Fixture Among BrokersTraditionally the company is employing a risk management team that is monitoring the exposure of the brokerage and the performance of select clients which it deems risky for the business. Common financial risks also come in the form of high inflation, volatility across capital markets, recession, bankruptcy, and others.As a countermeasure to these issues, brokers have looked to minimize and control the exposure of investment to such risks.In the modern hybrid mode of operation, brokers are sending out the flows from the most profitable clients to liquidity providers and internalize the flows from customers.This is deemed less risky and are likely to incur losses on their positions.This in turn allowing the broker to increase its revenue capture. Several software solutions exist to assist brokers to manage risk more efficiently and as of 2018, most connectivity/bridge providers are integrating a risk-management module into their offerings. This aspect of running a brokerage is also one of the most crucial ones when it comes to employing the right kind of talent. Read this Term solution provider.

NICE is a provider of both cloud and on-premises enterprise software solutions that empower organizations to make smarter decisions based on advanced analytics of structured and unstructured data.

Financial services organizations of all sizes rely on Guardian Analytics’ real-time behavioral analytics and machine learning solutions. Powered by the cloud, Guardian Analytics simplifies deployments and ongoing operations, optimizing operational resource efficiency.

The unique combination of NICE Actimize and Guardian Analytics’ fraud and anti-money laundering capabilities will empower firms of all sizes to accelerate the adoption of the industry’s most innovative solutions, to best protect their assets and customers.

The combination delivers AML and fraud capabilities in the cloud for complete financial crime and compliance coverage.

It dynamically adapts to new attacks and changes in customer behavior with real-time behavior-based analytics and machine learning, enabling higher detection accuracy, lower false positives, and 360 degree view to maximize operational efficiency.

Additionally, the combination delivers fast and easy deployment, significantly reducing time and cost with out of the box AML and fraud models and data connectors.

It will extend NICE Actimize's offering across the entire financial services sector, enabling firms of all sizes, from small and mid-sized banks to global financial institutions, to benefit from NICE Actimize’s financial crime and compliance solutions.

Advancing the future of managing financial crime risk

“Today, NICE Actimize is taking a significant step forward in advancing the future of managing financial crime risk,” said Craig Costigan, NICE Actimize CEO. “With criminals seeking to exploit the current environment, we need to make sure financial institutions and consumers are protected in a way that’s cost-effective and intuitive. The acquisition of Guardian Analytics brings together the unique combination of proven expertise, best-in-class innovation, and the power of the cloud, presenting a major opportunity for accelerated growth. I am excited to embark on this journey in advancing the industry’s fight against financial crime.”

“We are excited to join forces with NICE Actimize and look forward to the opportunities that the combination of our expertise and capabilities will bring to market,” said Eric Tran-Le, Guardian Analytics co-CEO.

“Financial services organizations need to stay ahead of today’s threats and our unique offerings enable firms to rely on a single provider to accelerate their financial crime risk management strategies, especially given the dynamic nature of today’s market,” he added.

The acquisition is expected to close in the latter part of Q4 2020.