For fintechs, if customer behavior is constantly changing, so should risk profiles adapt through Ongoing Customer Due Diligence. Perpetual KYC is a way of keeping up with new threats as well as new regulations.
Moreover, processes must be drafted in a way which can effectively speed up fintechs’ response to any given scenario.
By having perpetual KYC procedures in place fintechs will be empowered to a higher standard of vigilance will unquestionably help in creating a much more transparent organization.
As such, fintechs which make OCDD one of their core values will become an example of good governance, something which can easily translates into earning the trust of both clients and investors.
As much as machine learning and fraud analytics can help fintechs uncover patterns fraudsters might use, fintechs still need to take account that they need to deploy effective countermeasures as these are quintessential in what concerns compliance determinations.
While SARs reports help tackle fraudsters, further action should be taken so that fintechs send a clear message that they will not enter or maintain business relationships in which risks aren’t able to be properly mitigated.
There are certain data sources and activities which require tracking with a high degree of scrutiny, namely:
Lastly, considering taking steps towards KYC remediation might be a change which fundamentally alters risks profiles.
How can perpetual KYC help fintechs?
As OCDD procedures work as compliance obligations in which companies must monitor accounts while also assessing the risks they might pose for financial crimes such as money laundering
Money Laundering
Money laundering is a blanket term to describe the process by which criminals disguise the original ownership and proceeds of criminal conduct by making such proceeds appear to be derived from a legitimate source.Money laundering is an issue that traverses countless industries and sectors, which includes the financial services space. Though criminal money may be successfully laundered without the assistance of the financial sector, billions of dollars’ worth of criminally derived money are laundered through financial institutions each year.This is not entirely surprising given the structure of the financial services industry and the nature of products and services offered by its participants.An ecosystem that involves the management, control, and processing of finances is inherently vulnerable to abuse by money launderers.Money Laundering ExplainedThe act of laundering is committed in circumstances in which an individual or entity is engaged in an arrangement that involves the proceeds of crime. These arrangements include a wide range of business relationships, i.e. banking, fiduciary and investment management.However, the degree of knowledge or suspicion will depend upon the specific offense but will usually be present where the person providing the arrangement, service or product knows, suspects or has reasonable grounds to suspect that the property involved in the arrangement represents the proceeds of crime. In some cases, the offence may also be committed where a person knows or suspects that the person with whom he or she is dealing is engaged in or has benefited from criminal conduct.One of the primary criticisms against cryptocurrencies has been their propensity for money laundering. Their anonymous nature and unregulated network structure make them ideally suited for money launders.
Money laundering is a blanket term to describe the process by which criminals disguise the original ownership and proceeds of criminal conduct by making such proceeds appear to be derived from a legitimate source.Money laundering is an issue that traverses countless industries and sectors, which includes the financial services space. Though criminal money may be successfully laundered without the assistance of the financial sector, billions of dollars’ worth of criminally derived money are laundered through financial institutions each year.This is not entirely surprising given the structure of the financial services industry and the nature of products and services offered by its participants.An ecosystem that involves the management, control, and processing of finances is inherently vulnerable to abuse by money launderers.Money Laundering ExplainedThe act of laundering is committed in circumstances in which an individual or entity is engaged in an arrangement that involves the proceeds of crime. These arrangements include a wide range of business relationships, i.e. banking, fiduciary and investment management.However, the degree of knowledge or suspicion will depend upon the specific offense but will usually be present where the person providing the arrangement, service or product knows, suspects or has reasonable grounds to suspect that the property involved in the arrangement represents the proceeds of crime. In some cases, the offence may also be committed where a person knows or suspects that the person with whom he or she is dealing is engaged in or has benefited from criminal conduct.One of the primary criticisms against cryptocurrencies has been their propensity for money laundering. Their anonymous nature and unregulated network structure make them ideally suited for money launders. Read this Term.
Lastly, considering taking steps towards KYC remediation might be a change which fundamentally alters risks profiles.
How can perpetual KYC help fintechs?
Perpetual Know Your Customer (KYC), in essence, pushes fintechs to systematically keep reviewing accounts and transactions, but also risks.
· The high volume of data
While SARs reports help tackle fraudsters, further action should be taken so that fintechs send a clear message that they will not enter or maintain business relationships in which risks aren’t able to be properly mitigated.
· Suspicious activity
By shifting into an ongoing due diligence approach, these venues can consequently save time and costs while learning much more about their clients.
As such, fintechs which make OCDD one of their core values will become an example of good governance, something which can easily translates into earning the trust of both clients and investors.
In fact, there is a known gap between the SARs filed (suspicious activities reports) and actions taken after the fact.
The process entails a shift in mindset as it no longer becomes a check-the-box measure, rather turns into a holistic view of client data.
By shifting into an ongoing due diligence approach, these venues can consequently save time and costs while learning much more about their clients.
· The difficulty in understanding their clients and assessing risk.
Can help fintechs deploy high quality Ongoing Customer Due Diligence measures?
As OCDD procedures work as compliance obligations in which companies must monitor accounts while also assessing the risks they might pose for financial crimes such as money laundering
Money Laundering
Money laundering is a blanket term to describe the process by which criminals disguise the original ownership and proceeds of criminal conduct by making such proceeds appear to be derived from a legitimate source.Money laundering is an issue that traverses countless industries and sectors, which includes the financial services space. Though criminal money may be successfully laundered without the assistance of the financial sector, billions of dollars’ worth of criminally derived money are laundered through financial institutions each year.This is not entirely surprising given the structure of the financial services industry and the nature of products and services offered by its participants.An ecosystem that involves the management, control, and processing of finances is inherently vulnerable to abuse by money launderers.Money Laundering ExplainedThe act of laundering is committed in circumstances in which an individual or entity is engaged in an arrangement that involves the proceeds of crime. These arrangements include a wide range of business relationships, i.e. banking, fiduciary and investment management.However, the degree of knowledge or suspicion will depend upon the specific offense but will usually be present where the person providing the arrangement, service or product knows, suspects or has reasonable grounds to suspect that the property involved in the arrangement represents the proceeds of crime. In some cases, the offence may also be committed where a person knows or suspects that the person with whom he or she is dealing is engaged in or has benefited from criminal conduct.One of the primary criticisms against cryptocurrencies has been their propensity for money laundering. Their anonymous nature and unregulated network structure make them ideally suited for money launders.
Money laundering is a blanket term to describe the process by which criminals disguise the original ownership and proceeds of criminal conduct by making such proceeds appear to be derived from a legitimate source.Money laundering is an issue that traverses countless industries and sectors, which includes the financial services space. Though criminal money may be successfully laundered without the assistance of the financial sector, billions of dollars’ worth of criminally derived money are laundered through financial institutions each year.This is not entirely surprising given the structure of the financial services industry and the nature of products and services offered by its participants.An ecosystem that involves the management, control, and processing of finances is inherently vulnerable to abuse by money launderers.Money Laundering ExplainedThe act of laundering is committed in circumstances in which an individual or entity is engaged in an arrangement that involves the proceeds of crime. These arrangements include a wide range of business relationships, i.e. banking, fiduciary and investment management.However, the degree of knowledge or suspicion will depend upon the specific offense but will usually be present where the person providing the arrangement, service or product knows, suspects or has reasonable grounds to suspect that the property involved in the arrangement represents the proceeds of crime. In some cases, the offence may also be committed where a person knows or suspects that the person with whom he or she is dealing is engaged in or has benefited from criminal conduct.One of the primary criticisms against cryptocurrencies has been their propensity for money laundering. Their anonymous nature and unregulated network structure make them ideally suited for money launders. Read this Term.
Perpetual Know Your Customer (KYC), in essence, pushes fintechs to systematically keep reviewing accounts and transactions, but also risks.
There are certain data sources and activities which require tracking with a high degree of scrutiny, namely:
· Suspicious activity
Moreover, processes must be drafted in a way which can effectively speed up fintechs’ response to any given scenario.
For fintechs, if customer behavior is constantly changing, so should risk profiles adapt through Ongoing Customer Due Diligence. Perpetual KYC is a way of keeping up with new threats as well as new regulations.
Payment fraud 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 and Artificial Intelligence (machine learning) can help as it becomes easier to keep track of larger numbers of transactions and uncover patterns which might arise from fraudulent transactions and other illegal activities.
What countermeasures can fintechs take?
· Status changes
Keep Reading
By having perpetual KYC procedures in place fintechs will be empowered to a higher standard of vigilance will unquestionably help in creating a much more transparent organization.
The 3 main pain points are usually:
· Changes made to the account’s information
Data should thus be viewed in a holistic way but what happens when capabilities are limited and deep analysis is hampered?
What activities are tracked via Ongoing Customer Due Diligence?
Keep Reading
The 3 main pain points are usually:
· Trade data
Data should thus be viewed in a holistic way but what happens when capabilities are limited and deep analysis is hampered?
What activities are tracked via Ongoing Customer Due Diligence?
· Trade data
The process entails a shift in mindset as it no longer becomes a check-the-box measure, rather turns into a holistic view of client data.
· The inherent manual nature of KYC processes
· Risk thresholds
· The high volume of data
Generally speaking compliance, when done right, can effectively be turned into a competitive advantage.
· The difficulty in understanding their clients and assessing risk.
Can help fintechs deploy high quality Ongoing Customer Due Diligence measures?
Accordingly, real time analytical capabilities are key as Ongoing Customer Due Diligence requires fintechs to be prepared to constantly monitor account status as a way of tackling any emerging risk.
