Artificial Intelligence, Machine Learning, and fraud detection play a significant role in detecting money laundering activities. The App identifies all account types and analyses their deposits, withdrawals, and transactions past to scan for anomalies, fraud, or unusual activity. It can help alert the transactions made or predict any future transactions that could be Money Laundering into the financial institutions.
Most companies big and small tackle identity fraud daily and have come to rely on a fleet of tools, including multifactor authentication and CAPTCHA (completely automated public Turing test to tell computers and humans apart) codes, to help identify potential identity fraud. While these tools help to some extent, they don’t catch everything. According […]
One of the most important aspects of data science is building trust. This is especially true when you're working with machine learning and AI technologies, which are new and unfamiliar to many people. When something goes wrong, what do you tell your customer? What do they think will happen next? With explainable AI, you can provide answers that prove your product's legitimacy.
The world of video analytics has come a long way in the past few years. What started as a complementary security surveillance technology, has evolved into a critical decision-making solution for stakeholders beyond law enforcement and public safety. Powered by AI and deep learning, today's sophisticated video analytics have far-reaching and impactful applications, from accelerating investigations for criminal or commercial claims to increasing operational productivity across industries and end users, delivering cost efficiency, enhanced safety, and elevated experiences. These applications only continue to gain strength, and in this article, I'll walk you through some examples of diverse industries innovatively supporting operational and business decision making with the power of data-driven intelligence derived from video analytics. But first, a quick word on how it works: Video intelligence software detects and extracts objects in video, identifies each object based on trained Deep Neural Networks, and classifies each object to enable intelligent video analysis through search and filtering, alerting, data aggregation, and visualisation capabilities.
Artificial intelligence (AI) is hailed as the disruptive technology that is set to revolutionize the 21st century. The function and popularity of this technology are soaring by the day. It has the potential to solve many of humanity's most pressing problems. AI is an umbrella term for technologies that can display some kind of intelligence such as machine learning computer vision, natural language processing, etc… These intelligent agents are algorithms trained using vast amounts of data to give machines some kind of reasoning ability. Instead of purely logical processing that computers usually perform, intelligent agents are designed around human thinking patterns and problem-solving skills. Artificial intelligence technologies create intelligent systems capable of self-learning and adapting to any new challenge. These specification has led to the rapid adoption of AI across different fields and industries around the world. Artificial intelligence has been around for decades, but its applications are only now opening up as more and more resources are dedicated to it. Over the last few years, AI has significantly evolved and is being extensively used in different aspects of human life and industry. Companies have begun using intelligent machines to mine data to optimize just about everything within their business operations. Artificial intelligence is a branch of computer science that aims to create intelligent machines that work and react like humans. It is the broad term for any device that is capable of performing a task normally restricted to human intelligence. AI combines several disciplines such as computer science, cognitive psychology, and neuroscience. The concept underlying AI is to get a non-human entity to make decisions just as an intelligent human would. Artificial intelligence research is about the creation of computer systems capable of visual perception, speech recognition, decision-making, and translation between languages. So many fields are using AI nowadays, from research and home automation to data processing and analysis. The technology is used to solve problems in many different ways and it is found in many types of systems such as household appliances, automobiles, financial systems, medical applications, and many other common tools. AI has undergone rapid development over the past decades, fueled by significant research and trail-blazing technological advancements. Nowadays, it is often used to make computer programs better than humans at perception and cognition tasks. AI technologies are on an exponential level of development and are becoming so advanced that it is entering nearly every field of modern life.
ConsultDSAI (C-DSAI) uses Artificial intelligence (AI) on CCTV video analytics as a technology that utilises advanced algorithms and machine learning techniques to analyze video footage captured by CCTV cameras. The technology is designed to automatically detect and identify objects, people, and events in real-time, and it can be used for a wide range of applications in various industries. One of the key uses of AI-based CCTV video analytics is in security and surveillance. The technology can be used to automatically detect and alert security personnel of potential security threats, such as intruders or loiterers. It can also be used to track the movement of people and vehicles, which can help to identify suspicious behavior or potential criminal activity.
It may sound like the plot of the 2002 movie Minority Report, but artificial intelligence can predict any arrest within three years of a prisoner being released on parole. The machine learning was designed to determine the risk of releasing a prisoner early by analyzing 91 variables, including age, race and previous arrests. Scientists from The University of California, Davis (UC Davis) used the data of more than 19,000 inmates scheduled with the New York State Parole Board from 2012 to 2015. Court documents show 4,168 individuals were released, but that AI determined the board could have released double the inmates without increasing the subsequent arrest rate. The film, set in 2054, is about a specialized police department that apprehends criminals using foreknowledge provided by three psychics called'precogs.'
Data science courses are among the most popular globally, with a high likelihood of career prospects, according to the volume of internet searches for skill development or job-oriented courses. Data scientists are needed everywhere. The most fundamental prerequisite for developing any technology in this era of smart technology (which includes smartphones, televisions, watches, etc.) is data, and these data scientists serve as the foundation for machine learning and artificial intelligence specialists. A data scientist will also assist organizations in managing serious crises and assisting them in their resolution through the use of data-driven judgments. Data science is the study of analyzing and obtaining organized, unstructured, and noisy data from various sources. This analysis aids businesses in forecasting outcomes and making data-driven decisions. Data that adheres to a data model, has a clearly defined structure, follows a persistent order, and is simple for both humans and programmes to retrieve is said to be structured data. Unstructured data is not structured in a way that has been predefined, notwithstanding the possibility that it has a native, internal structure. The data is kept in its original format; there is no data model. Media, text, internet activity, monitoring photos, and more are typical instances of large datasets. Data Science – The MUST KNOW to become a successful Data Scientist! How can software engineers and data scientists work together? Corrupted data, a type of unstructured data, is another name for noisy data. It also includes any information that a user's system is unable to effectively analyze and interpret. If handled improperly, noisy data can have a negative impact on the outcomes of any data analysis and skew conclusions. Sometimes, statistical analysis is employed to remove noise from noisy data.
The global banking industry faces heightened risks due to the evolving financial crime compliance mandates to clamp down on money laundering and sanctioned entities and maintain CDD/EDD. Among all, money laundering appears the most pernicious, with more illicit transactions evading anti-money laundering (AML) systems yearly. In tandem, screening sanctioned entities, SDNs, blocked persons, etc., is now a perennial need of financial institutions. Industry estimates place the laundered money to the tune of 2.7% of the annual global GDP, a whopping US$ 1.6 trillion loss. With an estimated 24,000 sanctions worldwide in 2022, inadequate watchlist screening and KYC (EDD/CDD) pose prodigious risks.
Let's picture the following game; two individuals, an outstanding counterfeiter who is well known for producing the best fake bills ever made, and the other hand, police, who are responsible for identifying whether the money moving around is real or fake. We can cast Tom and Leo for the movie, right? Now, how is this related to Machine Learning, Deep Learning, or any kind of automated Learning known by humankind? The promise of deep learning is to discover rich, hierarchical models that represent probability distributions over the kinds of data encountered in artificial intelligence applications, such as natural images, audio waveforms containing speech, and symbols, among others. We dreamed about Deep Learning implementations that can actually create rather than copy, and that my friends, is part of this journey.