The security community has found an important application for machine learning (ML) in its ongoing fight against cybercriminals. Per Recorded Future, many of us are turning to ML-powered security solutions like Lastline that analyze network traffic for anomalous and suspicious activity. In turn, these ML solutions defend us from digital threats better than other solutions can by drawing on their evolving knowledge of what a network attack looks like. Digital attackers are aware of the fact that security solutions are using ML for security purposes. They also know that there are certain limitations when it comes to applying artificial intelligence to computer security.
Police will use artificial intelligence to predict real-life hate crimes based on Twitter comments in the first trial of its kind in the UK. The AI system, which was developed by Cardiff University researchers, will be used to match hateful comments on the social media site to locations in the UK in an effort to prevent violence offline. Researchers proved that as the number of "hate tweets" – those deemed to be antagonistic in terms of race, ethnicity or religion – made from one location increased, so did the number of racially and religiously aggravated crimes, including violence, harassment and criminal damage. Police plan to use this technology from October 31 to track racist and hateful...
Financial firms are working to identify potential fraud by analyzing how customers hold their phones, how fast they type and other information about mobile interactions--and the strategy is yielding results. Using artificial-intelligence tools to crunch behavioral data is often a more secure way to verify customers than traditional means such as passcodes, experts say. The Federal Bureau of Investigation warned companies last month that cybercriminals can circumvent typical multifactor-authentication techniques. One way is by calling a telecommunications company, posing as a customer and getting a service agent to switch that person's phone number to the criminal's device. The fraudster can then have the individual's bank send a one-time passcode to the phone and gain access to the target's bank account.
Confirming popular perception that we are being watched, a report by the Carnegie Endowment for International Peace said that more countries, led by China, are deploying artificial intelligence to monitor the whereabouts of its citizens. According to the report, at least 75 of 176 countries globally are actively using AI technologies for surveillance purposes. The report said 56 countries are using smart city/safe city platforms, 64 are using facial recognition systems, and 52 are using smart policing. China's strong technological base is an enabling factor in the growth of AI surveillance. The report noted that Technology linked to Chinese companies--particularly Huawei, Hikvision, Dahua, and ZTE--supply AI surveillance technology in 63 countries, with Huawei alone is responsible for providing AI surveillance technology to at least 50 countries worldwide.
Artificial intelligence may be able to settle the debate over how many people attend protests or gatherings. Vast numbers of people took to the streets of London this weekend to call for a second referendum on the UK's membership of the European Union. But exactly how many people were there is up for debate. Organisers say there were 1 million people, but when they made similar claims earlier in the year they were disputed by fact-checking organisations. A method developed by Reza Bahmanyar at the German Aerospace Centre and his colleagues that uses artificial intelligence could help improve counts in the future.
This blog post will take us through how a business which need to ensure customer due diligence (CDD) can automate the KYC (Know Your Customer) processes using deep learning and computer vision based solutions. But before we get started, let's familiarise ourselves with some basic terminology. Customer Due Diligence - CDD involves verifying that your customers are who they say they are and assessing the risks associated with each customer like the possibilities of fraud, money laundering, terrorism financing, etc. This includes verifying your customer's name, address, photograph by analysing bank documents, utility bills, etc. Anti Money Laundering - AML refers to a set of laws, regulations and procedures meant to prevent criminals from disguising illegally obtained assets and funds as legitimate income by safeguarding against trading illegal goods, tax evasion, market manipulation, corruption of public funds, etc. Know Your Business - KYB involves vetting a business trying to establish a relationship with a bank by determining their Ultimate Beneficial Owners (UBO) and enforcing compliance by assessing risks associated with the business. You can learn more about beneficial ownership structures and a risk based approach to counter laundering here.
Neotas – a leading provider of online due diligence for the financial services sector – is joining forces with artificial intelligence (AI) experts at the University of Essex to develop a next-generation screening system. The London-based company has been awarded a £200,000 grant from Innovate UK towards the first stage of the project, which it believes could revolutionise due diligence by providing new solutions to tackle financial crime and mitigate risk. Neotas uses powerful search techniques to analyse a company's or an individual's'digital footprint', providing advanced insights without invading their privacy. Clients range from private equity firms carrying out pre-investment checks to banks and institutions which need to comply with anti-money laundering (AML) rules or the Senior Managers & Certification Regime (SMCR). The project aims to make the screening process less labour intensive and automatically identify warning signs without creating false alarms.
Armed violence is on the rise and we don't know how to stop it1. Since 2011, conflicts worldwide have killed up to 100,000 people a year, three-quarters of whom were in Afghanistan, Iraq and Syria. The rate of major wars has decreased over the past few decades. But the number of civil conflicts has doubled since the 1960s, and terrorist attacks have become more frequent in the past ten years. The nature of conflict is changing.
Fintech startups and banks have always been at the forefront of tech adoption, and they've been curiously following the growth and development of AI for many years. And there's a good reason for it -- we, the consumers of their services, want to have access to cutting-edge technology while dealing with our finances, as well as making sure that the companies dealing with our savings be equipped with the best of what tech can offer. AI and ML have recently moved from the realm of futurism to the very crux of the conversation in the Fintech sector, and many aspiring businesses have started integrating it into their services. In this article, we wanted to touch on the ways various Fintech businesses and startups implement this technology in the services they provide their customers with and how it benefits their users. Let's dive right in, shall we?
Video: Ethan Haus, a 6-year-old boy who went missing, was found after a private drone operator was able to spot the missing boy using heat-seeking technology. A missing 6-year-old boy from Minnesota and his dog were found Wednesday after hundreds of volunteers -- including one who used his own drone with a thermal camera -- searched for him for hours. Ethan Haus got off the bus with his siblings around 4 p.m. on Tuesday near Becker, a city roughly 47 miles northwest of Minneapolis, and ran to play with the family dog, Remington, officials said. When Ethan and the dog didn't return home, a massive search ensued, with more than 600 volunteers and numerous law enforcement agencies, including the FBI, working to find the young boy who was outside in temperatures in the low 40s, Sherburne County Sheriff Joel Brott said in a news release. Ethan Haus, 6, was discovered laying with his dog in a cornfield early Wednesday morning.