2021 Intelligent security:Any system in which humans interact with technology involves a trade-off: security and accessibility. The more secure the system, the more difficult it is to access. This poses a dilemma for any organization under pressure, which can access anytime, anywhere, move the workplace and interact with customers and employees in real time – which describes almost every organization today.
Advances in artificial intelligence (AI) – and the millions of data points created by the Internet of things – are beginning to change the nature of this trade-off, especially when trust is part of a product or service. With more and more understanding of artificial intelligence systems, they can receive training to recommend the best action in the next step, automatically perform some repetitive tasks and minimize the maximum wind. With the growth of edge device intelligence, they can make real-time and near real-time determination, and security can be built into each transaction. Here’s how AI has revolutionized security in three industries.
Building trust is a special challenge in a business model that relies on doing business with strangers. Uber is a ride company that matches drivers and passengers. It constantly develops and tests new methods to prevent fraud and reduce risk.
“Our philosophy is no stranger,” explained Kate Parker, head of Uber trust and security initiative. “So we designed our platform to introduce drivers and riders immediately to improve the comfort of both sides.” because Uber’s business model is based on speed and safety, the company needs a way that will not make drivers and riders feel like they are waiting at the airport security line.
Therefore, in order to prevent fraud and improve the safety of drivers and cyclists, Uber uses intelligent face recognition technology to help ensure that drivers using the Uber application match their archived accounts. Cognitive ability ensures that additional verification steps are fast, applicable to all smartphones and dim lights, and can be extended to more than 1 million drivers.
Uber is not the only company that uses facial recognition. “This has become the standard login method in many industries, such as financial services,” said Dima kovalev, Uber product manager. “Your face is your new password.”
Mobile and online access create great opportunities for banks, insurance companies and wealth management institutions to interact with customers anytime, anywhere. However, these same capabilities have also led to incredible innovation by bad actors. The new AI capabilities are expected to help improve the way financial companies identify themselves, build risk models, and detect fraud and money laundering. These functions can also help solve ancient problems, such as privacy protection, compliance and credit risk assessment.
For example, HDFC bank in India deployed machine learning to create scorecards for loan applications that may have a thin credit record. By using demographic, geographic and other data to increase loan applications, HDFC bank analysts can conduct faster and more accurate credit analysis. This helps banks identify the best loan applicants and better manage their own risks.
“We can process more unstructured data, build clearer risk models and make better decisions faster,” said Bharath shasthri, senior analysis director of HDFC risk analysis. “Ultimately, this helps us get more new customers – and make sure they are the right customers.”
According to the joint report of the center for strategic and International Studies (CSIS) of non-profit policy research organization and McAfee of network security, cybercrime brings about US $600 billion losses to organizations, governments and individuals every year, mainly against banks. Company. Deep learning algorithms help detect anomalies in real time by analyzing millions of payment transactions and meaningful behavior and emotion analysis. According to corporate compliance solutions, a trade publication, money laundering is the main source of compliance fines for North American and European institutions, another area that has long frustrated financial institutions and authorities.
The current money laundering detection technology has produced a large number of false positives, leading to alarm fatigue. By deploying more sophisticated AI capabilities, financial institutions can reduce the number of false positives that must comply with due diligence. Not just paperwork and fines. Only 1 per cent of the estimated $3 trillion in illegal global financial flows were discovered and seized by the authorities.
Compared with digital medical records, the dilemma of security and access is the most obvious. Access is often elusive for practitioners and patients trying to browse digital records. Too many different systems require multiple logins and too much information must be entered manually. However, medical systems are known to be unsafe – especially through unprotected equipment and equipment. Telemetry and artificial intelligence help to establish accessibility immediately when needed, provide relevant information to medical service providers, and reduce medical errors.
Imagine a hospital room where the doctor’s equipment can communicate with the patient’s identity bracelet and allow her to unlock the patient’s medical files on the spot. The system of injecting cognitive ability can also put forward a series of relevant studies, available treatments and acceptable schemes according to the unique situation of patients.
When the doctor leaves the room, the access to the file is recorded and locked and saved until the authorized user invokes it again. Sensors in the room provide real-time information about the patient’s condition and activities when the caregiver makes a tour. Metadata from all interactions, as well as institutional and sensor data, combined with patient results, can be used to improve hospital procedures and then train cognitive systems to provide more intelligent and relevant advice to nurses.
With AI, security can be built in every encounter involving the device. The information obtained from these transactions can be used to detect anomalies, highlight potential hazards and continuously enhance all practices and procedures – especially in the area of security.