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Why Digital Identity Verification Is Gaining Ground
More than half of IT professionals don’t use advanced solutions and processes for their authentication processes, according to Equifax.
That’s why so many organizations are interested in digital identity verification technology, which helps them verify the digital identities of both new and existing users quickly using some combination of biometrics, machine learning and artificial intelligence.
Through brute force, phishing or third-party login processes, like the option to log in through Facebook, user accounts may fall prey to data breaches.
The ideal digital identity tool would leverage biometric technology like facial recognition and liveness detection [and] government-issued IDs, and ensure a friction-free process for the user.
Companies will need to be transparent on the personal data collected, manage requests for deletion of data and ensure policies against reselling data are in place.
They should protect people’s information by design and collect only the information they need, protected by the latest enhancements in biometric authentication, decentralized systems and anti-spoofing technologies.
When we look at the future of security and consider ways to prevent identity theft and attacks, there needs to be a mix of biometric authentication and zero-knowledge proofs--where users own their own data but don’t share it.
Klenk: Outsourcing identity verification could help businesses gain access to some of the best technologies out there and easily integrate several components like identity checks and fraudulent accounts through software development kits [SDKs].
This can be especially useful to small businesses, which need to facilitate interactions with people but don’t have the bandwidth or the desire to hire and sustain a compliance division in-house or store gigabytes of sensitive data on their servers.
The Racist History Behind Facial Recognition
Affect recognition draws from the work of Paul Ekman, a modern psychologist who argued that facial expressions are an objective way to determine someone’s inner emotional state, and that there exists a limited set of basic emotional categories that are fixed across cultures.
Sign up for our limited-run newsletter.] Moreover, it is not hard to stretch from interpreting the results of facial analysis as “how happy this face appears” to the simpler but inaccurate “how happy this person feels” or even “how happy this person really is, despite his efforts to mask his emotions.” As the A.I.
Artificial Intelligence in Finance: 5 Ways to Finest Customer Experience
The concept of harnessing artificial intelligence (AI) for business automation and transformation is sweeping the world.
Be it a startup or an established business, those companies that implement AI to boost in-house processes and external contacting with clients or partners are going in the right direction.
By employing AI in the finance sector, business owners can uncover a few new ways to upstage competitors through improved customer experience.
It can ensure well-structured cooperation with clients, increase the security level of financial transactions, facilitate risk management, create new products and services, and transform customer experience.
They found out that in the next 5 years AI in the fields of fraud prevention, risk management, personalized insights, and anti-money laundering will yield tangible results.
Facial recognition algorithms verify a person by taking facial features from images or videos and comparing to faces available in datasets.
The technology helps detect fraud on time and can be used to ensure the necessary level of security for both online services and within offices.
Source: Shutterstock AI-driven financial tools like the one announced by MX, large financial service provider, can assist customers in solving complicated financial issues.
With no or little human involvement machines can give financial advice, empower better decision making, and increase customer retention.
behavior more precisely and apply a more personalized approach to each customer.” AI can help increase client loyalty and build a competitive advantage.
It will result in better forecasting decision outcomes, mapping out different ways of development, and helping companies pick the best-suited strategies to mitigate business risks.
ML-based solutions can work with alerts, scrutinize large datasets, or perform analysis of suspect transactions in no time and with high accuracy.
They estimated that manual reviewing of 12,000 contracts requires up to 360,000 hours, whereas ML-based systems review the same amount in seconds.
An AI-driven solution enables the automation of routine ticket and query processing tasks and full or partial elimination of human involvement in the process.
Such ML techniques as sentiment analysis, ticket categorization, keyword analyzer can help tailor a custom solution to specific support service needs.
By opting for AI development services and a custom-made AI-led solution, you choose to focus on your clients’ expectations and creating a lasting customer experience.
Multi-Factor Authentication and the Identity and Access Management Capability Maturity Model, Part Two
And now that Identity Automation’s Co-Founder and Identity Fellow, Troy Moreland, has walked us through the full MFA Maturity Model in our recent webinar, Advancing Your Identity Management Strategy with the IAM Maturity Model, Part 2 - Multi-Factor Authentication, we’re ready to jump right into the remaining two levels— Adaptive and Intelligent, as well as the steps your organization can take to achieve them.
We left off part one at Level 2, or the Advanced level, where all three authentication factors (“something you have”, “something you know”, and “something you are”) are supported, achieving true MFA capabilities.
In addition, organizations in Level 2 have authentication policies that are flexible and fine-grained, providing users with authentication options that don’t disrupt the productivity of their day-to-day tasks.
At this point, you’ll also need to start thinking about how to refine these policies based on various contextual factors, such as time of day, day of the week, network origin, and whether the device is trusted.
For example, if your organization only operates out of the United States, an international login attempt would be considered higher risk, and therefore, require a stronger authentication policy for access.
So, if your organization typically operates 8AM - 5PM, Monday through Friday, an attempted login outside of that window of time could be flagged as high risk with stronger authentication policies associated.
While voice and face recognition are excellent examples of artificial intelligence driven authentication methods, there are other factors, such as keystroke patterns, which learn over time how you interact with the keyboard.
For example, school districts have a wide range of users utilizing their RapidIdentity single sign-on portal—anywhere from kindergarten students all the way up to advanced system administrators.
While a kindergartner needs age-appropriate authentication methods that overcome struggles with reading and remembering traditional usernames and passwords, a system administrator with unfettered access requires more stringent authentication than a typical end-user.
In this webinar, Troy Moreland, Identity Automation’s Co-Founder and IAM expert, provides actionable insights into how to evaluate your organization’s current authentication maturity level, take your MFA strategy to the next level, and even move away from using passwords altogether.
- On 18. juni 2021
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