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How Data and Dynamic Decisioning Enables a Frictionless User Experience

Dynamic Decisioning in Healthcare
Director for Healthcare Identity Solution Strategy

Rule Out Friction

How can you possibly provide a frictionless user experience? The potential risk hasn’t changed over time unless it has gotten worse. What has changed is the data-driven nature of the industry-leading cybersecurity solutions.

Including digital identity attributes and dynamic decisioning to your defense strategy will allow you to rule out friction based on your own rules. This gives you a sliding scale for friction and the ability to frustrate cybercriminals instead of trusted users.

Dynamic Decisioning – how it works
Dynamic decisioning in a cybersecurity solution is the ability to make instantaneous trust decisions based on many factors and inputs. This type of decisioning can be done behind the scenes and can determine if further authentication is needed. Dynamic decisioning helps you decide who is trusted and allows you to reduce friction for those users.

Persistent monitoring is required to make accurate trust decisions. What to monitor, allowable risk levels and definitions of suspicious behavior are up to you. Each organization has their own types of cybercrime they manage and defined risk limits. All of these are things that can be set up in rules. You won’t have to do this alone. Typically, there are standard sets of rules that can be used until your own data tells the story of what type of cybercrime or suspicious behavior you should be monitoring, this becomes your truth data. Also, most cybersecurity solution partners offer a set of standardized rules that have been developed based on similar healthcare organization findings.

What’s under the hood?
Data, rules and the power of artificial intelligence (AI) through machine learning (ML). When talking about an advanced solution with dynamic decisioning, it’s important to remember that the data it uses to make decisions is critical. A solution that offers the ability to compare online activity on your website to a vast data repository of past suspicious behavior is a powerful tool. This along with your own truth data helps you get the most preemptive protection.

How do these rules work anyway? The application of rules is accomplished through AI and ML. Industry-leading solutions are monitoring all website activity and respond with decisions based on rules. For example, someone logs into your website but mistyped the password twice, the solution uses a predefined rule to decide if further authentication is required. The beauty of rules is that you can be very specific and get alerts on activities that you know are most important to monitor.

ML is computational learning using algorithms to learn from and make predictions from data, just like we make decisions from experience. ML uses past data or experience on many dimensions such as device information, event velocity, and geographical location to learn cybercrime patterns. ML can learn these cybercrime patterns and classify a future event as such or not.

Look for flexibility
Rules can get complicated, but you control how deep you want to go. When assessing dynamic decisioning solutions, you’ll want to ask their analytics experts about options within rule sets, including standard sets and customization. A good solution partner has analytics experts that you can rely on. With an advanced solution, you’ll have the option to go very deep with rule logic. You can go deep or not – it’s entirely flexible.

Using your partner’s experts is great, but sometimes you don’t want to wait for someone else to make changes to your rules. Look for a solution that has a clear-box rule set. This allows you to study your rules and make changes when you are ready without assistance. Some solutions don’t offer this flexibility. More complicated rules are typically not available for editing without assistance. Very complex rules are best revised by an analytics expert that built it.

Cybersecurity solutions offer the ability to offer a frictionless user experience for trusted users. To get there, organizations need to use a solution that can identify users correctly, using large identity data repositories and rules to get accurate decisions. As an organization gains confidence in the results, more friction can be removed. Given the right tools, you can frustrate cybercriminals instead of your trusted users.

Read the “Top 10 Healthcare Cybersecurity Tips: Using Digital Identity to Detect Bad Actors to learn how to use digital identity to maintain a positive healthcare digital experience and get the security you need.


The DNA of Healthcare

At LexisNexis Risk Solutions, our goal is to provide the healthcare industry with insights and innovations to improve outcomes, grow market share, reduce fraud and increase compliance.

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