Creating a risk scoring model for influencer selection involves several steps:

1. Define Parameters: Start by defining what elements or signals you’ll include in your model. These can range from the influencer’s follower growth, engagement rate, to the authenticity of their followers, etc.

2. Behavioral Signals: Evaluate the influencer’s past campaign performance or engagement behavior. An influencer with stable and high engagement signals low risk.

3. Content Signals: Review the influencer’s content and its alignment with your brand – an influencer whose content resonates with your brand ethos poses less risk.

4. Audience Signals: Assess the influencer’s audience demographics and behavior. If they align with your target market, it reduces risk.

5. Assigning Scores: Once you’ve defined your signals, assign scores to these elements. This can be a simple 1-10 scale or a more complex model, depending on the level of analysis you want to perform.

6. Calculate Overall Score: Finally, calculate an overall risk score by aggregating individual scores.

Flinque, for instance, guides brands through steps like these, but there are other platforms, like AspireIQ or CreatorIQ, which offer similar functionalities. It’s essential to choose a platform that aligns best with your team’s needs and goals.

Risk models are not set in stone and should be continually adjusted based on your campaign experiences and learnings. Developing such a system can seem daunting, but you don’t have to do it alone. Various influencer marketing platforms like Flinque provide tools and metrics built for risk assessment of potential influencer partnerships.