4. Your data, decisioning, and AI should act as one cohesive unit. If they don’t, you may see value from AI, but you’ll never be able to maximize its potential. 5. Your technology needs to make it easy to push your AI models live. You’d never rehire an electrician if their wiring needed you to flip 15 switches to turn on a single light bulb. 6. Decisioning data helps your AI optimize its performance. You need technology that empowers the continuous feedback loop between decisioning and AI. 7. Once your AI is live remember that you’ll need a simple way to retrain it and keep it accurate. AI technology with support for live retraining makes that process much more efficient. 8. The right technology can make your Risk and Data Science teams much more efficient. For example, having technology that can auto select the right model for the right task can save you an incredible amount of time. 9. Data is the food for your AI strategy; having easy access to the right types of usable data is essential. If you don’t have the architecture to support this, partner with a technology partner who does if you want to drive AI value quickly. 10.You can achieve value from AI-Powered Decisioning in 60 days or less. Don’t believe us? Let us show you how! BONUS TIP: When you select a technology vendor, don’t look at the technology alone, ask yourself whether this is a partner that you want to work with. Does their knowledge and experience complement your own? It should!
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