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Financial institutions can better understand the risk profiles of small suppliers by leveraging alternative data and machine learning, thus expanding access to financing. It requires accurate data, robust technology, and thorough risk assessment, crucial to ensuring the creditworthiness of suppliers at all levels.
And right now, you look back over 10 years, our active funds, 94 percent are outperforming their competitive group averages, 68 percent are outperforming their benchmarks. That means a low hurdlerate. We measure our success by how are our funds doing, and we look back long-term performance. So we do that.
But I would say generally, there’s less leverage in the system. But I don’t think this is a wholesale shift, we’re in a higher rate environment, obviously, for now. So you’ve got to be really mindful that you’re getting paid enough on a nominal return basis versus the risk-free rate.
Most clients, whether they’re individuals or institutions, have some sort of benchmark, a policy portfolio, some strategic asset allocation that they start with. It’s Mr. And, and Mrs. The first is it creates a return hurdle problem, whatever I’m selling. So it creates a fer 00:24:32 [Speaker Changed] Rate.
00:26:19 [Speaker Changed] It, it’s, it’s usually it is aggressive shorts from leveraged funds on s and p futures. Here’s how I would identify a core along you, you first and foremost, you identify what your benchmark is, how are you measuring your performance? You can see it also in futures positioning.
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