bridgei2i
MAY 20, 2020
But because of COVID-19, digital transformation is helping B2B models trying to replicate successful B2C models. And since they involve making better decisions using data-driven insights, AI & Analytics led applications are leading the way forward. So how does this data and analytics enable these models?
bridgei2i
JULY 28, 2020
She’s a mathematician, a classical musician and the author of the book ‘All things are possible: Unleashing the superhuman within.’ The way an AI system will operate in terms of engaging our employment sector is first of all, we need people who can build the models, who would be the mathematicians, computer scientists, engineers.
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bridgei2i
MAY 4, 2020
And as you earlier mentioned, that we are seeing an unprecedented rise in claims, traction in digital sales channels, and change in the product that sells, the traditional models are looking to be falling apart, and companies are rethinking and redefining business models and strategies. Anirban: That’s true.
bridgei2i
JUNE 2, 2020
As past data isn’t relevant anymore, current models aren’t going to work. Then, being able to validate models to see if they’re holding, understand how to incorporate signals in a nimble fashion to read and recalibrate existing or position models as a stress on loss. Compliance is another.
bridgei2i
MAY 4, 2020
But with that said, we do see a lot of newer business models emerging, new channels of customer engagement, and definitely bigger and newer business problems. There’s data everywhere and hence it is going to underlie every aspect of operating models of businesses. So overall, digital is just more important than ever. Moni: Right.
bridgei2i
JULY 8, 2020
Can we model the impact for such structural shocks? Last but not least, the crisis has also gotten enterprises to think of a lot of newer business models. Now, how do you use signals from a pre-COVID world to predict a post-COVID demand scenario? How do they translate into real-world behavior?
bridgei2i
MAY 26, 2020
In the twelve-year bull run that preceded this crisis with short secular uptrends; statistical forecasting models could not really be differentiated from high powered causal machine learning models. And I’m specifically talking about demand forecasting here. You know, in terms of performance, at least.
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