 Well, in a country like India, a diverse country like India, with 1.4 billion population and the credit penetration is barely 450 million. So you know that if you're looking at a one-third or a one-fourth kind of a penetration in the formal credit system, right, not to increase this, of course, you need access to data. You need access to digital data, right, for easy underwriting or easy credit extension. And that's where the government and the other financial institutions have come up with this concept of using alternate data. So in case if the segment does not have a formal banking history, but is you want to induct him in the formal lending ecosystem, so how do you do that? Then the surrogate, which is the alternate data is used. And primarily telecom utility and payments, these are the broad three areas which are used. One telecom is the most preferred one because it has 100% teledensity in the country. So you know that everyone definitely has a mobile phone and definitely has got some transaction. And that's where exactly big data comes in because we're looking at a billion plus telecom users, a billion plus transactions, right? Now how do you churn them out? How do you create an underwriting model out of this transaction? And that's very interesting. All financial institutions, or rather, let me say most of the financial institutions are looking at telecom as a reliable alternate data source. And many analytical companies, credit bureaus are piloting this project where they tie up with telecom operators, get access to the data, right? Using big data technologies, they underwrite the data and create an underwriting score, almost like a bureau score, like it's a surrogate to a bureau score. And financial institutions do recognize that it's a surrogate and they do take a leap of faith and extend some credit products, which are maybe small tickets, definitely not high value tickets. But essentially they want to check the repayment pattern and the repayment discipline. So that's the problem that they're solving rather than access to credit. So they're okay to check with small credit products of $200, $400, and then eventually in three months, four months, see their repayment cycle and then decide what are the next steps are. So definitely big data is helping a lot across industries, be it telecom, utilities, payment in solving the problem of access to credit for the unbanked, right? You can open a bank account, but you need the credit product to use your bank account, right? So that's definitely there. And India is at an inflection point of adopting alternate data for accessing credit products, formal credit products. It's a typical classical marketing problem that is emerging out of the use case of alternate data for underwriting. So as a B2B, as an organization, I can tie up with a telecom operator, take data from users, prepare a model and prepare a score. But as a user, how do I know that I can take my telecom data, walk into a lender and say that, hey, you know what, this is my telco number or MNO number, take my number and pull out my score, and can I get a loan? So there is a demand side and there's a supply side, right? While we can work on the supply, but we also need to work on the demand side, where consumers are aware that, yes, as an alternative, if I don't have a banking history, but if I have a good telecom usage that can be used as an alternate method to get access to credit products. And that's where companies like Visa, where I'm a chief business officer, we solve this problem, we work with institutions, we create segments and cohorts of which, to whom they've already underwritten, like a pre-qualified product. And then we reach out to those consumers, either through digital or maybe a conventional marketing process like a call, a telemarketer call, telling them that if you're looking for a small ticket loan, you are credit worthy because we have got access to some other information. If you're looking for any credit product, give your consent and fill up this form digitally and we can look at extending those products to you. Now that is a big demand problem to be solved because not everyone is aware that, you know, what are the alternate data sources that have used, it's a very industry jargon, it's not a consumer jargon, right? So as a consumer, they are not even aware. So they feel that, okay, if I don't have banking history, there is no way that I can get a product. And that's where I go to market or rather I would say consumer awareness that if you're not having access to formal credit, but still if you're having reliable telco usage, you can request for some alternative products to be extended to you. So that's where it's a big industry and it's a big use case to be solved at an organizational level. We are talking about solving problems using alternate data. But in a country like India, approximately 700 million people don't have access to digital data apart from a telecom data, right? And the telecom data, while may or may not be useful in terms of predicting models, but what is the alternate method? There is no digital record. They've got their house records, which are a piece of paper or some land record, which is a piece of paper, which is issued by government some one or two decades or three decades ago. So how do you, you know, we talk about alternate data, but I think so in a country like India, and I'm sure it's more applicable even in Africa and large parts of Southeast Asia, where analog data is more dominant than digital data. What are the methods for financial inclusion for giving access to the analog data? So we talk about alternate data, but we need to look at alternate method altogether. So that's an interesting concept where the agri-tech, the agricultural technologies companies in India, they start using satellite imaging. Like, so for example, if a farmer wants a loan, right, how do you know that the piece of land is owned by him, right? It's a piece of paper that he's got. I can fudge it, I can write something, you know, so they use satellite imaging and they chalk out the boundaries, right? And then that is verified with the land record and overlaid that with his telecom usage that yes, his towers are the same. He's, you know, the telecom tower tells the location. So it's an overlay, it's an intersection of satellite images, the telecom tower location, and a joint model is created to extend a loan. Now, this is where I'm talking about an alternate method altogether, you know? So the paperwork is more like a validation, not the primary source. So there are many interesting data points and many technologies, including big data, satellite imaging, artificial intelligence, that are being deployed in the country to solve financial inclusion and serve and convert people from the unbanked to the bank and extend formal credit system.