Ashish Tiwari on AI and automation and brand trust

We're delighted to be joined by Ashish from Home Credit India. Before we get into data, let's start the other way around. Where do values feature in your business? Because you wouldn't be who you are if you didn't have them. I think one needs to understand that while whatever you might want to think about and whatever the stories might tell you, lending is a very very important business. It's a very ethical business. At the core of it, ethics has to drive it. Compassion has to be layered around it. And as a brand, and I can talk about my brand, we are driven by our brand purpose of saying Zindagi Hit loosely gets translated to life as a celebration. It's about empowering people to extract more of their life now.

And it's a very interesting thing, isn't it? Because the act of lending, which is a form of risk management, it's very data driven, it's very deterministic. But in the end, it'll come down to why do you trust one business versus another, which is a whole bunch of kind of non-data things, right? At the end of the day, you are giving money and money has same size, shape and color. So for a customer to be able to decide from one business to another is about the trust factor you can generate. And that trust in a brand comes from things where underlining fact can be data, but the storytelling has to be very, very strong. And where you can invoke the emotional part. Because I've tried to understand money itself does nothing. It's useless.

Even if I lock you up in a room stash full of money, you won't be excited about it because if you can't do money is a means to an end. So, I mean data needs to be used to weave your storytelling. Data needs to be used to make those decisions. Try and understand. I get almost about 30,000 to 35,000 applicants applying for loans every day. Every day. And this is 24 hours. Sounds easy. But the equation gets much more complicated if I were to tell you that 60% of this comes between three hours of 6 to 9, which are the business hours. Between 6 to 9 p.m. most of the people will apply. And you need to make decision about what limit, what interest rate, and how much does a person get for how long tenure. Well, let's get into the weeds of this, right?

So, 20,000, 30,000 people come in, right? X of them are ratified automatically, presumably. Y are rejected. How do you use data to handle the remaining Z where you're trying to figure out credit worthiness and the rest of it? How do you actually use data at that point? The entire game is in data there because of from the… See, if you look at lending business at the core of it, any lending business is about while at the front it might look like you are giving out money, which is the easiest business to be into. You give me $1 trillion and I can distribute in next 30 seconds. The real business is to be able to give money to people who will return it back. Am I right?

So, the decisioning is about putting people at a scale of probability with the probability telling you that what is the probability of money coming back within the given time. It is also important because of then you are enabling a person to live a dream life rather than putting them into debt trap. And data here becomes at the core, at the center data drives decisioning about putting that probability together. So, whether it's a first party data, augmented data, data from our previous learnings, which is a non-PI one, put together into a model and there is the model tells us that whether the person gets the money and for what all parameters are attached to it.

Okay, so data, it's a bit like the conversation with Abhinav, different types of data, different types of methodology all sort of converging towards a decision with a lot of responsibility around that decision. But let's think about the manpower involved in this. We have a lot of viewers out there who are young marketeers. Do you need in Home Credit India, Ashish, marketeers who are fundamentally different to the marketeers that Gull needs or Abhinav needs? Do you need more people who are more data scientists than marketeer? Where do you stand on that? I don't need different kind of marketers because of marketing at a core. The fundamental of marketing remains the same.

It's about people, it's about your customers, it's about making their life easy, it's about the experience you deliver. And the storytelling and all of that. The data here, all one needs in any business in today's time, needs people who can understand data. There's a very old age saying about data in storytelling that not many truths you will find which do not have our data associated. But no lie has ever come without a number attached to it. Well that's very interesting isn't it? Because we're living in the kind of post and pre possibly Trumpian age, right? Where things like fake information, manipulation of information, all that kind of stuff has become absolutely prevalent. And that's where data does damage.

How do you stop that happening Ashish in your brand? I think some of the things that we do very very specific is one certainly comes about at an individual level. It's about data privacy and guarding our consumers. Educating them very much about the best practices in the industry as well as at the product level, at the individual level. So we have a complete content play out there. Whereas we push out content to our consumers helping them understand their basics better. At a corporate level and at an industry level, I think both the regulator as well as industry is doing a lot of initiatives to educate consumers about what is right to be done. And try and understand as an industry, our category flag is about trust.

And you cannot win into the category if you are not able to educate your customer rightly. If you are not able to provide them the right information. If you are not able to give them information when they need it the most. And these are some of the things which all of us do. Well it's an interesting thing isn't it? Because you are a national scale business like Abenev and actually everybody here. But along with guys like Abenev and brands like College Deco, you are dealing with people who either don't have data or at the very least need help interpreting the data. Right? So you are as much in the storytelling game because data on its own means nothing. Numbers are useless. I mean 2 into 2 just equal to 4.

Now you don't know whether 2 into 2 is a interest rate calculation or it is about the IRR or it is about the money or it is about a cost or it is about unit versus money. What are you talking about? So there has to be a reference of frame which changes everything around data. And hence data alone is useless. And that's where I think today's marketer need to understand we are not living. We have in past 15-20 years the world has changed very very drastically. Earlier there was a dearth of data. Today there is a I think we are living in an over. We are drowning. We are drowning in data completely. So it is not about big data. It is about the crucial specific small data which you need which can help you build better connections to your customers.

Can help you to help your customer lead a better life. And if you are able to use that small data I think you have done your job. I can't end this show Ashish without talking about AI. Is it your forecast in a couple of years time or even a couple of months time my producer is going to replace me with a laptop. I mean they can probably but then they will not have viewers then the viewers will be bots I think. They can do that if they are producing a show for bots I'm sure they can do it for the laptop. I like the things you say Ashish. Please tell my producer the same. You've been an absolutely fantastic guest. Not enough time. Have a terrific 2024. Thank you so much. Thanks Jasper and same to you. Thanks for having me.