Meet Mr. Chetan Pandya: Integrating AI into Finance with Credit Siddhi


In today’s rapidly evolving financial landscape, the integration of artificial intelligence (AI) and big data is revolutionizing how enterprises and financial institutions manage credit-related processes. One company at the forefront of this transformation is Credit Siddhi, a pioneering force in building AI and big data-driven credit ecosystems. Their innovative platform enables businesses to seamlessly acquire, appraise, transact, monitor, and collaborate, transforming traditional credit practices.

In this exclusive interview, we have the privilege of speaking with Mr Chetan Pandya, one of the visionary minds behind Credit Siddhi. Let’s look into the company’s journey, the transformative power of AI and big data in credit ecosystems, and his vision for the future of finance.

An introduction about the founder by himself

I am Chetan Pandya, the founder of Credit Siddhi. I have spent 27 productive years in banking and financial services, with a long stint in Kotak Group. I was very lucky to be mentored by banking experts, which have inculcated a deep sense of risk management over time. I came out of my professional Avatar in 2019 and started this company in 2020.

What exactly is Credit Siddhi? What was the plan?

In 2014, I shifted from Kotak Group to a technology company  Intellect Design based in Chennai. I was heading business for them, cloud banking for smaller banks. So I headed up deep inside the country because that was where the customers were. As a very curious person, I used to think about why particular things are happening; and as I went deeper and deeper into those banks, talking to the management, and customers, what I realized was 95% of the customers have a business. Only 5% of customers are getting a salary.

A major part of the population is running a micro-macro business. We don’t know if it is by choice or by some force, no one knows. But largely India is a country where people are doing business and earning a living by themselves. But, if you look at how those guys are doing it, with a lack of credit or any guidance, which might help them borrow better does not exist.

 It is pretty exploitive for most of them when they get into formalization because invoices come thick and fast but their ability to generate revenue out of formalization is limited.

They contribute a significant percentage to the GDP; we have a dream of 5 trillion dollars for the economy. Unless and until these businesses start doing well, it would be a very hard scenario to achieve. With all the problems that I saw, I concluded that as soon as you can solve the credit problem then things would improve for them. But the conventional credit systems would fail them. Because, none of these guys have balance sheets, the ratio or return which could be used for doing things. This is where I thought of using technology, bringing their unstructured data into a particular format, cleaning it and then making it available to the lenders as well as others to make the digital profiles of these customers and based on those digital profiles you can have an actionable credit assessment or you could have an accessible supply chain relationship.  As we went deeper into it, we now pretty much do things on ML and on the conventional path. The results have been very good. Borrowers who had no credit history have come to us, got into the system, got themselves rated for various things that credit assessment needs, and get credit from the system. From the common banking and financial channels. Some of the guys who started with us, the first loan was 29% are now with our banking partners, getting credit at 12%. So that entire 29 to 12 is an addition to his bottom line. It makes him more viable in the market. It gives him more confidence to do things. And as he proceeds, if he or she applies himself, maybe some of them will become very good.

How is Credit Siddhi different from other credit ecosystems in the market right now?

So our focus is clearly on MSMEs and within MSMEs, our focus is on guys who are digitally Grey. Let me explain what is digitally Grey is. So a person who has a digital footprint has digital know-how. everything is available for him from various registries and even digital exhaust to be able to appraise them. And that is what maximum fintech and BFC and everybody are doing business because it’s easy to do digitally.

Grey are the guys who have basic information in digital. Everything else is on paper or has to be physically or manually verified for you to do things. Our focus is this market. We started as 40% automation, 60% manual. We moved into 80% automation, 20% manual. The last bit, which we are doing now would even take that out and let’s say July 100% automated process for anyone to come to the platform and do things for that service.

According to you how AI and technology are helping in transforming credit systems overall?

See, the conventional processes are understood by you and me. All of us have read that in post-graduation and doctorate that if you have this ratio and this liquidity, you are a good business to do, but take it a step ahead. All these businesses which have good ratios collapse or sometimes don’t do it or are not a good credit risk. AI and ML part helps us to connect disparate data points which is not possible in the conventional system. It could be because of weather conditions in a particular location. To the cash flow of that particular month, how would it impact for a period of time? So ML or let’s say automation is once done, you keep on applying various parameters to each other and find these relationships. These relationships over a period of time rectify for better credit. Now, the one part that we are doing and this is why I’m saying the 20% part where we are automating the most complicated part of credit appraisal for MSMEs that is a personal discussion.  The bot calls the user, at the appointed time. The user gets onto the video call and answers a set of 17 questions. These 17 questions’ answers are converted to text, the text is converted into data and goes into various mechanisms to become operational data. All the frames of the video also get into the system enabling the psychometric evaluation of the user. Every twitch, every hesitancy, everything is captured as data and then that also adds to the appraisal. I would not be able to do it or anybody would not be able to do that in a conventional. It’s only ML which is allowing us to do that.

How was your journey of becoming a founder? What did you learn?

Number one, you need to have perseverance. Every day something is going to break. Every day a new surprise will come. You need to not get irritated by that and keep your focus on what you want to do. Do not discuss too many things with people. Many will give their viewpoint on the entire thing, or a newspaper report which is pretty comprehensive in terms of saying that boss, this is already sorted or this is a big problem. Don’t get mesmerized by media or an opinion that you listen but learn to decipher every wart in a conversation or opinion or an article or theory. It’s you who has to make the call. Don’t let others make the call. You have to be very careful. Another thing, it’s lonely so if you have a very active social life you can forget about being an entrepreneur, everything comes second. Like my wife says Chetan has a kid called Credit Siddhi, he has no time for anything. When you are building something it’s very painful for others around you to accommodate, conduct your time and your mood swings. Last but not least, always keep your financials in control. It’s very easy to get a trade and start spending money whether yours or somebody else’s. You need to understand that this money s the last money you have. So whatever you do, it has to have maximum ROI for your effort. If you are able to focus, you will go places. Attainment? How does attainment come to focus? If you do all those things, you will go places.

A piece of advice from you to the future generations who are planning to start something of their own.

Don’t do it half-heartedly. If you just have an idea or if you are doing it as a passing time, don’t do it until you are fully into it. Don’t even try and focus does not come in or that zinc does not come in a day. Take time for a period of time. Build your thesis. Discuss it with your people who give you an unbiased opinion about yourself. Everybody thinks that I’m an entrepreneur. It’s not possible. Yesterday night I have to get up at 02:00 in the night to write an email because I forgot about a job I could have done it in the morning or I could have just postponed it. But here you can’t. So I got to. So unless and until you want to do it like this and you are very clear.

The interview with Mr Chetan Pandya from Credit Siddhi has shed light on the remarkable advancements made in AI and big data within the realm of credit ecosystems. We have witnessed how their ground-breaking platform has disrupted traditional practices, empowering enterprises and financial institutions to optimize their credit processes. Through the seamless integration of AI-driven algorithms and comprehensive data analysis, Credit Siddhi has demonstrated the potential to enhance efficiency, accuracy, and collaboration in credit acquisition, appraisal, transactions, monitoring, and beyond. As we look to the future, it is evident that the transformative power of AI and big data will continue to reshape the financial landscape, offering new opportunities for growth and innovation.

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