Our secret sauce is our risk models

Ritesh Jain Co-Founder of helps us to calculate how, and where, risk models, data science algorithms, AI engines, and ML.

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Ritesh Jain

India’s real-time payment mechanism is one of the best in the world – let’s find out why as we understand how AI and ML are redefining the landscape of loans and quick finance for MSMEs.


Ritesh Jain Co-Founder of helps us to calculate how, and where, risk models, data science algorithms, AI engines, and Machine Learning help in creating fast and fluid finance. He also gives a peek into why Open APIs, CBDC networks and UPI are important for the industry.

What’s the big difference between neo-banks or Fintech players vs. traditional finance players? Especially now when everyone can access or buy technology?

There is no doubt that technology is more accessible than ever. However, Fintechs and traditional finance players still have a lot of differences. Taking no credit away from the traditional finance players, Fintechs are more customer-centric. In addition, Fintechs, including Flexiloans, have a niche target audience to which we cater. Fintechs carry out an in-depth market assessment and target customers who remain underserved by existing financial services players.


For instance, there are categories within MSMEs (With an average loan amount of Rs 5 lakh) which the traditional financials are unable to identify, underwrite and service. Our operational costs are lower, the errors in service provisions are also negligible, and we can understand, evaluate, reach, and serve a section of the customers.

How crucial are open APIs to achieve speed and fluidity in the partner ecosystem and the collaborations you have?

The long-term aim of Fintechs is dependent mainly on effective APIs. The entire process of finding opportunities in the financial services sector, understanding the gaps, and providing the required services to the underserved section of consumers in a 100 per cent-digital environment could be facilitated only when open APIs are effectively used.


Open APIs help integrate with new partners for lead sourcing and new alliances that can help in digital assessment. It helps us to embed our journeys into partner ecosystems and empower end-to-end digital lending on a partner platform. It offers a superior, frictionless customer experience without significant drop-offs in the digital journey. Each partner can modify the customer journey to suit the needs of their customers.

Tell us more about your data science algorithms—how do you balance aspects like speed, customization, and precision with imperatives around privacy, fraud control, loan recovery, and compliance? Especially for collateral-free loans.

Sincerity dictates that we implement the best and most trusted mechanisms with utmost accuracy. Massive data sets can be analysed and integrated into the system, thanks to the sophisticated hardware and software that our team of technicians uses. We envision doing away with all manual processes from application to disbursal. Hence, we must ensure that the data science processes implemented are impeccable.


Our secret sauce is our risk models, trained over millions of records to accurately risk price the unsecured MSME loans in India. We use some advanced algorithms to train these models and keep them updated with the latest macro and micro trends that are picked up by the learning algorithms.

How do you build and maintain this strength?

We have a dedicated ‘Deep Learning and Technology Applications’ team to solve complex problems across image processing, scoring, digital extraction, credit analysis, and financial analysis through AI/ML technologies. Documents uploaded by customers are classified and tagged by our in-house ML engine.


Our in-house Machine Learning technologies can read hundreds of different uploaded documents in seconds, and our credit analytics tool can also provide a credit decision in real time. We also have 20+ proprietary data science assets and five patentable algorithms across the loan life cycle.

Are zero-proof models in use yet? Do you use synthetic data in your algorithms anywhere?

Our data science algorithms use synthetic or derived variables, which are very much a part of the systems. Our core strengths of holistic risk and growth models are made possible with their assistance.


Can you comment on the expected impact of SWIFT’s new cross-border CBDC solution? What’s different in terms of challenges and technology with your PayPal initiative?

In a world without borders, we should also understand that regulators are fighting hard to ensure that money laundering can be avoided and safe transactions between stakeholders can be facilitated. This is why the new initiative is quite remarkable. It aims to eliminate intermediaries and ensure that real-time payments are facilitated (just like we have in domestic payments systems).

This will improve interoperability in the global payments network. Through a single gateway, various CBDC networks worldwide would be interlinked not only with one another but also with the current payment systems. For us, this could be a game-changer as far as international trade is concerned. This will revolutionize the payments industry and even be disruptive to lending.


How much have India’s strengths with UPI helped to increase financial fluidity and inclusivity—any implications for your business?

As I mentioned in the previous point, India’s real-time payment mechanism is one of the best in the world. UPI has led the digitalization and Fintech revolution in the country. Cash usage has decreased, and overall confidence in digital payments has grown. A large number of sub-sectors within fintech, such as asset management, investment, peer-to-peer lending, and digital payments, have been facilitated by UPI.

All these factors combined have led to the formalization of the economy. UPI has enabled open banking in India with the addition of technology partners like Google and Amazon into the payments’ ecosystem, which has helped companies like Flexiloans scale.

Why did you choose the MSME space? What’s the roadmap ahead—especially in terms of technology?

There is no denying that MSMEs represent the most dynamic and potent section of India Inc. The sector is a significant contributor to our current economy and has the potential for sizable growth with some financial assistance. The MSME sector remains unmatched in its zeal and innovation for transforming lives at the grassroots level.

I recall visiting one of our customers in Udaipur with a small loan of Rs 5 lakh. That customer acquired a new shed, expanded his business, and employed five additional resources. He bought a scooter, and he now drops his daughter at school while coming to work and picks her up from school while taking a lunch break. Consider the effect that our 30000 loans have had so far. Stories of growth and progress like these make us immensely proud.

Regarding the technology roadmap, we are currently concentrating on the development of an end-to-end embedded finance stack, BNPL, and Colending stack.

Anything else you wish to share about your company and its vision?

We, at FlexiLoans, are just getting started. We want to make sure that everyone in the country benefits from digitalization and financial inclusion. I believe our nation has a lot of potential in every sector and sphere, and together we can help accelerate economic growth.

FlexiLoans is one of the few SME Fintech lenders with 100% digital origination and processing, resulting in an efficient and transparent customer experience.

We have an unparalleled digital reach with over 1,50,000+ new borrowing applications per month (we have disbursed loans in over 1400+ cities/towns) and continue to be a leading digital brand across the web and app. Our network of Partner ecosystems like Flipkart, Amazon, PineLabs, Mswipe, etc., allows seamless credit delivery to millions of small merchants selling on our 50+ partner platforms.

Technology is a core enabler for what you offer, right?

Our underwriting process is powered by advanced machine learning algorithms and alternate digital data of businesses. And this entire sophisticated model is delivered through a proprietary technology stack.

Despite the business loans segment having a varied set of documentation, processes – 75 per cent+ of our customer interactions are done by the system only. We use a broad mix of computer vision tech, IVRs, bots, social media assistance, and workflow automation to manage ~ 10 lakh documents and calls/per month with a small CRM team.

What sets your enterprise apart in a Fintech heavy market today? Where, and how, does technology play a differentiator?

We are focussing on attaining 100% digital fulfillment in a sector that comprises of small-sized MSMEs. This has not been tried or achieved before by any of the Fintech enterprises.

Ritesh Jain


By Pratima H