OnFinance, a Bengaluru-based finance startup is leveraging AI to bring solutions to the banking, financial services and insurance (BFSI) sector. NeoGPTThe company’s proprietary LLM is specially designed to cater to analysts, consultants and BFSI companies.

“Recently, we became NSE’s first GenAI startup. [National Stock Exchange of India] As a client,” said Anuj SrivastavaIn an exclusive conversation with, Co-Founder and CEO of OnFinance the aim.

Chat GPT for Enterprise Finance

OnFinance’s use cases include financial research for enterprises, equity research, AI copilots for underwriting, and a full spectrum of financial services in the form of index research. Additionally, there are relationship management, compliance and AI co-pilots for wealth advisory. “Think of it as ChatGPT, but for enterprise finance,” said Srivastava.

Operating in the critical financial sector, where consumers are wary of their data being used for AI, OnFinance ensures that criticality is maintained. Shrivastava identified this as the main reason why enterprises are shying away from ChatGPT APIs.

“All financial clients in India currently want on-prem solutions because they don’t want their data to go outside their cloud or infrastructure. That’s why they are still not able to use OpenAI, APIs, etc.,” said Srivastava. .

To ensure data security, the company ensures that no customer data is used for training. “We don’t use any data for training, fine-tuning or feedback loop analysis. We actually transmit the data to Copilot on a real-time basis, so you know it’s not being used for those purposes. Is.

Accelerating AI Startups

With the option of GPT stores and similar models, where companies can train and optimize their models with their proprietary data, finance startups like OnFinance find a better fit.

“What happens that he [models built on GPT Store] are not scalable, and cannot be generated. The main reason they are not executable is that you cannot directly access these APIs after creating a GPT. Even if you are able to access them, they are rate-capped, so you won’t be able to produce them,” said Srivastava.

“In GPT stores, any data or question your analyst asks will go directly to OpenAI,” Srivastava said.

Moreover, big players like Microsoft will never pose a direct threat to these companies as it only increases their business. Srivastava explains how, like his, there will be 20-40 companies building domain-specific models and turning to Azure for cloud and GPU compute.

“So the revenue they will be able to get from these 40 companies will be much higher than building their own domain specific models and selling them as copilots,” he said.

Interestingly, the startup has cloud partnerships with AWS, Google and Microsoft Azure. Also available on NeoGPT. AWS Bedrock.

Open source is still the way.

While data security is a priority, OnFinance’s proprietary models are built on open source models that are publicly available, namely Code Lama by Meta AI and Mistral 7B by Mistral AI. “On top of these two models, we fine-tune a lot of financial data sets such as AGM reports, credit reports, compliance circulars, and more,” said Srivastava.

In addition, the instructions are tuned to questions and answers prepared with information from 25,000 finance-related news websites, including Money Control, the Financial Times, and others. These datasets are created on a question-and-answer basis. “So, that’s why it’s so intelligent when it comes to financial data,” he said.

Partnerships and JioGenNext

OnFinance has already partnered with 15 major banks and wealth management players in India, including ICICI and exchange platform Centrum. It has recently tied up with NSE, Oyster Global, and Let’s Venture.

Startups are also part of it. JioGenNext, the popular startup accelerator program that promotes GenAI startups. Through this program, OnFinance will be able to offer its services to JioGenNext’s major tech clients.

Srivastava, a BITS Pilani alum, co-founded OnFinance Paresh SrivastavaWhoever is from the same college. Last November, the startup received $1.1 million in seed funding, and the two founders named Forbes 30 Under 30 Asia List

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