OnFinance, an AI Startup from Bengaluru, is creating ripples in the Banking, Financial Services, and Insurance (BFSI) domain. Their distinct NeoGPT language model is designed to respond to the requirements of various financial analysts, advisors, and BFSI enterprises.
NeoGPT and National Stock Exchange (NSE) Client
OnFinance has also developed NeoGPT, an improved language model designed to increase efficacy, security, and performance in the BFSI environment. OnFinance became the first generative AI startup to seal the deal with the National Stock Exchange of India (NSE). This accomplishment proves OnFinance’s credibility and the possibilities that the company offers.
Financial Services
Financial Research systematically identifies, analyzes, and collects information on markets, economies, and investments. Equity Research evaluates stocks, segments, and overall corporate performance. Underwriting is useful when assessing risks and setting up insurance rates. Index Research assists in keeping track of market indices and benchmarks. Relationship management is useful in improving client contact. Compliance also plays a role in ensuring compliance with the rules and regulations. Wealth Advisory offers individual consulting services in the financial sphere.
Technical Approach
OnFinance constructs NeoGPT using reliable open-source structures such as Code Llama (Meta AI) and Mistral 7B (Mistral AI). The fine-tuning stage uses Q&A datasets from financial news sources such as Moneycontrol and the Financial Times.
Challenges faced by OneFinance during development
While working on NeoGPT, OnFinance faced several obstacles while building an AI model specific to the BFSI field. One of the biggest challenges in the application’s development was obtaining the appropriate, accurate training data on financial language and concepts. The model used in NeoGPT had to learn the financial news, reports, and lingo used in the financial markets.
Balancing between concrete and abstract was the focal point in the process. To balance between recognizing specialized financial requests while preventing overlearning, it was crucial to tune NeoGPT. Working in the BFSI sector, the solution had to provide robust data privacy and security measures. Due to the nature of OnFinance’s services, NeoGPT had to be designed to process queries while not violating the clients’ privacy. One major drawback of NeoGPT was the ability to interpret its decisions and explain how to arrive at certain solutions. OnFinance focused on increasing the transparency of the model’s decision-making process. Despite these challenges, OnFinance developed a powerful tool with a focus on innovation and data security, which is crucial for the BFSI industry.
Success Stories of OneFinance
OnFinance, which started operations in 2022, is on the path of growth in the financial sector. It was started by Anuj Srivastava, an alumnus of BITS Pilani. OnFinance created NeoGPT, a large financial learning model (LLM). NeoGPT provides targeted AI assistance for different procedures in banking entities, AMCs, or wealthy management companies. Its uses span data analysis, client relations, sales, and customer success.
Among these accomplishments, OnFinance secured a new client, the National Stock Exchange of India (NSE). That NeoGPT is the first generative AI startup to form a strategic partnership with NSE shows confidence in the capability of the technology. OnFinance does not allow customer data to be processed for training, retraining, or feedback purposes. This is an advantage since their focus on data privacy corresponds with the need to protect clients’ identities. These success stories are a testament to the operation of OnFinance and its commitment to advancing the BFSI sector.
Conclusion
NeoGPT of OnFinance is transforming the BFSI sector. It is created by expertise in AI and adherence to the data privacy policy. In the BFSI sector, data security concerns cannot be overemphasized. OnFinance guarantees that customers’ personal information is not utilized in training, fine-tuning, or feedback loop analysis. Clients’ top priority is data privacy, and their focus on on-premises solutions reflects this attitude.
