Sesame is India's first Large Language Model (LLM) specifically designed for the banking, financial services, and insurance (BFSI) sector. Sesame will pay a major role in the adoption of advanced AI technologies in the financial services industry.
BFSI - banking, financial services, and insurance sector.
Innovators Behind Sesame
Sesame (Bengaluru, May 7, 2024) unvailed by Setu, a leading Indian fintech company and part of the Pine Labs Group, in collaboration with indigenous AI research firm Sarvam AI. Developed in collaboration with indigenous AI research firm Sarvam AI, the company said this marks a "ChatGPT moment" in financial services.
The unveiling took place at Adbhut India, an event organised by the non-profit People+ai, in the presence of Nandan Nilekani (co-founder and director of EkStep Foundation), Shankar Maruwada, Tanuj Bhojwani (head of People+ai), and other major persons in fintech, AI, and digital public infrastructure.
Setu, part of the Pine Labs Group, is a leading API infrastructure company that is building the rails for digital financial services in India. offering services across bill payments, savings, credit, and payments. With the Reserve Bank of India's license, company works with banks, insurance companies, lending firms and other financial institutions for financial architecture integrations. With a mission to democratize access to financial services, Setu enables developers and businesses to create innovative financial solutions through its open APIs and tools. for more detail click here https://setu.co/
Sarvam AI was founded in July 2023 by Vivek Raghavan and Pratyush Kumar, Sarvam develops a full-stack offering for Generative AI, ranging from research-led innovations in training custom AI models to an enterprise-grade platform for authoring and deployment. The company received around $41 million in funding from Lightspeed. for more detail click here https://www.sarvam.ai/
Strength of sesame
Sesame leverages the vast data ecosystem of India's digital infrastructure and vast amounts of financial data available both internally and externally in a compliant manner, to power various features, including improved credit underwriting, fraud detection, loan monitoring, upsell or cross-sell, and personal finance advisory. Setu and Sarvam AI have created a solution that is both domain- and region-specific, tailored to the unique requirements of India's BFSI sector. this will enables enterprise customers to make smarter and faster credit decisions, while also providing personalized financial services to their customers.
Features of sesame
Domain-Specific LLM
Sesame is tailored to the unique requirements of India's BFSI sector. It leverages the rich data ecosystem enabled by India's digital infrastructure.
The model provides various features
- Improved Credit Underwriting: Helping financial institutions make smarter credit decisions.
- Fraud Detection: Enhancing security by identifying fraudulent activities.
- Loan Monitoring: Keeping track of loan performance.
- Upsell or Cross-Sell: Recommending relevant financial products to customers.
- Personal Finance Advisory: Providing personalized financial advice.
Harnessing Financial Data Responsibly
Sesame can access vast amounts of financial data both internally and externally in a compliant manner. Enterprise customers can benefit from faster credit decisions and hyper-personalized financial services across the entire customer lifecycle.
Integrate API
Business can use open APIs and build innovative In-Store Integrated payment solutions and payment gateway solutions in there system. Get access to secure payment APIs and get coding. for more details regarding integration and pricing click here
Aim of sesame
India has led the way with groundbreaking innovations like Aadhaar and UPI, Setu aims to build meaningful, compliant, and responsible AI applications that showcase India's leadership in Applied AI. Setu aims to empower BFSI customers to make smarter and faster credit decisions using Sesame, while providing personalized financial services across the to customer.
For more details can refer here
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