Finqy has secured USD 2 million in funding, planning to expand its customer base and its range of products. Finqy leverages technology to assist sales professionals in the insurance, credit card, and loan sectors through its B2B2C business model.

Supported by over 100 financial and banking partners, Finqy provides AI-powered tools designed to simplify complex financial decisions and improve customer engagement in the realms of credit cards, insurance, and loans. The platform's approach marks a notable shift in the industry. Finqy is targeting unicorn status within the next 3-5 years, focusing on continuous product improvement and expanding both domestic and international market presence.

The company is committed to transforming the BFSI landscape by integrating technologies such as AI, machine learning, and data analytics.Upcoming initiatives from Finqy include the launch of Q, a personal finance management app, and Test My Card, a product focused on credit cards. AI and machine learning in BFSI AI and machine learning are revolutionising the BFSI industry by introducing solutions that improve customer experiences and simplify financial decision-making. These technologies leverage vast amounts of data to provide personalised recommendations, automate routine tasks, and improve operational efficiency.

For instance, AI-powered chatbots and virtual assistants are being used by financial institutions to handle customer inquiries and provide support 24/7, improving response times and customer satisfaction. Machine learning algorithms analyse customer behavior and transaction patterns to offer tailored financial advice, detect fraudulent activities in real-time, and customise product offerings, thus improving the overall customer experience. In the realm of risk management, machine learning models are employed to predict and mitigate potential risks by analysing historical data and identifying emerging trends.

These models can assess creditworthiness more accurately by evaluating a broader range of factors beyond traditional credit scores, leading to better loan underwriting decisions and reduced default rates. Additionally, AI-driven tools are used for portfolio management and trading, where they analyze market data, identify investment opportunities, and execute trades with precision, enabling financial institutions to optimise returns and manage risks more effectively. .