Are you weary of seeing the same or unrelated personal loan or credit card suggestions every time you open your banking app? Newgen Software, located in New Delhi, has developed a technology to assist banks expedite hyper-personalization!

Newgen delivers Gen AI solutions to banks and organizations, resulting in hyper-personalized recommendations. This new solution is intended for bank marketing teams, retail banking divisions, and data scientists.

Highlights:

• Enhances banking services by providing personalized recommendations based on individual behavior and preferences.
• Used by banks like Union Bank of India and IndusInd Bank to offer tailored financial solutions.
• Analyzes over 200 behavioral elements, ensuring unique customer experiences while maintaining data privacy and security.

LumYn, a newly introduced product by Newgen, has clients like Union Bank of India, IndusInd Bank, and ING Vysya Bank, among others. It is a hyper-personalized generative AI model that enables banks to give bespoke services to customers. Newgen says that their methodology provides personalized service and financial solutions tailored to individual interests. Unlike prior models based on age or account balance, the AI will examine an individual's tastes, spending history, and behaviors when recommending choices for the customer to pick from.

"It could be more about your behavioral elements, such as what you spend money on, what products you are interested in, and where you travel, because that is transactional data." "There are another 200 behavioral elements that can be extracted from this data," says Virender Jeet, CEO of Newgen Software.

"The experience of two end-users will differ depending on what is advised to them based on their profiles. No two consumers, or even comparable customers, will be given the same options. They may receive quite different offers that are extremely tailored to them," adds Jeet. "We provide what consumers are supplied as products in order to increase the quality of their service. So, we're working with the bank's corporate users to support them," he says.

LumYn's strong conversational AI capabilities will allow banks to gain a hyper-personalized understanding of each customer's requirements, behavior, preferences, and purpose in order to generate deeper interactions while maintaining data privacy and security. The AI model will be trained on financial data, namely transactional information, transaction history, and account history for a consumer.

The firm says that its suggestions are unbiased. In reality, bias issues are more prevalent in credit underwriting since models rely on past trends. "Our generative AI focuses on engaging and turning natural language into an internal theory that the machine can understand. The issue of bias is more relevant to credit ratings and underwriting than recommendation engines, according to Jeet.

"What we are seeing today is an outcome of 70% development over multiple years," Jeet adds. The Asian Data Sciences platform, the company's AI and machine learning platform, has been developed during the previous five years. "Our other technical components, which simply serve a product platform, have been built during the previous 20 years.