The Bud.ai platform will enable any financial services organisation to transform their transaction data into new customer insight and achieve high levels of personalisation at scale in customer experience.
Bud has a track record in its development and application of Al, machine learning, and Natural Language Processing in banking and financial services. Bud has been developing foundational language models on top of banks first-party transaction data and consumer-permissioned, third-party Open Banking data since 2018.
This development represents an augmented logic core that can generate new insights for consumer and corporate users in real time. With a growing capability to comprehend financial data, Bud.ai allows developers, marketers, and risk professionals to integrate deep financial insight into their workflows, growing engagement through meaningful hyper-personalisation, and generate more opportunities to match consumers with the right financial products.
The two products offered by the company—Assess, a solution for lending and determining affordability, and Engage, a solution for individualised money management—are built on Bud's recent Al core. Financial organisations can adopt Bud's extended language model (LLM) technology through an easy integration procedure. Bud's transactional data models, which have been improved over the course of five years, can be combined with this technology to allow banks, lenders, and other financial organisations to easily transform their sizable pools of unstructured data into more understandable representations of a person's financial situation or thorough summaries of the institution's wider portfolio.
By introducing Jas, a customised generative chat interface, Bud is expanding its portfolio of products with a solution built on the Bud.ai core. Jas lets users to communicate with a skilled AI assistant who may help them with various aspects of their financial health, such as proposing acceptable credit products and providing financial planning advice.
Bud's generative Al chat interface uses Google's PaLM 2 large language model, to feed on enrichment and analysis driven by Bud's transactional data intelligence platform, and presents these insights directly to consumers, in an intuitive way, similar to the conversational Al programmes now being widely adopted.
Consumers can ask a multitude of questions, and be supported with straightforward, easy to understand, easy to action, and accurate, insights.
With Jas, individuals can take steps to enhance their financial resilience, whilst financial institutions can customise the service to align with their specific objectives around customer engagement and satisfaction, product upselling or cross-selling, risk management etc. As Jas evolves, it will transform into an action-bot, capable of providing tailored recommendations and executing tasks on behalf of customers and clients.
Bud's collaboration with Google Cloud is helping companies in their digital transformation strategies by enhancing customer engagement along financial journeys. Officials from Google emphasised the use of generative AI for improved workflows and user experiences. Since 2018, Bud has been developing language models leveraging bank data, resulting in secure and personalised AI capabilities. Bud’s executives see this as a breakthrough logic core that provides real-time insights for individuals and corporations, enabling better marketing, customer segmentation, and operational optimisation.
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