BofA launches AI for payment; AI fuels weather data demand in EU

Bank of America (BofA) (NASDAQ: BAC) has launched a generative artificial intelligence (AI) solution designed to save thousands of employee hours and provide instant answers to complex clients’ questions.

According to an official press release, employees of the U.S.-based bank can rely on Ask Global Payments Solutions (AskGPS), an in-house AI chatbot, to resolve customers’ queries. Previously, a complex inquiry could take an employee hours to complete, involving multiple phone calls to product specialists across multiple time zones.

The large language model (LLM) was trained on nearly 3,500 internal documents spanning product guides, term sheets, and frequently asked questions (FAQs). Jarrett Bruhn, head of Data & AI for GPS at Bank of America, noted that the solution was built entirely in-house without external influences.

Apart from saving thousands of employee hours, the new AI chatbot offers a range of benefits for customers. Clients will experience faster turnaround times for product and onboarding inquiries, while receiving tailor-made solutions that comply with local regulations across multiple jurisdictions.

“AskGPS turns institutional knowledge into real-time intelligence,” said Mark Monaco, head of GPS at BofA. “It’s more than a search tool—it’s a strategic engine, helping our teams respond faster and deliver the kind of clarity and advice clients expect in today’s environment.”

BofA has a long streak of incorporating AI into its operations, tailoring its deployment across four primary areas. The financial institution has achieved success with intelligent agents, search and summarization, content generation, and coding use cases powered by AI.

BofA’s Cash Pro Chat with Erica technology has seen a surge in adoption rates since its launch, with 65% of clients utilizing it for real-time account and transaction support. Furthermore, its CashPro Forecasting and Intelligent Receivables AI-based tools have gained significant traction since the start of the year.

The bank has increased its investment in distributed ledger technology (DLT) for settlements amid reports of an upcoming stablecoin offering for clients.

A slow and steady approach

While fintechs have taken a bold approach with emerging technology companies, traditional financial institutions are opting for a tentative push. In light of the risks associated with a data leak, the Reserve Bank of India (RBI) has proposed a framework for ethical AI in finance, warning that unchecked adoption will pose financial stability risks.

However, proponents are citing the prospects of using AI to comply with anti-money laundering regulations while providing personalized services to clients. Others are exploring AI for credit scoring and algorithmic trading as regulators beam a searchlight on the industry to protect consumers.

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AI fuels weather data demand craze for Europe’s largest forecaster

Executives at the forecaster disclosed that AI is fuelling the rush for weather data amid a raft of commercial use cases. ECMWF executives stated that its customers are feeding weather data into machine learning tools to make accurate predictions and gain a “critical edge” in key industries.

For energy traders, turning to AI weather tools is now part of their internal strategy to place bets in Europe’s renewable power markets. Swiss-based trading firm DXT Commodities SA has developed numerous computer models to predict climate-induced changes in energy supply and demand.

Energy traders are not the only ones paying top dollar for ECMWF data; the report also highlights insurance, media, and agricultural companies. Currently, these firms are spending up to $42,200 each year for access to weather data from the ECMWF.

“Data is a fuel for these businesses,” said Dennis Schulze, chairman of PRIMET, a trade association for private weather forecasting companies in Europe.

Keen on improving the scope of its offerings, ECMWF has revealed plans to provide low-latency forecasts for free download. However, higher-resolution data will be available for enterprises, but sources say the offering will be limited to a two-hour delay.

Currently, ECMWF operates the largest electronic record of weather observations, with a broad pivot towards AI. Apart from providing data for the AI machine learning models of its clients, ECMWF has adopted AI faster than other government-backed weather forecasters.

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Pivoting to AI for weather forecasts

The European forecaster decided to integrate AI tools in its workflows following the early successes of Google DeepMind’s GraphCast model. At the time, the AI-based weather prediction model outperformed conventional forecasters, such as the ECMWF, forcing a strong pivot to remain competitive.

Since then, AI tools have recorded advanced proficiency in forecasting storms and spotting weather changes that are difficult to detect. Several countries have adopted AI and emerging technology solutions to address climate challenges, with China and India leading the charge in recent months.

In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.

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