Arta Expands Arta AI Platform for Global Wealth Managers

Nov 7, 2025
Arta announced the global expansion of its Arta AI platform, adding new institutional clients including Bank of Singapore, Hong Leong Bank, and Ethivo Asset Management. The AI Sidekick tool aims to support financial advisors and wealth managers with analytics, automation, and client engagement capabilities.

Arta has expanded its Arta AI platform for global availability, announced in a press release. The platform, designed to assist financial advisors and wealth managers, now includes new institutional clients such as Bank of Singapore, Hong Leong Bank, and Ethivo Asset Management.

Arta AI provides an AI Sidekick for advisors, integrating client portfolios, firm data, and market research through a conversational interface. The system enables portfolio analysis, Monte Carlo simulations, stress tests, and multilingual communication while automating analytical and reporting tasks.

The platform integrates into existing banking and brokerage systems, allowing for white-label deployment and firm-specific customization. It connects client data with CIO research and risk models to generate personalized investment recommendations and reports.

Bank of Singapore is deploying Arta AI to enhance services for external asset managers and family offices, while Hong Leong Bank will use it to support relationship managers in delivering investment opportunities aligned with the bank’s risk framework and model portfolios.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Finance AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Finance AI Weekly

Weekly newsletter about AI in finance. Covers AI-driven trading, fintech innovations, and data analytics transforming markets

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.