Arria NLG for
FINANCIAL SERVICES
Top Use Cases
- Fund Performance Commentary
- Market Update Commentary
- Equity Attribution
- Fixed Income Attribution
- Risk-Adjusted Attribution
- ESG Attribution Methodology
- MSCI Index
- AML – Financial Intelligence
- Earnings Reports
- M&A Due Diligence Reports
Empowering the Finance Sector with Natural-Language Insights
Data-literate finance organizations possess the critical ability to retrieve, structure, analyze, and leverage data to their advantage. A seemingly infinite number of sources continue to produce endless streams of data that grow deeper and more complicated each day. In banking, this means that fluency in the practices of data analytics and data science is paramount. Arria’s Natural Language Generation offering for financial services was built with these specific data challenges in mind, and we have worked closely with Financial Institutions to develop this technology in a way that provides the entire finance sector with AI-driven report generation — enabling improved data communication and faster decision-making.
Meet the Expert
“NLG dramatically reduces the amount of time clients spend writing personalized client summaries and reports.”
NLG for Fund Commentary
See how natural language technology improves the accuracy of fund performance commentary
Arria NLG for Financial Services
Using NLG to accelerate decision-making and information delivery
Arria for Business Intelligence
Create BI dashboards that are simpler and faster to interpret with generated written summaries
Data and Analytics with NLG Inside — A Breakthrough in Financial Data Delivery
“We have built a set of NLG capabilities in portfolio management, portfolio analysis, and performance measurement that dramatically reduces the amount of time clients spend writing personalized client summaries and reports.”
INTERACTIVE DASHBOARD
See Arria in Action
See how you can quickly identify, communicate, and action key insights with configurable, out-of-the-box NLG narratives — based on visuals, or all underlying data within your existing dashboard.
