About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

SmartStream Air Version 6 Takes Automation and Exceptions Management to the Next Level

Subscribe to our newsletter

SmartStream Technologies has released Version 6 of its SmartStream Air cloud-native AI data reconciliations solution. The release includes two new features: enhanced exceptions management capabilities; and attribute-by-attribute matching.

The exceptions management enhancement increases automation, while the solution’s AI capabilities manage discrepancies during the reconciliations process by creating exception cases. Users can track the status of exceptions, assign cases to relevant teams or users, and add supporting comments or attachments.

Version 6 also simplifies user options for defining automation rules for exception management by including a pre-defined library of commonly used automation rules that help users achieve rapid set up.

The new version also simplifies the reporting process with higher levels of automation for attribute-by-attribute matching. This allows users to check far greater data sets than seen before and validate data integrity across all shared fields to provide accuracy. Validating data integrity across a huge number of fields, particularly for reference data, regulatory and intersystem reconciliations, helps to build a strong data governance framework to ensure data quality, completeness and accuracy of reporting.

SmartStream brought SmartStream Air to market in September 2019 and has since continued to release new versions that update and enhance the solution. The company’s data scientists are developing the platform to support limitless data types.

Commenting on Version 6, SmartStream CIO Andreas Burner says: “This release recognises that organisations need to modernise their operational blueprint and use the latest AI technologies to evolve data strategies that better support changing business needs. Many of the tier one buy- and sell-side firms we speak to highlight the importance of being able to spot both data and reporting irregularities in one control framework. Having better control means they can show regulators that they’ve taken all the necessary steps to ensure their data is both complete and accurate.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Navigating a Complex World: Best Data Practices in Sanctions Screening

As rising geopolitical uncertainty prompts an intensification in the complexity and volume of global economic and financial sanctions, banks and financial institutions are faced with a daunting set of new compliance challenges. The risk of inadvertently engaging with sanctioned securities has never been higher and the penalties for doing so are harsh. Traditional sanctions screening...

BLOG

As Finance Sector Workers Embrace AI, Study Warns ‘Be Careful What You Wish For’

The potential real-world impacts of hastily deployed artificial intelligence rollouts have been highlighted in new reports that underscore the need for better-quality data and greater literacy in the technology. Financial firms that don’t invest in creating greater workforce awareness of how AI tools can be used are at risk not only of failing to optimise...

EVENT

TradingTech Summit London

Now in its 15th year the TradingTech Summit London brings together the European trading technology capital markets industry and examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...