LONDON, 6 October 2026 – Suade held its fifth annual RegTech Forum at Guildhall in the City of London. The Forum featured speakers from the Bank of England, FCA, ECB and EBA, alongside senior representatives from financial institutions including JPMorganChase, Goldman Sachs and Standard Chartered, as well as technology leaders and regulatory experts. 

Diana Paredes, co-founder and CEO of Suade, said: “The RegTech Forum 2026 once again demonstrated the importance of collaboration in shaping the future of financial regulation.” 

The programme centred on one question: how can firms adopt AI in regulatory reporting while keeping people in the loop and accountable for the results? Over the course of the event, speakers set out what needs to be in place first, from shared data standards and well-engineered systems to clear human oversight and ownership of AI-assisted outputs. 

The discussions highlighted a shared challenge for the industry: how to embrace innovation without compromising the accuracy, transparency and accountability that effective regulation requires. 
 

Building the foundations for responsible AI 

Opening the Forum, Sushil Saluja, Alderman at the City of London Corporation and former CIO of the Bank of England, highlighted the importance of collaboration between regulators and industry in establishing common standards and improving the quality of regulatory data. 

Drawing parallels between the historic hallmarking system and the need for trusted data standards today, Saluja emphasised that technological progress must be underpinned by strong foundations. 

“AI is pivotal, but we also know that AI on its own is not enough. We have to use the right tools for the job,” said Saluja. 

He added: “Innovation will only be as strong as the data and the controls underneath it.” 

His remarks reinforced the importance of addressing data quality and interoperability as financial institutions explore new applications for AI, while ensuring regulatory reporting remains reliable and auditable. They also underscored that better tools and data do not remove the need for people to exercise judgement and remain accountable for the results. For further context, see the Bank of England and FCA’s review of AI and machine learning in UK financial services. 
 

Moving beyond the AI hype 

In his presentation, How I Learned to Stop Worrying and Love AI, Murat Abur, Co-founder and CIO at Suade, examined the practical implications of AI for regulatory reporting. 

Drawing on Suade’s experience developing regulatory reporting technology since 2014, Abur challenged the notion that AI will simply replace existing software or human expertise. He argued that AI’s potential lies instead in building on reliable, well-engineered systems that can deliver precise results in highly regulated environments. In regulatory reporting, where errors can compound across complex processes, AI must be supported by dependable tools, structured data and systems designed to make information accessible and actionable. 

Murat also highlighted the importance of keeping people at the centre of technological progress. Rather than replacing human expertise, AI should act as a powerful tool to help professionals work more efficiently and productively. As he argued during his presentation, AI will need us more than we need it. 

For Suade, this means developing technology that enables firms to take advantage of emerging AI capabilities while retaining flexibility over the models they use and where they deploy them. Whatever tools or models a firm chooses, responsibility for the use of AI and the resulting regulatory outputs must remain clear and firmly with the firm. 

Why standardisation matters more in an AI-driven world 

Closing the Forum, Lyndon Nelson, Senior Technical Expert and Visiting Scholar at the IMF, former Deputy CEO of the PRA and advisor to Suade, offered a regulatory perspective on AI adoption, human oversight and accountability. 

Nelson used the analogy of containerisation to illustrate why standardisation is essential to technological progress. Just as standardised shipping containers transformed global trade, common data structures and interoperable systems can make complex regulatory reporting environments more accessible to AI. The ECB’s Banks’ Integrated Reporting Dictionary (BIRD) provides an example of collaborative work on common data models for regulatory reporting. 

“Open data models, common definitions, and open interfaces matter more in an AI world, not less,” said Nelson. 

He also highlighted the risks of relying on AI without meaningful human oversight, stressing that people must retain the expertise and authority to challenge automated outputs. In regulatory reporting, accountability cannot be delegated to technology. The Bank of England has also explored these challenges in its discussion of AI and financial stability. 

Nelson argued that across the AI value chain - model provider, software vendor, integrator and bank - accountability can slip through the gaps. Speaking in a personal capacity and as an advisor to Suade, he said the bring-your-own-AI approach was, for now, the right one because it leaves no doubt that the bank owns the AI and so owns the whole. 

“Everyone owns a part. Someone must own the whole,” he said. 
 

A connected, trustworthy reporting ecosystem 

From open data standards to AI-enabled reporting, the path forward depends on collaboration between regulators, financial institutions and technology providers. By improving the foundations of regulatory data and building systems designed for interoperability, the industry can reduce operational complexity and unlock new opportunities for innovation. 

The Forum concluded with a clear message: in an AI-driven world, the future of RegTech is not simply about automating existing processes. It is about building a connected, trustworthy reporting ecosystem in which people stay in the loop, and ownership and accountability are never in doubt. 

Reflecting on the event, Paredes added: “By bringing together leading voices from across financial services, regulation and technology, we explored how stronger data foundations, responsible AI and innovation can help address the industry’s evolving challenges and build a more effective future for regulatory reporting.” 

About Suade 

Suade has been developing regulatory reporting technology since 2014. Suade remains committed to advancing the transformation of regulatory reporting, helping financial institutions modernise through technology designed to support accuracy, efficiency and adaptability in a changing regulatory landscape. 

Media contact: 
marketing@suade.org 
020 3923 7049 

As geopolitical pressures intensify and regulatory requirements diverge across jurisdictions, global banks face growing challenges in managing cross-border compliance. The Navigating a More Fragmented Global Banking Landscape panel explored how financial institutions can respond to this complexity by building more flexible regulatory infrastructure, strengthening data foundations and balancing global consistency with local requirements.

Regulatory fragmentation is becoming a strategic challenge. Differences in rules, supervisory expectations and national priorities are making cross-border compliance increasingly complex and costly. While perfectly harmonised global standards may be unrealistic, firms can reduce unnecessary divergence by reusing established definitions, standards and reporting approaches wherever possible.

Global consistency should be the starting point, with flexibility for local differences. Shared data models, platforms and processes can reduce duplication and improve efficiency across international operations. However, these systems must also accommodate genuine jurisdiction-specific requirements. A flexible approach allows firms to maintain consistency without overlooking local regulatory obligations.

Effective regulatory reporting starts with strong data architecture. Data must be captured accurately and at sufficient granularity from the outset. Attempting to resolve missing information or inconsistent classifications at the reporting stage can be expensive and difficult. Building robust data foundations early helps firms meet reporting requirements more efficiently and adapt to future changes.

Data should be treated as a strategic business asset. High-quality, well-governed and accessible data supports far more than regulatory compliance. It can strengthen risk management, improve capital planning and inform broader business decisions. Designing data infrastructure around the needs of risk, finance and the wider business can deliver more sustainable outcomes than building separate systems for individual reporting templates.

Proportionality must reflect the realities of different institutions. Global banks and smaller international firms operate with different levels of complexity, resources and technological capability. Regulatory requirements and implementation approaches should account for these differences while maintaining appropriate standards of oversight and risk management.

Technology can accelerate transformation, but strong foundations remain essential. Automation, cloud infrastructure and AI offer opportunities to improve efficiency and shorten transformation timelines. However, technology cannot compensate for weak data quality, fragmented architecture or unclear governance. Firms must first understand the problem they are trying to solve and select tools that address it effectively. Not every process requires AI, and where AI is appropriate, clear accountability and suitable safeguards remain critical.

Data sharing requires careful navigation of geopolitical and legal constraints. As institutions seek to make information more accessible across their operations, differences in data protection laws, national security priorities and cross-border restrictions can create additional challenges. Firms must balance the benefits of data sharing with their obligations around privacy, security and local regulation.

Collaboration between regulators and industry is vital. Sustained dialogue and early engagement can help identify implementation challenges, improve understanding of firms’ operational realities and reduce unnecessary complexity. Closer collaboration can also support regulatory frameworks that keep pace with technological innovation while remaining practical to implement.

Ultimately, navigating regulatory fragmentation requires long-term investment, adaptable infrastructure and a culture that recognises the value of data. Modernising regulatory reporting is not simply a technology project; it requires careful planning, cross-functional collaboration, the right skills and sustained commitment. By combining consistent global foundations with the flexibility to meet local requirements, financial institutions can manage regulatory complexity more effectively and build capabilities that support both compliance and wider business objectives.

Panellists:

• David Covey, Director, Suade (Moderator)
• Lauren Dixon, Chief Data Officer, Financial Conduct Authority
• Giles French, Chief Executive, Association of Foreign Banks
• Tom Morrisey, Managing Director, Goldman Sachs
• Helen Bex-Vigoureux, Global Head Regulatory Change, Standard Chartered

This summary captures key themes from the discussion. Individual contributions have not been attributed to participants, in accordance with the Chatham House Rule.

As regulatory requirements continue to evolve, financial institutions must prepare for more than the next implementation deadline. Basel 3.1, the Fundamental Review of the Trading Book (FRTB) and the Integrated Reporting Framework (IReF) reflect the ongoing need for firms to adapt their data, systems and reporting processes. The Staying Future-Proof – Basel 3.1, FRTB, IReF and Future Regulatory Change panel explored how organisations can manage these demands while building capabilities that make future regulatory change easier to implement.

Regulatory change should be a long-term strategic priority. Rather than treating each new requirement as an isolated project, firms have an opportunity to strengthen their data foundations, improve processes and develop reusable capabilities. Each implementation should leave the organisation better prepared for the next change, rather than adding another layer of complexity.

Granular, high-quality data is essential for future readiness. As reporting requirements become more detailed, firms need reliable, well-classified data that can support new calculations and disclosures without repeatedly rebuilding their systems. Standardised data models, reusable capabilities and a clear separation between core data and reporting-specific calculations can make implementation more efficient and adaptable.

Data governance must be an ongoing discipline. Maintaining data quality, lineage, controls and clear ownership requires continuous attention. Effective governance cannot sit solely with technology or data teams; it depends on shared accountability across business, data and technology functions, supported by an organisation-wide culture that recognises the importance of reliable data.

Breaking down data silos creates opportunities for greater consistency and reuse. Combining accounting, statistical and other datasets where appropriate can help firms reduce duplication and respond more effectively to different regulatory requirements. Initiatives such as IReF and the development of common data dictionaries offer opportunities to support greater harmonisation, although differences in national requirements and regulatory objectives must still be considered.

Continuous improvement and automation can make reporting more resilient. Automated testing, frequent releases and more regular reporting runs can help firms identify issues earlier, reduce month-end surprises and improve the reliability of regulatory processes. Even when immediate deadlines require a focused delivery, organisations should look for opportunities to strengthen their wider data environment and create capabilities that can be reused.

Simplification and collaboration remain important to effective regulatory change. Reducing duplicated returns, unnecessary detail and unclear instructions can deliver practical benefits in the near term, while longer-term investment supports more integrated, data-led reporting. Early engagement with regulators, practical industry feedback and shared technical work can help ensure requirements are clearly defined, implementable and aligned with genuine regulatory needs.

AI can accelerate implementation, but human accountability remains essential. AI offers opportunities to support regulatory interpretation, code development, data lineage analysis and anomaly detection. However, firms must retain responsibility for interpreting requirements, validating outputs and maintaining effective controls. As regulatory processes become more automated, teams will also need broader skills spanning AI, data, regulatory expertise and commercial understanding.

Ultimately, future-proofing means building the foundations to adapt continuously, rather than simply meeting the next deadline. By investing in reusable data capabilities, embedding effective governance and adopting a culture of continuous improvement, financial institutions can make regulatory change more manageable and sustainable. The goal is to create flexible, reliable reporting infrastructure that meets today's obligations while preparing the organisation for requirements that have yet to emerge.

Panellists:

• Kira Snow, Regulatory Change, Suade (Moderator)
• Dan Waites, Head of Finance Transformation, Starling
• Helen Terry, Chief Data and Analytics Officer, Bank of Ireland
• Tanja Loman, Team Lead, European Central Bank

This summary captures key themes from the discussion. Individual contributions have not been attributed to participants, in accordance with the Chatham House Rule.

This year’s event saw insights from across the industry, with regulators, banks and technology leaders coming together at Guildhall, London on 6 October to discuss the future of regulatory reporting. From building trust in AI and keeping human judgement at the centre, to managing constant regulatory change and an increasingly fragmented global landscape, the conversations went well beyond the headlines.

Our key takeaways bring together the main themes, insights and points of debate from the day, including perspectives from our opening and closing keynote speakers. Download the PDF to see what the industry is thinking and what to prepare for next.

Read the full summary of the Forum, including the key takeaways from across the day.

Access key takeaways

Date: Thursday 12th November 2026
Time: 11:30AM - 12:15PM ET
Duration: 45 minutes
Format: Live Webinar

Join Suade's expert, Greg Goodall and Lindsay Fortnum, Senior Manager at Deloitte for a practical look at the latest developments from OSFI, what has changed in Canada's regulatory landscape, and what it means for disclosure, reporting and data processes at financial institutions.

The session will cover

• Recent developments in the Canadian regulatory landscape, and the key shifts in supervisory priorities
• OSFI's updated Pillar 3 disclosure guidelines, including IRRBB requirements and the expected implementation timeline
• Lessons from the first year of regulatory return assurance, and where reporting processes can improve
• Recent changes to the Domestic Stability Buffer and what they mean for institutions
• How to strengthen data quality and controls, and streamline reporting to reduce administrative burden

This session is designed for regulatory reporting, risk and finance professionals at Canadian financial institutions.

Tuesday 24 November 2026 | Bank, London

Celebrate the Season with Suade and join us for an evening of drinks, festive food and great company as we bring together peers from across the regulatory reporting community.

As the year draws to a close, it’s a chance to catch up with familiar faces, make new connections and celebrate another year in the industry. And, of course, you’ll leave with a little Christmas gift from Suade!

Register your interest:

As financial institutions explore new ways to improve efficiency and modernise regulatory reporting, choosing the right technology for the task has become increasingly important. The How to Use the Best Tool for the Job panel examined how automation and artificial intelligence can deliver meaningful benefits, while highlighting the importance of reliable data, effective controls and human accountability.

Automation creates value when it frees people to focus on higher-value work. Replacing repetitive manual processes with more effective tools can improve speed and efficiency, allowing specialists to dedicate more time to investigating risks, analysing data and supporting better decisions. However, these benefits depend on selecting technology that addresses a genuine business need.

Strong data foundations remain essential for reliable AI. Legacy systems, inconsistent data definitions and poor data lineage continue to present challenges for financial institutions. AI cannot compensate for fundamental weaknesses in the information it relies on. Investing in data quality, integration and consistent definitions is therefore critical to producing trustworthy outputs.

Accuracy requires more than generating an answer. Producing a report or recommendation does not guarantee that it is correct. Reconciliation, validation and robust controls are essential to ensure outputs are accurate, consistent and suitable for regulatory use. As AI becomes more capable, firms must retain the ability to verify its work rather than assume its results are reliable.

AI governance must be embedded into the technology itself. As AI agents become more autonomous and operate at greater speed and scale, relying solely on human oversight may not be sufficient. Firms need clearly defined permissions, preventative controls and mechanisms to identify and stop inappropriate actions. The level of control should reflect the risks associated with each application.

Human accountability remains central to responsible adoption. Organisations must be able to explain why they trust a system, demonstrate the checks applied to its outputs and identify who is responsible when something goes wrong. AI can support decision-making, but it does not remove the need for professional judgement or clear ownership of outcomes.

The right tool depends on the task and its potential impact. AI can be particularly valuable for improving productivity, scrutinising data and interpreting complex regulatory requirements. Applications with greater autonomy or significant financial or customer consequences require more rigorous testing and stronger safeguards. The objective should not be to deploy the most advanced technology available, but to choose the solution best suited to the problem.

Technology should strengthen expertise, not replace it. Making information and answers more accessible can support learning and collaboration across teams. However, employees must continue to develop the knowledge and judgement needed to challenge AI-generated outputs and recognise when results may be incomplete or incorrect. Effective adoption combines technological capability with human understanding.

Effective oversight starts with asking the right questions. Boards and senior leaders do not need to become technical specialists, but they must understand the potential impact of AI, the scenarios in which systems could fail and the safeguards in place. Clear accountability, credible contingency plans and informed challenge are essential to maintaining effective governance.

Looking ahead, legacy infrastructure and fragmented systems remain significant barriers to progress. Modern tools can help connect information and improve reporting processes, but sustained investment in underlying technology and data capabilities is still required. As lending, payments and other financial activities become faster and increasingly real-time, regulatory reporting and risk management will also need to become more responsive.

Ultimately, successful technology adoption is about combining innovation with control. By choosing the right tools, strengthening data foundations and embedding effective governance, financial institutions can turn efficiency gains into better decisions and stronger risk management. The goal is not simply to automate more, but to ensure that technology delivers reliable, measurable value while preserving the expertise and accountability on which the industry depends.

Panellists:

• Oliver Margetts, Chief Technology Officer, Suade (Moderator)
• Zachary Anderson, Chief Data & Analytics Officer, Global Banking & Payments, JP Morgan
• Jonathan Taylor, Head of Quantitative Analysis & Model Risk Management, PRA, Bank of England
• Nick Wilson, Liquidity Reporting Senior Manager, Lloyds

This summary captures key themes from the discussion. Individual contributions have not been attributed to participants, in accordance with the Chatham House Rule.

As financial institutions navigate an increasingly complex regulatory environment, adapting to evolving requirements across jurisdictions remains a significant challenge. The Living in a World of Constant Regulatory Change panel explored how firms can manage regulatory divergence, strengthen data governance and modernise reporting processes while balancing compliance obligations with operational efficiency and commercial priorities.

International alignment must account for local differences. Global regulatory standards provide a common foundation, but differences in legislation, market structures and domestic priorities mean that requirements are not always implemented consistently. Firms operating across multiple jurisdictions must understand these local nuances and ensure their reporting frameworks can accommodate different interpretations and obligations.

Strong data governance is fundamental to consistent reporting. Clear data definitions, standardised data dictionaries and traceable data lineage help ensure information can be interpreted accurately across jurisdictions and reporting requirements. As regulatory expectations evolve, firms need robust data foundations to maintain consistency, accuracy and confidence in their submissions.

Proportionality and simplicity must deliver practical benefits. Simplifying regulatory requirements can reduce unnecessary reporting burdens, but frameworks must reflect the size, complexity and risk profiles of individual firms. Similarly, more granular rules can improve risk sensitivity, yet introduce additional operational complexity. Effective regulation must strike a balance between meaningful oversight and manageable implementation.

Granular reporting increases the importance of data quality and accountability. As regulators request more detailed information, firms need stronger reconciliation processes to connect granular submissions with existing regulatory returns, investigate discrepancies and explain reported figures. Clear ownership, senior oversight and effective governance are essential to maintaining accuracy and accountability as reporting obligations expand.

Successful implementation depends on communication and collaboration. Translating complex regulatory requirements into practical business language is critical to ensuring teams understand what needs to change and why. Training and collaboration across regulatory, risk, technology and customer-facing functions can help embed new requirements effectively. Ongoing dialogue between firms and regulators is equally important, enabling unintended consequences to be identified and helping ensure policy remains workable in practice.

Automation can help firms manage growing reporting demands. Modernising legacy systems and automating manual submissions offers opportunities to reduce repetitive work, improve efficiency and free up resources for higher-value activities. However, firms must also maintain the flexibility and expertise needed to respond to changing requirements without compromising data quality or control.

Ultimately, managing constant regulatory change requires adaptability, forward planning and a strong data foundation. By investing in flexible reporting systems, clear accountability and effective collaboration, financial institutions can respond more effectively to evolving regulatory expectations across jurisdictions. The challenge is not simply to keep pace with new rules, but to implement them in a way that supports accurate reporting, proportionate compliance and sustainable business outcomes.

Panellists:

• Max Gerard, Solutions Consultant, Suade (Moderator)
• Ian Warren, Chief Financial Officer, iFast
• Tamiko Bayliss, Head of Banking Capital Policy, Bank of England
• Judy Zhu, Head of Regulatory Reporting; Bank of China
• Jina Kim, Head of Financial & Regulatory Reporting, Redwood Bank

This summary captures key themes from the discussion. Individual contributions have not been attributed to participants, in accordance with the Chatham House Rule.

As artificial intelligence becomes increasingly embedded in financial services, building trust in its use is essential. The Building Trust in AI panel explored how organisations can realise the benefits of AI while ensuring its deployment remains safe, responsible and reliable. The discussion highlighted the importance of strong governance, high-quality data and clear accountability in managing the risks associated with increasingly capable AI systems.

Strong governance is the foundation of trust. Organisations need clear accountability, effective oversight and robust controls to ensure AI is deployed responsibly. These safeguards should be integrated into existing risk management frameworks, taking into account potential challenges such as bias, data privacy, security and operational resilience.

Reliable AI depends on reliable data. The quality of AI-generated outputs is directly linked to the accuracy of the underlying data, the clarity of data lineage and the explainability of the processes involved. While AI can deliver significant efficiencies, speed must not come at the expense of accuracy, transparency or trust.

Controls must reflect the level of risk. Not all AI applications carry the same potential impact. Organisations should adopt a proportionate approach to governance, validation and monitoring, applying more rigorous safeguards where AI decisions could have significant business or customer consequences.

Trust requires continuous monitoring. As AI systems evolve and become more widely accessible, organisations must maintain visibility over how they are used and regularly assess emerging risks. Ongoing monitoring is essential to ensure controls remain effective and that AI continues to operate within appropriate boundaries.

Human accountability cannot be delegated to AI. Although AI can support decision-making and improve operational efficiency, organisations must retain responsibility for its outcomes. Decisions and outputs should remain open to scrutiny, challenge and explanation, with appropriate human oversight in place.

Ultimately, responsible AI adoption requires a balance between innovation and control. Financial institutions have opportunities to use AI to improve efficiency and customer outcomes, but realising this potential depends on understanding its limitations and maintaining appropriate safeguards. By prioritising strong governance, reliable data and human accountability, organisations can build the trust needed to adopt AI responsibly and sustainably. The Building Trust in AI panel explored how organisations can realise the benefits of AI while ensuring its deployment remains safe, responsible and reliable. The discussion highlighted the importance of strong governance, high-quality data and clear accountability in managing the risks associated with increasingly capable AI systems.

Strong governance is the foundation of trust. Organisations need clear accountability, effective oversight and robust controls to ensure AI is deployed responsibly. These safeguards should be integrated into existing risk management frameworks, taking into account potential challenges such as bias, data privacy, security and operational resilience.

Reliable AI depends on reliable data. The quality of AI-generated outputs is directly linked to the accuracy of the underlying data, the clarity of data lineage and the explainability of the processes involved. While AI can deliver significant efficiencies, speed must not come at the expense of accuracy, transparency or trust.

Controls must reflect the level of risk. Not all AI applications carry the same potential impact. Organisations should adopt a proportionate approach to governance, validation and monitoring, applying more rigorous safeguards where AI decisions could have significant business or customer consequences.

Trust requires continuous monitoring. As AI systems evolve and become more widely accessible, organisations must maintain visibility over how they are used and regularly assess emerging risks. Ongoing monitoring is essential to ensure controls remain effective and that AI continues to operate within appropriate boundaries.

Human accountability cannot be delegated to AI. Although AI can support decision-making and improve operational efficiency, organisations must retain responsibility for its outcomes. Decisions and outputs should remain open to scrutiny, challenge and explanation, with appropriate human oversight in place.

Ultimately, responsible AI adoption requires a balance between innovation and control. Financial institutions have opportunities to use AI to improve efficiency and customer outcomes, but realising this potential depends on understanding its limitations and maintaining appropriate safeguards. By prioritising strong governance, reliable data and human accountability, organisations can build the trust needed to adopt AI responsibly and sustainably.

Panellists:

• Murat Abur, Co-founder & CIO, Suade (Moderator)
• Gaetano Chionsini, Head of Statistics, European Banking Authority
• Vicki Jordan, Policy Manager - AI, Remuneration, and Policy Profession, Financial Conduct Authority
• Nick Talbot, Head of Climate & Nature Risk; Head of AI Risk Framework Programme at NatWest

This summary captures key themes from the discussion. Individual contributions have not been attributed to participants, in accordance with the Chatham House Rule.

400+ Senior Leaders | 25+ High Profile Speakers | Networking

We’ve reserved a place for you at this year’s RegTech Forum. We’d be delighted to have you join us at Guildhall on 6 October.

This invitation gives you access to our 2026 RegTech Forum, bringing together senior leaders from across banking, regulation and technology.

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About

A senior forum bringing together leaders from banking, regulation and technology to explore how regulatory reporting is evolving in practice, and what it takes to build scalable, data-driven and resilient reporting frameworks in an era of rapid change.

Key themes

This year’s forum will explore how regulatory reporting is evolving in practice, as banks respond to rapid advances in AI, increasing data complexity, and continued regulatory divergence across jurisdictions. Discussions will focus on how firms are operationalising change across data, technology, controls and capital frameworks.

Agenda

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Tuesday 6th October | 10am - 12pm | Guildhall, London

We welcome our clients to join the Suade team for an morning of discussion, updates, and conversation with peers across the community.

During the forum, the Suade team presented a round-up of what has happened so far this year, what we have been working on, and the product updates currently in the pipeline.

Speakers:

Kira Snow, Senior Implementation Specialist, Suade

Florent Audigier, Head of Product, Suade