AI Model Risk Management in Financial Reconciliation: Challenges & Progress

About this Event

Join us for this essential 60-minute webinar panel event, "AI Model Risk Management in Financial Reconciliation: Challenges & Progress" designed for financial services leaders who oversee operational excellence and governance at reconciliation CoEs, Global Banks, and Business Process Outsourcing firms.

The adoption of AI in financial reconciliation is now mainstream, but the conversation has moved from "if'" to "how safely and compliantly".

As matching engines become increasingly reliant on machine learning, they introduce new layers of complexity - from model drift and explainability challenges to new regulatory scrutiny (e.g., SR 11-7, EU AI Act).

This live webinar session will provide a strategic deep dive into establishing robust Model Risk Management (MRM) and governance frameworks tailored specifically for high-volume financial matching environments.

We will explore how BPOs can confidently offer AI-driven services, and how financial institutions can conduct the necessary due diligence to ensure vendor and internal AI systems are secure, compliant, and deliver provable accuracy.

If your mandate is to scale AI while satisfying internal audit and regulatory requirements, this is a must-attend event.

All attendees will receive exclusive, early access to the upcoming Operartis white paper on AI Model Risk Management in Reconciliation - your essential guide to building an audit-ready AI strategy.

Points We’ll Cover:

We'll guide the discussion through the critical pillars of AI model risk for reconciliation operations, providing practical, actionable frameworks:

Defining and Mitigating Core Risks:

➡️ Exploring the model risk aspects of both ai-based and traditional rule-based matching systems (e.g., false positives/negatives, model drift, and data quality dependencies).

➡️ Strategies for accurately measuring and maintaining model stability and accuracy as data volumes and patterns shift over time.

Data Lineage and Auditability:

➡️ Creating audit trails and documentation robust enough to satisfy both internal risk teams and external regulators.

Validation, Monitoring & Control:

➡️ Outlining standards for continuous performance monitoring, validation, and ongoing recalibration of AI models in production.

➡️ Essential Key Performance Indicators (KPIs) for model health, including precision/recall, confidence scores, and model decay metrics.

Human-in-the-Loop Oversight:

➡️ Highlighting successful frameworks for combining AI recommendations with human exception handling to mitigate model errors and maintain explainability and control.

➡️ Defining the roles and responsibilities of the Human-in-the-Loop (HITL) to ensure model accountability.

Regulatory Compliance & Accountability:

➡️ Addressing how emerging AI risk guidelines (e.g., SR 11-7, OCC, EU AI Act) apply directly to to reconciliation matchers and the necessary governance policies and sign-off processes.

➡️ Leveraging technology to automate compliance reporting and reduce the manual burden of Model Risk documentation.

Who is this for?

This webinar is critical for senior leaders who own the intersection of technology, compliance, and operations, including:

• Heads of Reconciliation/R2R CoE, Operations, and Transformation at Financial Institutions.
• Chief Risk Officers (CROs) and Heads of Model Risk Management.
• Senior VPs and Managing Directors at BPO firms responsible for Financial Services delivery and governance.
• Internal Audit and Compliance professionals overseeing AI strategy.

Who is Speaking?

Tracey Lall (Founder, Operartis):

Tracey brings a cutting-edge perspective to our panel as a leader in enterprise automation powered by artificial intelligence and machine learning - specifically, how to architect an AI system that is inherently compliant and low-risk from the ground up.

As the Founder of Operartis and producer of Matchimus, an AI-based matching engine, Tracey’s expertise is centered on pushing straight-through processing to new levels while ensuring governance is non-negotiable.

Her company's mission is to revolutionize how organizations operate by streamlining tedious processes, allowing businesses to redirect their focus to high-value tasks. As the producer of Matchimus, a best-in-class AI-based add-on matching engine, Operartis is dedicated to boosting match rates within existing reconciliation systems.

Tracey will move beyond general principles to share actionable insights on how solutions like Matchimus are designed for the very model risk management frameworks the audience is implementing. She will explain how the right technology provides essential features like explainability, continuous performance monitoring, and robust audit trails required to meet regulatory and internal audit standards.

With a team comprising banking IT veterans, PhD data scientists, and enterprise architects, Tracey embodies the ideal combination of academic rigor, system performance know-how, and grounded operational understanding essential for successful AI deployment in complex financial environments.

Tracey will connect the dots between AI innovation and demonstrable ROI. She will share real-world deployment case studies that illustrate how a governance-focused approach to AI not only boosts match rates and operational efficiency but also transforms profitability and performance, ensuring clients achieve optimal operational scale through compliant, audit-ready AI technology without trading efficiency for risk.

Marc McCarthy (Managing Director, ProConsultIQ):

Marc McCarthy serves as the voice of operational integrity and regulatory assurance on this panel. With over 25 years of experience leading reconciliation and data programs at global banks, he provides a holistic understanding of what it takes to transform fragmented operations into unified, transparent, and scalable platforms.

His work with ProConsult IQ focuses on delivering solutions that specifically embed control and unlock efficiency - the exact twin objectives of the modern reconciliation COE.

Marc's history advising institutions like the Bank of England and top-tier asset managers gives him unparalleled credibility to speak authoritatively on how AI Model Risk Management satisfies stringent regulatory demands.

He will share insights on data integrity and real-time reporting, explaining how adopting a transparent, auditable AI solution is the only way for BPOs and banks to optimize their reconciliation strategies for accuracy, resilience, and scale while meeting evolving compliance mandates.

Manish Upadhyay (Sr. VP & Business Head - BFSI & Sports Tech Europe, Tech Mahindra)

Manish joins us to provide the crucial commercial and strategic perspective from the viewpoint of a major global BPO partner and brings over 20 years of global leadership and strategy in the BFSI (Banking, Financial Services, and Insurance) industry.

Leading a large sales organization focused on innovative solutions for global service providers, Manish offers a critical view on the client-side demand for governance and how managing AI Model Risk is no longer a back-office compliance issue but a front-end sales enabler.

His expertise bridges the gap between technical risk management and commercial success, explaining how a platform architected for governance is essential for delivering value-proof, outcome-based reconciliation services.

Prashant Shegaonkar (Director, Global Head - Professional Services, FIS)

Prashant is a visionary executive whose two decades of global experience are essential for leaders focused on operational agility and governance.

As an authority who has successfully built and scaled high-performing global Centers of Excellence (CoEs) for top-tier investment banks, he offers the executive blueprint for achieving compliant transformation at scale.

Prashant's expertise is grounded in delivering measurable outcomes. He has led the modernization of reconciliation architecture for over 300 global clients, resulting in tangible results such as a 30% reduction in time-to-market and a 20% decrease in Total Cost of Ownership (TCO). He understands that Model Risk Management isn't just a compliance overhead - it's a necessary component of Operational Agility and Data-Driven Decision-Making.

Prashant will share practical advice on implementing AI transformation within a heavily regulated environment, ensuring your organization sees that adopting an audit-ready solution is the clear path to achieving both strategic growth and sustained profitability.

Kavita Dwivedi (Sr.Business Consultant - Model Risk Management, Tata Consultancy Services)

Kavita brings the indispensable perspective of a practicing Data Scientist with over 20 years of experience in the Banking and Financial Services sector. Her extensive work in complex, highly regulated domains like Fraud Analytics, AML, BASEL, and CCAR means she views AI not just as an efficiency tool, but as a system requiring rigorous Model Risk Governance.

As a Senior Business Consultant focusing on Model Risk Management in Fraud and Anti-Money Laundering, Kavita handles teams managing complex AI/ML models for global banking clients.

She is perfectly positioned to discuss how the best practices for controlling high-stakes financial crime models - such as threshold fine-tuning, model validation strategy, and regulatory compliance - are directly applicable to managing AI in reconciliation.

You will gain practical, frontline insights on the technical and compliance burden of AI implementation, ensuring your organization understands how to move from model deployment to an audit-ready, governable solution. Her presence assures Risk and Compliance leaders that the discussion is anchored in real-world regulatory requirements.

When and Where it?

The live webinar will kick off at 09:30 EST(14:30 BST / 19:00 IST) and conclude by 10.30 EST (15:30 BST / 20:00 IST). This is an online event, accessible from anywhere.

What’s the next step?

Secure your place by registering and we'll keep you updated as the event approaches.