Author: Simetrik editorial team

Acquirers play a pivotal role in the modern financial ecosystem, facilitating card payments and disbursing the right amount to merchants with every purchase. But each transaction is a potential point of failure that’s subject to risk from errors, disputes, and revenue leakage.

To handle high transaction volumes and maintain your reputation in a fragmented payments market, you must reliably automate reconciliation and reporting—starting with activity related to the card networks that make up a major portion of your transactions.

Simetrik’s preconfigured Visa and Mastercard solutions make this possible without exorbitant costs or a heavy engineering lift. It’s designed to help you set up best-practice reconciliation workflows with no code, guided by an intelligent setup assistant and a dedicated onboarding team, and maintain full visibility into the inner workings of your rulesets and logic as they evolve.

We’ve connected nuanced capabilities and financial controls to enable six key use cases, from authorization to dispute management, in a way that’s easy to deploy and adopt.

Why should acquirers automate reconciliation?

Monitoring and reconciling card network transactions is critical to your success as an acquirer. Visa and Mastercard not only make up a large portion of total transactions, they also each have their own set of requirements for acquirers, including specific audit frameworks and scheme fees that must be tracked meticulously.

Simetrik automates reconciliation down to the transaction level, matching records across internal and external systems and generating reports for your merchants, auditors, and other stakeholders that are already aligned with Visa and Mastercard’s requirements. Instead of managing spreadsheets and scrambling to organize data for network reports like the QMR (Mastercard Quarterly Member Report) and GOC (Visa Global Operating Certificate), you can focus on quickly remediating errors and disputes.

Once data is reconciled and verified, it can be used by your team and your merchants to make better operational decisions, from forecasting to fee strategies.

5 reasons to automate Visa and Mastercard reconciliation:

• Improved cash-flow visibility
• Accurate forecasting
• Efficient fee management
• Faster dispute resolution
• Stronger risk management

6 key functionalities you can enable on Simetrik

Simetrik connects acquirer-supplied scheme files, bank statements, and records from internal systems like your ERP, automating six key reconciliation use cases for Visa and Mastercard transactions:

• Funding – Validate programmed versus received bank receipts, investigating partials or delays to ensure compliance and timely execution.
• Authorization – Ensure control and reduce fraud by reconciling authorized requests and responses with network data and matching clearing files to issuer records.
• Clearing – Validate scheme fees, interchange fees, and network adjustments against acquirer records to prevent overbilling and missed charges.
• Disputes – Confirm funds debited from issuers, reconcile pre-arbitration and arbitration cases, and help merchants manage evidence.
• Settlement – Calculate daily net settlement and validate receipts against bank statements for optimal liquidity management.
• Agenda – Split domestic and international agendas, with or without deferment, validating expected financial movements to prevent loss from delayed or missing settlements.

Minimize risk with fast, guided deployment

Simetrik leverages a dedicated onboarding team alongside AI-enhanced setup flows to help you quickly improve reconciliation and reporting. The platform eliminates careless errors while giving users control over the final output, complete with built-in governance and guardrails that maintain the integrity of your data.

With Simetrik, you don’t have to worry about managing a tough implementation alone. Our Visa and Mastercard solutions can be delivered in weeks, not months, with help from a dedicated onboarding team and an intelligent, guided setup assistant.

Simetirk customers can also choose from prebuilt, customizable dashboards that highlight the metrics acquirers care about the most—out-of-the-box KPIs with drill-down capability and AI-driven recommendations. 

Get started with a personalized demo

Want to see Simetrik’s card network solutions in action with your own data? Get in touch to request a demo and we’ll show you how to scale reconciliation with modular, ready-made workflows.

Learn more about our Visa and Mastercard solutions.

When you think about resilient finance operations, what comes to mind? 

Accurate numbers, limited risk exposure, data-driven decisions, and well-controlled costs—all of these are made possible through the process of reconciliation.

Today, however, the reconciliation process is still plagued by outdated technology and manual number-crunching. It’s tedious, rife with errors (as seen in recent public cases where mistakes have cost companies millions), and unscalable in a market where complexity seems to grow by the minute. 

It’s time to adapt. In this guide, we’ll take a look at a model for reconciliation maturity that will guide you toward fully automated, AI-enabled reconciliation at every level. From siloed, costly operations to expertly orchestrated workflows with clear ROI, each advancement reduces cost and drives efficiency across the organization.

5 factors making reconciliation painful:

1. Massive transaction volumes involving many fintech, payments, and banking partners
2. Highly complex, nonstandardized remittance data in varied formats
3. Stringent, inconsistent regulations across many regions and industries
4. A fast-growing market that regularly requires new partnerships, integrations, and workflows 
5. The en masse adoption of AI that requires real-time, trusted data to operate

Why reconciliation maturity matters now

Until recently, the standard response to reconciliation complexity was to add headcount, boost engineering spend, or accept a baseline level of revenue leakage, audit fees, and costly errors. 

But the modern financial ecosystem has reached an inflection point that makes this path impossible to stay on. The last decade has seen sweeping changes in global regulations, an explosion of payment companies and offerings, open banking standards, and an AI boom that reset the bar for real-time data access and deep interoperability.

Legacy reconciliation solutions can’t meet the demands of today’s market, always one step behind and far too unreliable for the speed and volume of modern money movement. and Miss out now, and you’ll face increasingly prohibitive costs as you try to keep up with competitors who’ve adopted  scalable, AI-ready reconciliation platforms.

The great enabler: the AI reconciliation platform

To reach full reconciliation maturity, companies need technology that can handle enterprise complexity. While it’s possible to make it past the first stage of reconciliation maturity using point solutions or home-grown scripts, you won’t get much further without a unified platform for all of your reconciliation data, controls, and workflows.

AI reconciliation platforms help you integrate internal and external transaction data sources, connect internal systems like your ERP or core banking system, and deploy sophisticated governance and automation in a way that doesn’t plunge you into technical debt as regulations and business needs change.

The best reconciliation platforms do more than just reconcile multi-way transactions. They incorporate agentic AI and intelligent, adaptive rulesets to reconcile data at three distinct levels:

• Transaction level – Matching individual transactions to create a reliable source of truth for all downstream processes, detecting anomalies and discrepancies in real time.
• Financial level – Using reconciled data to manage cash flow and control costs, supporting strategic decisions, and reporting accurately to internal and external auditors.
• Accounting level – Aligning transaction and financial data with journal entries to ensure compliant, accurate reporting and accelerate close cycles.

In the next section, we’ll show you how adopting an AI reconciliation platform is essential to increasing the maturity of your finance operations. There are many paths to success—keep reading to explore ways to advance that fit your unique use case, resources, and goals.

What can an AI reconciliation platform do?

• Process massive transaction volumes with low latency at T+1 speed 
• Standardize and match multi-platform, highly varied transaction data
• Meet stringent, inconsistent regulations across many regions and industries 
• Keep TCO manageable with no-code, scalable deployment and iteration
• Support constant change and scale with zero downtime

An actionable model for reconciliation maturity

Fully mature, AI-optimized reconciliation drives value beyond just reporting the numbers. It gives you trusted, real-time financial data to use in any downstream application you can dream up. 

The Simetrik reconciliation maturity model consists of five stages, starting with completely manual finance operations and ending with transformative, continuously improving reconciliation automation. From instant customer refunds and nuanced loyalty programs to advanced, predictive FP&A modeling, getting to Stage 5 will put you at a huge competitive advantage.

Stage 1: Slow & siloed 

At the first stage, reconciliation is almost entirely manual. Minimal data integration, no scalability, and a lack of confidence in the numbers hurts the business.

• Data management: Spreadsheets and macros are the finance team’s primary tools, and siloed transaction data must be exported, validated, and entered correctly into backend systems. 
• Development: Any attempt at integration or automation is reliant on engineering, so progress is slow and costly. There’s no path to leveraging AI or using transaction data in decisioning models. 
• Exception handling:  Finance teams manually check for discrepancies and fraud to a limited degree of success. When found, outreach and remediation can take weeks.
• Financial oversight: Little insight into current operational balances makes decision-making difficult. Transaction data often doesn’t match bank statements, bank balances, revenue forecasts, and other indicators of financial health.
• Accounting integrity: Transactional data is not aligned with operational balances or ledgers, slowing the financial close and often resulting in reporting errors. 
• Risk: Risk is at a critical level, with many unexpected, unexplained losses and siloed internal knowledge. If a key employee leaves, they take the understanding of reconciliation logic with them.
• Compliance: Without audit trails, data must be compiled manually. Audits are costly and drawn out, and compliance gaps can lead to fees and reputational harm.

Stage 2: Limited automation

Benefits start to materialize at stage two, but reconciliation still isn’t scalable. With many data sources not yet integrated, AI adoption is not yet possible.

• Data management: Some integrations are in place, but transaction data remains fragmented.  Manual data exports and spreadsheets are still common. 
• Development: Automations are homegrown or piecemeal and rely on constantly changing logic and data sources. Engineering costs to add new integrations are high.
• Exception handling: Anomaly detection and transaction matching is automated for some sources, lightening the burden of exception management. Remediation is still entirely manual.
• Financial oversight: Increased visibility into transaction data helps with financial modeling and performance tracking, but isn’t enough to inform major decisions or drive AI innovation. 
• Accounting integrity: Transactional data is still not aligned with general and sub-ledgers. Close cycles are long, and reporting is error-prone.  
• Risk: Risk is still high, but the number of unexplainable losses starts to drop. Siloed internal knowledge is still a problem, with many black boxes across teams and information held by a select few team members.
• Compliance: Rev rec and reporting for standards like ASC 606 and IFRS 15 is manual and lacks complete audit trails. Internal audits can take months due to visibility gaps.

Stage 3: Full transactional coverage 

At this stage, transaction-level reconciliation is fully automated, scalable, and prepared for financial reporting and downstream innovation. Accounting-level reconciliation remains manual.  

• Data management: All transaction records are integrated, standardized, and automatically reconciled. Finance teams have real-time visibility into granular transaction details and discrepancies.
• Development: No-code tools and AI agents accelerate time to value and alleviate reliance on engineering as new workflows are needed. Anyone with permission can adapt the rulesets and business logic that power automated reconciliation and reporting. 
• Exception handling: With the day-to-day reconciliation fully automated, team members can focus on exception handling. As discrepancies, chargebacks, disputes, and potential fraud are detected in real-time transaction streams, alerts tell the FinOps team it’s time for remediation.  
•  Financial oversight: Transaction data is occasionally reconciled against operational balances in the ERP, but records quickly outdated. Finance operations and accounting teams must manually compare ERP data with transactions for a true picture of the company’s finances. 
• Accounting integrity: Accounting-level reconciliation is still manual. Transaction data doesn’t always match the GL and subledgers. The financial close takes days longer than it should due to manual data collection and reporting.
• Risk: Risk is greatly reduced due to transactional visibility, with losses easier to explain and quickly resolve. Knowledge of transactional reconciliation logic is accessible across the company—key employees can leave with zero disruption to the business.
• Compliance: Detailed transaction-level audit logs exist, but the audit process is still slowed by outdated reporting mechanisms. Documents are created manually or using scripts, without being connected to updated source data.

Stage 4: Complete accounting control 

Transaction data is automatically reconciled against accounting balances. Accounting teams have dynamic, dedicated dashboards for the metrics they care about. Financial oversight is strong, but room for innovation remains.

• Data management: ERPs and other internal accounting systems are integrated alongside transaction data sources, all on a single reconciliation platform. Accounting teams can see always-updated, reconciled journal entries in the GL and sub-ledgers.
• Development: Users can deploy no-code workflows and update accounting rulesets to correctly transform data and sync it with the ERP. AI agents simplify the process of automation without diminishing control. 
• Exception handling: The accounting team receives real-time alerts for discrepancies between transactional data and accounting balances. Exceptions are caught and remediated before the end of the close period.
• Financial oversight: Data is synced at least daily with the ERP and prepped for downstream reporting and AI analysis. Finance leaders can make fast decisions without digging into transaction details. 
• Accounting integrity: Accounting leadership can see calculated balances, auto-reconciled journal entries, and progress against the close at a glance. The financial close is reduced by an average of five days. 
• Risk: Operational loss and revenue leakage happens rarely, with complete explainability. Finance operations, accounting, product teams, and leadership all have visibility into reconciliation logic without needing to understand code. 
• Compliance: Transaction- and accounting-level audit logs accelerate compliance efforts and minimize cost. Reporting is automatically tailored to relevant regulations and internal compliance requirements.

Stage 5: End-to-end AI automation

The final stage is an ongoing journey of iteration, scale, and increased ROI. New use cases are continuously deployed with zero code. AI agents learn and suggest improvements as the business and ecosystem evolves.

• Data management: Every data source, internal and external system, and regulatory requirement is unified on an AI reconciliation platform. Adding a payment partner, adapting to new laws, and expanding into new markets is painless.  
• Development: Scalable, no-code automation makes adding a payment partner, adapting to new laws, and expanding into new markets painless. Massive changes to the financial ecosystem no longer pose a threat.
• Exception handling: Agentic AI powers every step of risk detection and exception management. Users manage sophisticated automations that quickly remediate issues like chargebacks, disputes, and refunds.
• Financial oversight: AI-ready, reconciled data powers a multitude of innovative financial modeling, forecasting, and performance tracking. New use cases are easy to implement as requirements change.
• Accounting integrity: The books always align with transactional data. AI agents drive a fully automated and auditable financial close, with reporting and documentation dynamically aligned to evolving IFRS standards and business-specific workflows. 
• Risk: Risk due to reconciliation errors is eliminated, with advanced predictive models and no-code automation driving complete transparency across the org. 
• Compliance: AI agents and intelligent logic powers adaptive, accurate reporting across many internal and external compliance use cases.

What’s next on the path to maturity?

Now that we’ve laid out a vision for full reconciliation maturity, it’s time to get to work. Plot yourself on the model, outline next steps, and prioritize the use cases that are most likely to move you to the next stage. 

At Simetrik, we’ve helped finance operations teams across top financial services, retailers, and marketplaces move from costly manual transaction matching and reporting to AI-enabled, fully automated reconciliation. 

Get in touch with our team to request a demo.

In September 2024, the FDIC proposed a rule to improve recordkeeping for custodial (also called FBO, or “for benefit of”) accounts, where fintechs and non-bank entities pool customer funds in FDIC-insured banks. The goal is to ensure that banks can accurately identify individual fund owners and their balances, even when intermediaries track transactions.

The rule, aimed at enhancing depositor protection and increasing public confidence in insured deposits, could become law any day. When it happens, unprepared banks will have to scramble to put new technology and workflows in place to maintain compliance. 

The catalyst: the 2024 Synapse bankruptcy 

The proposed FBO rule is largely a response to the 2024 bankruptcy of Synapse Financial Technologies, a middleware provider that allowed businesses to integrate banking services into their own applications. 

After a subsidiary of Synapse began offering cash management accounts to their partners’ end users, the company filed for bankruptcy protection. One of their partner banks, Evolve, froze access to Synapse accounts to the tune of over $200 million, stating lack of access to an essential system of record. 

The result was chaotic. End customers couldn’t access their funds, but to release them the FDIC needed transaction and ledger records from Synapse. Between access issues and inadequate recordkeeping, there was no way to recoup losses using FDIC insurance. With $96 million missing and over 100,000 customers affected, the saga still isn’t fully resolved.

What are custodial, or FBO, accounts?

Custodial accounts are bank accounts held by one party (the “custodian”) on behalf of another (the “beneficial owner”). In fintech-bank partnerships, these accounts typically hold pooled customer funds under the fintech’s name or a third party’s, with individual user balances tracked outside of the core banking system by the third party.

This arrangement creates a visibility gap for the bank. It doesn’t inherently know who the end users are or how much each is owed, making things complicated for FDIC insurance determinations when something goes awry. 

Why is custodial account recordkeeping so complicated? 

Over the past decade, a huge influx of fintech companies have entered the market. These entities aren’t allowed to provide the full spectrum of financial products, so they rely on partners to enable them. 

In the case of custodial accounts, these partners are banks (referred to in the rule as Insured Depository Institutions, or IDIs) who already are licensed and insured to provide accounts insured by the FDIC. 

These partnerships create a complex ecosystem of intermediaries and fintech partners that each enable their own customer base to open accounts with the custodian bank. For most banks, it’s nearly impossible to keep track of who manages whose accounts, transaction details, and daily balances across all of the different systems.

For example, while individual customers may initiate millions of transactions each day on the fintech side, the details aren’t necessarily preserved by various members in the ecosystem. Some will initiate bulk movements that aggregate individual transactions into a single amount, making them hard to disambiguate later. 

Any company growth, new partnerships, or regulatory changes just increase this complexity, risking the loss of visibility and traceability of critical financial movements. Catastrophic events like the Synapse bankruptcy don’t happen every month—but losing millions to leakage, inefficient operations, and audit fees is far more common. 

What are the FDIC’s proposed changes to FBO accounts?

The FDIC’s proposed rule, Part 375, outlines new requirements for maintaining and reconciling records for FBO accounts. IDIs holding custodial deposit accounts with transactional features would be required to:

• Meet new recordkeeping requirements, including maintaining records of custodial account details like the beneficiary, owner, and the balance attributed to each end user in a standardized format.
• Be subject to an annual validation by an independent person or entity to assess and verify that third parties are maintaining accurate and complete records consistent with the proposal’s requirements.
• Implement internal controls to ensure that balances of custodial deposit accounts are accurate and reconciled daily.
• Complete an annual certification of compliance and an annual report of compliance.

Banks would be allowed to partner with a trusted third-party to meet these requirements, as long as certain conditions are satisfied. They must have direct, continuous, and unrestricted access to the records maintained by the third party, as well as have continuity plans and internal controls in place.

How do the FDIC’s proposed changes affect PSPs and fintechs?

For banks to meet these requirements, their fintech and intermediary partners must be able to provide daily transaction-level data on money moving to and from custodial accounts. These individual records must be reconciled against FBO balances, taking into account complications like rolling reserves and delayed settlements. 

To facilitate this, PSPs and other fintechs should invest in scalable, real-time transaction tracking and reconciliation technology that can sync data across all systems at least once per day.

How Simetrik helps you prepare for the new FDIC rule

Simetrik is an enterprise reconciliation platform that helps banks maintain and govern this improved method of recordkeeping that will soon be required by the FDIC. 

Here’s how it works:

• Banks can integrate data from all of their fintech and middleware providers in one place, standardizing it to meet the specific requirements outlined in the proposed rule.
• Transactions are monitored and reconciled daily, catching discrepancies and potential fraud instantly so they can be handled before reporting to the FDIC.
• Bulk money in/money out records are automatically disambiguated to keep end user balances accurate.
• Simetrik dashboards inform stakeholders of individual beneficiary activity and balances, total daily net movement, daily cumulative balances, and more.
• Simetrik users can search and explore a subset of custodial accounts, like a specific partner.
• Reporting is automatically prepared for appropriate third-party auditors and shared in the correct format. 

A similar process applies to fintech and middleware providers who choose to follow suit by adopting Simetrik. Transaction data from their platforms is monitored and reconciled daily with bank balances. This reconciled data is always accurate, searchable, and ready to use in customer-facing products or to meet additional reporting requirements. 

Scaling with no code automation

Unlike legacy or homegrown solutions you may have used in the past, Simetrik doesn’t require expensive integrations or hours of engineering work to set up each partner. Unify your custodial account transaction data and configure advanced reconciliation logic faster with flexible, no-code building blocks—so you’ll be ready when the proposed rule becomes enacted law.

Don’t get caught unprepared

The FDIC hasn’t yet announced when this rule will go into effect, but it may happen soon. While you still have time, adopt a unified reconciliation platform that will make the whole process painless and successful. 

To learn more about Simetrik, request a demo here.