It’s time for banks to get their reconciliations house in order

Banks spend significant amounts of time and money on reconciliations to ensure their trading systems, books and records align with their market cash and security positions.

But despite the obvious benefits of overhauling reconciliations—which today is a largely manual, inefficient process—financial institutions have been reticent to do so. Many believe the potential cost of supporting reconciliations as an operational and technology process is too high.

A modular approach to reconciliations helps banks manage those concerns. By utilizing best practices that include front-to-back planning, automation and risk management, they can reap the benefits of greater efficiency and lower total cost of ownership.

Why the reconciliations process lags

Several factors have slowed financial institutions’ efforts to get their reconciliations house in order. Data quality is often poor. Legacy systems are fragmented by business or geography. Most banks track reconciliations through spreadsheets that make processes laborious and error prone. Risk management and enterprise oversight are also manually intensive.

Now, however, new regulatory requirements mean financial institutions are supporting more reconciliations than ever. For many global FIs, the answer to the increased complexity is more spreadsheets. Yet amid increasing regulatory scrutiny, FIs will soon need to demonstrate control and compliance on a real-time basis, which makes reliance on legacy processes and spreadsheets unsustainable.

Another critical factor is that many banks view reconciliations automation as an IT project instead of a top-down, strategic project. By carefully designing and managing all the components in the reconciliations process, however, banks can not only achieve their objectives but also avoid costly project overruns.

While choosing the platform is as key for reconciliations as it is for trade expense, it’s just one component in building an optimal reconciliations solution that delivers TCO reductions and timely ROI. Also critical is demonstrating data integrity, completeness and control during the parallel efforts of implementation and decommissioning.

For example, we partnered with a global bank that had long struggled with multiple challenges to overhauling its reconciliations process. It was unsure how to manage the upfront investment and establish the business case, as well as develop a plan to keep its systems running in parallel. We built a five-year plan that will enable the bank to execute on its strategy to centralize and standardize its target operating model (TOM) while meeting its cost reduction goals and aging profile improvements.

Upfront planning also helps ensure banks reap the underlying benefits: After we worked with another global investment bank to overhaul its intersystem reconciliation process and control standards, the bank optimized operations by 60% and improved the age profile by 70%.

Five best practices for modernizing reconciliation

Through our work with global FIs, we’ve identified five best practices for streamlining the reconciliations process. The best practices include guidance for a tailored, modular approach that suits the bank’s business, priorities and IT architecture.

1. Plan a front-to-back data strategy. To optimize the reconciliations matching process, establish a data transformation layer that normalizes and enriches the thousands of feeds and data attributes. Be sure to allocate adequate budget and development resources for the data quality issues that will inevitably arise and require addressing from upstream business areas. Otherwise, operational inefficiencies will result. Increasingly, banks are looking to cloud data migration strategies in the longer-term plans.
2. Achieve design and stakeholder agreement. One of the most critical building blocks is building consensus on a standardized, front-to-back target operating model across operations and technology.
3. Employ intelligent automation. By applying intelligent process automation (IPA) to manual processes throughout the lifecycle, banks can drive higher match rates and reduce exceptions. Automated orchestration of the exception management workflow is another driver of operational efficiency and timely resolution.
4. Implement real-time risk management. Deploying a reconciliations dashboard and reporting tools can help transform a firm’s aging profile and streamline regulatory compliance, reducing the risk of operational losses and overhead. By performing data analytics on the root cause of breaks at a granular level, FIs can fix issues at the source or create automated resolution suggestions.
5. Create a delivery plan to implement the target operating model on time. This step is as important as meeting cost reduction targets and lowering upfront investment. Given the investment and effort involved with automating reconciliations, financial institutions want a delivery plan that provides the long-term solution they’re looking for. That is, they only want to fix the reconciliations process once.
   
   The most successful delivery plans adopt a factory-based model—automated and flexible—to support reconciliations and requirements going forward. A realistic delivery plan specifies critical details such as reducing parallel runtimes and decommissioning legacy systems, as well as plans for automation, process and reporting.

What’s clear is the days of spreadsheet reconciliation are numbered. Regulations will continue to create new requirements for banks, and volumes will continue to rise. With a standardized digital model for reconciliations, banks can achieve the TCO reduction and control they’re looking for.