Trade expense is one of the toughest topics in banking. These transaction-related fees cost banks billions of dollars every year. Yet most banks lack transparency into the drivers of those costs — and therein lies the problem. With limited insight into what they’re spending, banks struggle to make informed business decisions or develop a focused strategy to optimize the spend.
The combination of digital infrastructure, data lineage and analytics provides a path forward. By breaking the complexities of trade expense into initiatives that tackle small, manageable pieces, banks can begin to digitize data and automate the calculations and reconciliations.
In so doing, they also gain granular data to help them better understand their business. Data analytics and optimization across all of trade expense is now a realistic aspiration.
A big problem keeps getting bigger
Every day, banks generate millions of post-trade expenses associated with executing transactions. The related costs fall into dozens of categories, from brokerage and exchange fees, to clearing, settlement and regulatory fees. Most banks manage the monthly invoice process and bilateral rate agreements using information stored in PDFs or spreadsheets.
This approach offers little opportunity to analyze data at a macro level or effectively calculate expense at a trade level to facilitate more granular micro-level analysis for different products.
Without full visibility into the costs associated with a particular product or client, banks struggle to make informed decisions. Because they lack clear counterparty and consistent pricing, there’s limited opportunity to optimize their spend through renegotiation or to redirect flow based on liquidity and benefit from discounting.
For a trade expense solution to provide value for senior management, it has to occur at the corporate level and run across all products. Yet keeping up with regulatory changes such as European Market Infrastructure Regulation (EMIR) and Markets in Financial Instruments Directive II (MiFID II) has taken its toll on banks’ discretionary funds, absorbing much of the capital they could have used for large digital initiatives.
Learn to walk before you run
In virtual roundtables and client discussions over the last 12 months, chief operating officers and operations heads have been candid about their need to overhaul trade expense. They’ve shared frustrations such as the lack of agreement on the definition of trade expenses. Which fees does it encompass? Is market connectivity included?
Most COOs admit that their banks have only a rough estimate of the impact of trade expense on the business, and without one, they’re unable to write a business case to outline the ROI for fixing the trade expense process.
Where banks struggle to create the short-term business case, they may need to think about an initial proof of value. Instead of first tackling brokerage fees, for instance —which is tempting because these costs can be in the hundreds of millions a year — they might be better off digitizing first to gain transparency into some of the many smaller fee categories.
The fact is, while brokerage fees represent the greatest opportunity for savings, there are many other fee types (such as custody, tri-party and funding fees) that are less complex to address. By starting with a front-to-back solution — from digital ingestion of invoices through to automated calculation, reconciliation and allocation — in one of these more focused fee areas, banks can learn to walk before they run.
By taking this approach, banks can discover and fix potential problems, such as underlying data quality issues, that will be helpful to them when they take on brokerage fees. Equally important, they’ll gain insight into factors that drive their costs and be better able to demonstrate the business value of tackling trade expense.
What to expect
Starting with one of these smaller fee categories can provide the quick wins as well as the transparency and granularity that help propel banks forward in remaking trade expense. Here are a few initial considerations:
- Preliminary data work is essential. Before a bank can renovate and optimize, there is work to be done. For instance, counterparty referential data is usually inconsistently stored across products and entities, and rate agreements relating to vendors are typically not centrally stored or are out of date. The data attributes required to support calculations are also often not passed through from front-office systems.
While much of this can be fixed at the outset, it’s important to take a pragmatic approach to rationalizing the data to ensure timely delivery.
- Data transparency is key. Centralizing data is only one aspect of remaking trade expense. Equally important is the ability to create clear and transparent visualization of data at both a macro and micro level. By establishing an efficient process to manage trade expense and invoices, combined with data analytics, banks can gain the transparency needed to spot optimization opportunities.
One obstacle is that the data attributes required to support an efficient process are often stored in front-office systems. As trade data flows through a bank’s architecture, it’s not uncommon for data to be lost. By implementing data lineage from the front of your organization to the back, you will be better positioned to support invoice management, data analytics and reporting.
- Prepare your organization to collaborate. Banks traditionally take a go-it-alone approach to IT. While we haven’t seen a lot of industry collaboration, most banks share similar challenges with data, transparency, analytics and optimization. From client conversations, interviews with financial leaders and participation in trade expense forums, we believe the industry has a real opportunity to bring together market participants and benefit from economies of scale, such as support costs and process standardization.
In 2021, the technology and capabilities are here to finally resolve trade expense. By getting a better handle on trade expense, banks can reduce costs and gain transparency that will drive insight and value to their underlying businesses.