In today's highly competitive and heavily regulated financial landscape, global banks must understand each client's profitability in a scalable and repeatable manner.
Daily insights into how much each client relationship contributes to Net Interest Income (NII) enable executives to make data-driven decisions, from optimising Risk-Weighted Assets (RWAs) to identifying high-value customers. However, calculating this metric daily presents a significant architectural challenge.
This blog explores the high-level architecture required and why off-the-shelf, cloud-native solutions like Oracle Profitability and Balance Sheet Management Cloud Service can accelerate the delivery of building in-house solutions using public cloud providers like AWS or GCP, which is what most of our banking clients are doing.
The High-Level Architecture for Daily Client Profitability
At its core, a daily client profitability system relies on a robust data warehouse that aggregates vast amounts of data from disparate sources across the bank. This includes transaction details, account information, product usage data, and risk factors. The data warehouse feeds a powerful analytics engine capable of slicing and dicing this data by client relationship, product, and other relevant dimensions. Finally, a user-friendly reporting layer presents these insights in an easily digestible format for executives.
Calculating Net Client Profitability
Net client profitability is a comprehensive metric that considers all the costs associated with serving a client and subtracts them from the income generated. Here's a deeper dive into the specifics of this calculation, an area where Revvence has deep expertise:
- Income Streams: The system captures all income generated by the client relationship, including interest income, fees, commissions, trading profits, and a breakdown of NII contribution.
- Direct Costs: This includes all expenses directly attributable to serving the client, such as people, transaction processing costs, and product-specific costs.
- Indirect Costs: Allocating indirect costs like overhead, technology infrastructure, and risk management to individual clients can be complex. Cloud-native solutions often leverage sophisticated allocation models based on industry best practices to ensure accurate cost attribution.
- Risk Provisions: The system factors in provisions for potential loan losses, impairments, and other credit risks associated with the client, which impacts RWAs.
Risk Adjusted Performance (RAP)
We are encouraging our clients to explore the benefits of building robust systems and analytics to make the details of the risk-adjusted performance of clients or products pervasive across the bank.
Here's how we think RAP helps our clients to make smarter decisions, optimise resources, and ultimately, drive superior business outcomes:
- Granular Pricing Strategy: RAP goes beyond simple profitability. It allows you to see how much risk you're taking on for each unit of revenue generated by a client. This empowers you to set risk-adjusted pricing strategies, ensuring you're adequately compensated for the level of risk involved.
- Improved Capital Allocation: Regulatory requirements often tie a bank's capital reserves to its risk profile. Daily RAP gives you the insights needed to allocate capital efficiently. You can ensure you don't over-allocate reserves to cover miscalculated potential losses from high-risk clients. There is the potential to free up capital to support lending to lower-risk clients.
- Identify and Prioritise High-Value Clients: RAP helps you identify the sweet spot – clients who deliver strong profitability while posing a minimal risk. These are the clients you want to nurture and invest in. Daily insights allow you to proactively engage with these high-value relationships, strengthen partnerships, and unlock further growth opportunities.
- Faster, Data-Driven Decision Making: Intuition and experience are valuable, but in today's data-driven world, cold, hard facts are essential. Daily RAP provides a wealth of objective data that can inform critical decisions across various departments, from credit risk management to product development and marketing. We've seen this objective hampered by slow in-house systems that don't deliver insights at the level of granularity needed.
Daily Risk-Adjusted Performance is not just another metric for banking executives. It's a must-have insight for more intelligent decision-making and optimised resource allocation to deliver superior business results.
Critical System Capabilities
We can provide an exhaustive list of system capabilities to deliver a scalable, high-performance, client-level profitability platform, but at a high level, the critical capabilities should include:
- An Open Allocation Engine: An open allocation engine allows you to combine different methodologies, from simple to complex, to create profitability line items. This flexibility will enable you to build both top-down and bottom-up allocations. The allocation engine should be capable of utilising transaction-level data, customer relationship data, or management ledger data.
- Sophisticated Profitability Modelling: Profit models should leverage aggregate balance data, detailed customer-level instrument data, and transaction-level data to build sophisticated profitability models. The solution should allow analysts to combine combinations of attributes, hierarchies, dimensions, and filters to precisely define business rules.
- Integrated Balance Sheet Management: The ability to fully model the cost of funds, transfer pricing, capital allocations, etc., at a detailed cash-flow level is essential, especially for improving capital allocations. By understanding, at the lowest level, your client's projected future cash flows, you can make more accurate capital allocation decisions. We believe many of our clients are tying up more capital than they need to, and by incorporating cash-flow forecasting alongside profitability analytics, you can free up capital for potentially higher-yielding opportunities.
- Ultra High Performance: For our clients with millions of clients and enterprise-scale requirements, it's critical that any system can process billions of data points in minutes and not hours or days.
Build versus Buy
It's important to note that most of our banking clients are opting to build their crucial finance platforms for regulatory reporting and stress-testing. However, integrating a reliable commercial platform like Oracle's can provide significant advantages in delivering client-level profitability insights.
The Downsides of Building In-House on AWS/GCP
While public cloud providers like AWS and GCP offer a tempting platform for building your own solution, several drawbacks make them expensive and risky for a client-level profitability solution. At Revvence, our approach is to integrate our profitability solutions so that they can seamlessly co-exist with internal initiatives.
Some of our observations from existing clients who are following a build strategy include:
- Integration Complexity: Integrating siloed data sources into a cohesive data warehouse is a monumental task. Public cloud providers offer generic data management tools, but financial institutions require specialised tools to handle complex financial data.
- Time to Value: Designing, building, testing and integrating all the necessary components for a profitability solution from scratch is a lengthy process with an uncertain outcome. In our experience, clients can spend years working on complex solutions such as profitability analytics.
- Significant Resource Allocation: It is staggering the number of people and expensive external consultants our banking clients allocate to build projects in-house. Building from scratch appears to have limited, if any, strategic value and the potential cost savings can be material to the P&L.
Cloud-Native Solutions: A More Efficient, Cost-Effective Path
Cloud-native solutions like Oracle Profitability and Balance Sheet Management Cloud Service offer a pre-built, industry-specific solution specifically designed for financial institutions. These solutions leverage the benefits of the cloud – scalability, elasticity, and subscription pricing – while addressing the unique challenges of the banking industry.
When discussing the options with our clients, we typically highlight the following upsides:
- A Pre-Built Profitability Architecture: This architecture includes pre-built data models, configuration abilities, business rules and integration APIs designed explicitly for profitability data. This significantly reduces development time and ensures seamless integration with your in-house build strategy.
- Faster Insights: If improving performance and returns for shareholders is critical now, why wait for an in-house system to be finished? The Oracle pre-built solution allows for quicker implementation, in our experience, weeks, not years, providing the business with the client profitability insights you can use sooner rather than later.
- Reduced TCO: A solution designed specifically for the profitability use case offers a predictable cost structure, with ongoing maintenance and upgrades handled by Oracle. This frees up your critical resources for other strategic initiatives.
How can we help?
Revvence can help in several valuable ways:
- Benchmark your current approach versus best-in-class.
- Creating a strategy roadmap and execution plan to deliver a robust, scalable, daily, client-level profitability solution.
- Creation of a proof-of-concept to show you the art of the possible and build your business case.
- The design and delivery of an end-to-end client-profitability solution.