Taking a new approach to portfolio management in a complex landscape

Faced with a rapidly evolving suite of tools and a more complex risk landscape, banks must take a new approach to portfolio management to be resilient. Historically, compliance or regulatory requirements were the drivers behind advancements in risk management, but they also reinforced siloed expertise and processes—an issue so inherent in banks’ operating models it can be difficult for executives to see a new way forward.

AI-enabled processes are reshaping how bank executives and Moody’s Analytics experts are surfacing actionable insights and directing expertise for enhanced operating leverage across the credit lifecycle. Portfolio monitoring is an important starting place for this transformation, as existing customer data is already available and represents embedded risks that shape the trajectory of future growth.

Portfolio management commonly falls to credit and enterprise risk executives, but there are key connections to front-office activities (new originations, cross sales, renewals, etc.) that risk officers should not overlook. A holistic approach to both risks and opportunities is more likely to justify the investment in these enhanced capabilities and will ultimately help banks grow profitably.

An integrated risk framework for growth

With this multidisciplinary mindset, we’ve established an outcome-focused framework for banks preparing for the future of credit:

1.Structured sensitivity analysis: Understanding events that impact borrowers’ businesses in an empirically structured way is key to an integrated risk assessment. Evolving regulatory and customer expectations are forcing bankers to address a range of business assumptions, macroeconomic and climate scenarios or “what-if” analytics.

To deliver the nuanced analysis these questions deserve, bankers must move beyond rudimentary shocks to borrower performance metrics. Tools that maintain relationships among financial statement line items (for example, shocks to revenue produce corresponding changes in cost of goods sold, inventory and accounts receivable) represent a significant step toward this goal. These tools help keep existing credit and enterprise risk management frameworks resilient to emerging risks and agile for new opportunities.

2.Ensemble of signals: The need to address the variety and frequency of signals that support decisions and target experts where they add value is a key competitive evolution. Equity market, trade credit, adverse media, cyber risk scores, climate and macroeconomic scenarios and industry and peer benchmarks are all examples of alternative signals that enrich traditional risk measures and provide a more diverse mosaic of evidence to support confident decision-making.

To find opportunities and stay on top of risks, portfolio managers need to assess potential gaps in traditional approaches (e.g., financial statements are a historic view of a customer’s business and only arrive annually), address portfolio data that is scattered across systems and mitigate risks of bias or information gaps that could skew analysis. Solutions that centralize these inputs and increase the diversity of signals available are critical enhancements to bank operating leverage— helping bankers prioritize opportunities, get earlier warnings for changes in risk and transform manual or periodic processes by targeting expertise in real time.

3.AI-enhanced expertise: While there is no shortage of hyperbole around the ways AI will impact the future, there are present examples of its impact on credit processes and a steady pipeline of innovations that make it an invaluable tool for bankers. Current AI and machine learning tools for adverse media scanning and automated financial data ingestion have brought substantive operating leverage to loan origination and credit review processes by moving experts away from data entry and toward judgments and client interactions.

Smart workflow tools expand on this foundation by helping experts manage the ensemble of signals they’ve assembled and identify patterns that traditional approaches may miss—benefiting portfolio and opportunity management, as well as fraud detection and other multidisciplinary applications.

With this framework for the future of credit, portfolio managers and experts from across the bank can prioritize investment opportunities and reimagine their portfolio processes for profitable growth. The best way to grow your business is always to help your customers grow theirs— understanding your customers with sensitivity analysis, monitoring changes with an ensemble of signals and amplifying the impact of your experts with smart technology are all key to this effort in an evolving risk environment.

Chris Stanley is Moody’s Analytics’ senior director, banking industry practice lead.

We offer actionable insights on other data and analytics topics that can benefit financial institutions in the BAI Executive Report, “The insights of data and analytics.”