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Overview
As part of my Executive MBA at Ivey Business School, I built a Canada SME Financial Stress & Credit Demand Tracker to examine how shifting financing conditions manifest in both business sentiment and credit dynamics. The project combines high-quality public datasets from the Bank of Canada and Statistics Canada into a simplified, repeatable framework that can support executive decision-making.
What I did
I downloaded and structured three complementary data sources: the Bank of Canada's Business Outlook Survey (BOS), the Senior Loan Officer Survey (SLOS), and Statistics Canada's business credit series. I then built a clean quarterly analysis panel in Excel, selecting leading indicators related to credit conditions (from the firm perspective) and business lending standards (from the bank perspective). To make the signals comparable, I standardised the BOS and SLOS series and constructed a composite SME Financial Stress Index.
To help distinguish short-term noise from underlying direction, I added a four-quarter moving average, a simple deviation-from-mean measure, and a traffic-light classification (green/yellow/red). I also linked the stress index to observed business credit levels and year-over-year growth to test whether survey-based tightening or easing was reflected in actual lending outcomes. The final output is an executive-friendly summary view with charts and a recurring "pulse" structure.
Chart 1: SME Financial Stress Index (Canada)
This chart tracks a composite SME financial stress index for Canada alongside a 4-quarter moving average. The goal is to convert noisy survey signals into a single, readable stress "pulse" that highlights regime shifts rather than month-to-month volatility. The core intelligence is that the index clearly captures major stress cycles over the last two decades, with pronounced spikes around crisis periods and visible easing phases afterward. The moving average helps confirm whether a spike is a true turning point or just short-term noise. This chart is therefore a compact way to communicate when SME balance sheets and credit conditions are tightening versus normalising.
Chart 2: Financial Stress vs Business Credit Growth
This chart overlays the SME financial stress index with year-over-year business credit growth. It is designed to show the interaction between sentiment/constraints and real credit outcomes. The key intelligence is the directional relationship: when stress rises, credit growth tends to weaken or become more volatile, while periods of easing stress are more consistent with stabilising or recovering credit conditions. Even without claiming strict causality, the visual makes an important macro point for lenders and SME ecosystems: stress is not just a survey story; it has a measurable connection to financing momentum. This chart therefore works as an early-warning lens for shifts in SME credit demand and supply conditions.
Why it matters
Access to financing is a defining constraint for small and medium-sized businesses, especially during periods of macro uncertainty. A timely understanding of whether credit conditions are tightening or easing can shape expectations for SME investment, hiring plans, and capital demand. This project demonstrates how high-quality survey signals, when combined into a simple composite index and validated against credit trends, can provide a more reliable read of the financing environment than any single indicator alone.
How can this be used in practice?
This framework is designed to function as a repeatable monitoring tool rather than a one-off analysis. With richer data inputs—such as firm-level transactional or balance-sheet microdata—the same methodology could be extended into sector- and region-specific risk signals, more granular liquidity and cash-flow stress measures, and early-warning indicators for lenders, policymakers, and SME support organisations. The format naturally lends itself to quarterly or monthly updates, where the narrative, charts, and index refresh with minimal manual effort.
Tech stack
I used Excel for time-series structuring, standardisation, rolling averages, and year-over-year calculations. I relied on Bank of Canada BOS and SLOS data, alongside Statistics Canada's business credit series, as core inputs. The workbook is organised as a reusable tracker: once new observations are added, the index, charts, and summary can be updated efficiently.
