Introduction

The credit analysis skill gap in Australia is one of the most under-acknowledged yet important skill gaps in finance. In an era when interest rates have surged from their lowest levels, business bankruptcy is running at higher than pre-pandemic rates, and lenders in the banking, non-banking, and corporate sectors are experiencing credit pressures in portfolios built during the decade of low rates, the credit analysis capability of finance teams has never been more important. But why don’t finance teams have credit skills is a question many organisations are now starting to ask themselves, usually after a credit loss has highlighted the deficiency. 

Australia’s credit analysis skill gap affects institutional and non-institutional players. In the financial institutions and non-bank lenders, the impact of poor credit analysis skills was diminished by the decade of low interest rates, during which almost all borrowers could afford to service their debt; credit analysis skills were not applied and therefore declined. In corporate finance groups, credit analysis is seen as a specialised banking skill, rather than a mainstream finance skill, so corporate treasury, FP&A and M&A professionals lack the skills to evaluate the creditworthiness of their customers, suppliers or targets. Australia’s finance teams have extensive cross-functional skill gaps in credit risk. 

This piece is for finance professionals who wish to understand and improve their own credit risk assessment skills, managers who wish to improve their team’s credit risk assessment skills, and individuals who wish to leverage their skills and experience by gaining actual credit assessment skills in a market where these skills are rare and in high demand. 

What Credit Analysis Actually Requires — and Where Teams Fall Short

The three layers of lending risk assessment skills

Effective lending risk assessment skills span three dimensions, which training courses cover to varying degrees. The first is financial analysis: understanding what the past financial statements tell us about the quality of earnings, cash flows, leverage and working capital. The second is commercial analysis: understanding the business model, competitive strategy, industry structure, and management quality that determine the likelihood that past performance predicts future performance. The third is structural analysis: understanding how the particular credit structure, with its security, covenants, tenor and amortisation, addresses the risks identified in the first two layers. The first layer is something most finance professionals can do well; the second is more difficult; and the third is the layer most frequently relying on lawyers and credit committee approval rather than the analyst’s skills. 

•  Most bank credit analysis problems occur in the second layer: the commercial analysis that controls whether a borrower’s business plan is sound, whether the management has the skills to survive the bad times, and whether the industry is likely to play out as forecast. 

• Credit analysis errors in the third layer (covenant design, security perfection, intercreditor agreements) are the most common ones highlighted during a credit event, when the structural protections are relied upon but are ineffective or unenforceable. 

Why improving credit analysis skills is harder than it looks

The skills of credit analysis are more difficult to enhance than most modelling skills because the learning curve is delayed. A financial model either balances or it doesn’t; the error is obvious. An overly optimistic credit assessment may not be recognised as an error until 18-36 months later, when the borrower’s performance fails to match the assessment. By this time, the original credit assessor may no longer be on the credit team, the file may have been reviewed by one or more teams, and the chain of cause and effect from the initial credit weakness to the eventual impairment may no longer be clear. It is a feature of the industry that is structurally unsuited for skill development without practice design. 

•  Developing credit risk skills depends on the creation of artificial feedback loops in training environments: retrospective reviews of past credit assessments and outcomes, reviews of impaired credits to understand where the credit risk assessment went wrong, and presentation of credit risk recommendations in environments where expert practitioners will challenge them. 

•  The fastest way for credit professionals to build credit risk skills is to be in a high-activity credit review environment – workout teams, credit committee presenters, or lenders’ technical advisory engagements – where the feedback loop between assessment and outcome is more direct. 

Five Root Causes of Weak Credit Skills in Finance Teams

Effective team training in credit risk should start with the problem’s root causes, rather than its symptoms. The five causes below are the most frequently identified by credit professionals, bank regulators, and L&D professionals in credit capability development projects. 

Root Cause	How It Manifests	Finance Team Skill Gaps Australia Implication	How to Address It
1. Training that teaches ratios without judgment	Teams can calculate DSCR, interest cover, leverage ratios, and working capital metrics, but cannot explain what those ratios mean for a specific business in its specific stage and sector context	Weaknesses in credit assessment that result from ratio-only training produce analysts who flag the number but not the story; a 1.1x DSCR for a growth-stage business in a favourable sector is different from a 1.1x DSCR for a mature business in a declining sector	Ratio analysis must always be contextualised: practise explaining what each ratio implies about the business’s financial dynamics, not just whether it is above or below a threshold
2. Benign conditions that reduced the consequences of weak analysis	A decade of near-zero interest rates and strong economic conditions meant that most borrowers could service their debt regardless of the quality of the original credit assessment; weak analysis was not punished by outcomes	Bank credit analysis challenges are now surfacing as rates normalise and economic conditions tighten; analysts trained in benign conditions have never had to write a credit that failed, manage a stressed borrower, or value security in a distressed market	Build downside scenario analysis into every credit assessment as a standard discipline; practise stress-testing assumptions against realistic adverse scenarios, not just minor sensitivity adjustments
3. Over-reliance on templates and credit system outputs	Credit assessment templates are designed to ensure minimum coverage of key risk factors; they are not designed to substitute for the analytical judgment that determines whether the coverage is adequate for the specific credit	Credit evaluation mistakes in template-driven environments are often errors of omission: the template was completed, all boxes were ticked, and the specific risk that ultimately caused the impairment was not captured because it did not fit a template category	Use templates as a minimum coverage checklist, not as an analytical output; the narrative sections of a credit assessment are where the analytical judgment lives, and they should reflect genuine analysis rather than boilerplate
4. Limited exposure to credit events and workout situations	Finance professionals who have only worked in performing portfolios during benign conditions have never seen what a credit deterioration looks like from the inside: the early warning indicators, the management behaviour patterns, the cash flow dynamics of a business under stress	Lending risk assessment skills are most deeply developed through exposure to stressed credits; the professionals who have managed impaired borrowers understand what the pre-stress indicators look like in a way that purely theoretical training cannot replicate	Request involvement in credit review, early arrears management, or restructuring work within your organisation; study published case studies of credit impairments and work backward to identify the early indicators that were present in the original assessment
5. Credit analysis is treated as a banking skill, not a general finance capability	In many corporate finance teams, credit analysis is assumed to be a banking function that does not apply to FP&A, M&A advisory, or treasury — creating blind spots in customer credit risk, acquisition target credit quality, and supply chain financial exposure	Credit analysis skill gap Australia is not confined to banks; corporate finance teams that cannot assess the credit quality of their major customers, key suppliers, or acquisition targets are carrying unmanaged financial risk	Build credit literacy as a standard component of finance team development across all functions; the ability to read a credit risk profile is a commercial skill, not a specialist banking one

Of these five causes, the most relevant today is root cause 2 – benign conditions that minimise the impact of poor analysis. The credit professionals working in the Australian market in 2026 have operated the majority of their careers in a low-interest-rate, increasing house price, and conducive economic cycle period. The skills most important to a tightening credit environment – recognition of early warning signals, security valuation in a stressed environment, managing a distressed credit relationship, and negotiating a workout – were not honed because they were not required. Developing credit risk skills today demands simulating the environment that adverse credit experiences create, not more time in the world of performing credit analysis. 

How to Build Strong Credit Analysis Capability

A practical pathway for improving credit analysis skills

To build credit analysis capability, a development approach is needed that goes beyond textbook analysis of ratios to include commercial judgment, business structure assessment, and stress-testing skills that will distinguish analysts who can value a credit under normal circumstances from those who can value it under stress. The four-step journey below shows how a credit professional builds capability rather than compliance.

Phase 1	Phase 2	Phase 3	Phase 4
Financial Analysis Foundation	Commercial Assessment	Stress Testing and Structuring	Impaired Credit Study
Build fluency in cash flow analysis from source documents: operating, investing, and financing cash flows; practise distinguishing reported earnings from cash generation; identify normalisation adjustments in the P&L; calculate and contextualise DSCR, leverage, interest cover, and working capital metrics	Practise writing the commercial assessment section of a credit: competitive position, sector dynamics, management quality, and whether historical performance is a reliable guide to future; use five real businesses across different sectors; get feedback from an experienced credit practitioner	Build downside scenarios for every credit: what does the DSCR look like if revenue falls 15%, margins compress 200bps, or a key customer is lost? Practise designing covenant structures calibrated to the specific risks identified in the assessment	Study three to five publicly documented credit impairments: read the original business description, reconstruct what the credit assessment likely said, identify the early warning indicators that were present, and determine where the assessment failed

Real Cases and Lessons from the Field

Real cases: the consequences of credit evaluation mistakes

A regional lender had provided a term loan to a business service company based on its strong earnings before interest, taxes, depreciation and amortisation (EBITDA) over the past three years and its leverage (debt to equity) ratio of 2.8x at loan origination, which was in line with the bank’s sector policy. The credit analysis relied on financial ratios and collateral quality but did not consider the borrower’s revenue stream. In particular, it failed to note that 65% of the borrower’s revenue was derived from a single government contract that was up for re-tender 18 months after the facility was drawn. The loss of the retender led to a 58 per cent decline in EBITDA over the following 12 months, and a DSCR of 0.4x (covenant of 1.15x). The collateral was not sufficient to cover the loan at the stressed value. The credit assessment mistakes were not calculations: the original ratios were correct. The mistake was a commercial assessment error: the revenue concentration risk, which was evident in the borrower’s management accounts, was not recognised as a significant credit risk in the assessment. 

The second example is a corporate treasury department of a manufacturing company that granted 60-day credit to a large customer without a credit assessment. This customer accounted for about 18 per cent of the revenue. During the customer’s voluntary administration, the $2.3 million receivable was written off as doubtful, and a recovery rate of 12 cents in the dollar was estimated. The treasury team did not have a formal credit assessment process for customer credit risk, did not have a trigger that would have led to an earlier review of the customer’s creditworthiness and did not have credit insurance in place to cover the receivable. Why finance teams were not trained in credit assessment in this instance was not a banking failure, but a corporate finance failure that impacted the bottom line. Training finance teams in non-banking roles in credit risk is often overlooked because it is regarded as a banker’s skill – until it is too late.

Conclusion

The credit analysis skill gap in Australia is real and pervasive, now being put to the test in a credit environment that has not been as tough for many credit professionals in their careers. Deficiencies in credit assessment are structural, resulting from training based on ratios rather than judgment, favourable environmental factors that did not discourage poor credit analysis, and a culture that assumes credit risk is a banking specialty rather than a finance skill. Developing credit risk assessment skills across the finance team requires a development strategy that addresses the three dimensions of credit analysis: financial analysis, commercial analysis, and structural analysis. 

•  The most valuable single development initiative for any credit practitioner to build skills in credit analysis is to work on impaired credits in reverse: from the known outcome, reverse engineer the assessment, and determine exactly where the commercial or structural assessment went wrong; the learning from such a pattern recognition exercise cannot be gained in any other way. 

• Credit assessment errors are rarely errors in arithmetic; they are errors in judgement – specifically, errors in the commercial analysis of the sustainability of revenue, management quality and industry trends that determine whether historical financial ratios are a predictor of future performance. 

•  For managers developing credit risk training for groups: the single most valuable training investment is in creating artificial feedback loops (bring credits to teams who will test the commercial assessment, and review past decisions against outcomes); build stress testing as a routine rather than an optional sensitivity analysis.