Expected Loss is a critical KPI that quantifies potential financial losses due to credit risk, influencing cash flow and overall financial health.
It serves as a leading indicator for risk management, enabling organizations to align their strategies with risk appetite.
By understanding expected loss, executives can make data-driven decisions that enhance operational efficiency and improve cost control metrics.
This KPI directly impacts business outcomes, such as profitability and liquidity, by providing insights into potential defaults.
Effective management reporting on expected loss can drive better forecasting accuracy and enhance the overall KPI framework.
High values of expected loss indicate significant credit risk and potential financial strain, while low values suggest effective risk management practices. Ideal targets typically align with industry benchmarks, reflecting a balance between risk and return.
We have 3 relevant benchmarks in our benchmarks database.
Source: Subscribers only
Source Excerpt: Subscribers only
Additional Comments: Subscribers only
| Value | Unit | Type | Company Size | Time Period | Population | Industry | Geography | Sample Size |
| Subscribers only | basis points | quartiles | large corporates | lifetime ECL (Stage 2) | hypothetical borrower, participating banks’ IFRS 9 models | banking | United Kingdom | 26 banks |
Source: Subscribers only
Source Excerpt: Subscribers only
Additional Comments: Subscribers only
| Value | Unit | Type | Company Size | Time Period | Population | Industry | Geography | Sample Size |
| Subscribers only | basis points | quartiles | large corporates | 12-month ECL (Stage 1) | hypothetical borrower, participating banks’ IFRS 9 models | banking | United Kingdom | 26 banks |
Source: Subscribers only
Source Excerpt: Subscribers only
Additional Comments: Subscribers only
| Value | Unit | Type | Company Size | Time Period | Population | Industry | Geography | Sample Size |
| Subscribers only | percent | threshold | Year 5 | rated instruments | structured finance | global |
Many organizations overlook the importance of accurately calculating expected loss, leading to misguided financial strategies.
Enhancing expected loss metrics requires a proactive approach to risk management and credit evaluation.
A mid-sized financial services firm faced challenges with its expected loss metrics, which had steadily increased over the past year. This rise indicated potential liquidity issues and prompted the CFO to initiate a comprehensive review of credit policies. The firm employed a data-driven approach, leveraging advanced analytics to reassess customer creditworthiness and refine risk models.
The initiative involved cross-departmental collaboration, bringing together finance, sales, and risk management teams. They identified key segments of customers with higher default rates and adjusted credit limits accordingly. Additionally, the firm implemented a new reporting dashboard that provided real-time insights into expected loss, allowing for timely interventions.
Within 6 months, the firm saw a 30% reduction in expected loss, significantly improving its financial health. The enhanced metrics enabled better forecasting accuracy and informed strategic decisions, leading to more effective cost control. As a result, the firm regained confidence from stakeholders and positioned itself for sustainable growth.
This KPI is associated with the following categories and industries in our KPI database:
KPI Depot takes you from KPI intelligence to finished deliverable. Consultants, strategy teams, FP&A leaders, and analytics teams use it to answer the two hardest questions in performance management, what to measure and what the target should be, and then to produce the scorecard itself.
The difference is intelligence, not just data. Anyone can list metrics. Every KPI in KPI Depot carries 13 practical attributes, from formula and measurement approach to diagnostic questions, risk warnings, and Balanced Scorecard perspective, across 15 corporate functions and 153 industries. And every target you set is grounded in our database of 34,304 source-attributed benchmarks, each detailing metric value, company size, time period, industry, geography, sample size, and source. Benchmark data at this scale is otherwise the domain of research services costing thousands to hundreds of thousands of dollars per year.
When your metrics are selected, KPI Depot finishes the job: export an interactive Strategy Map, a Balanced Scorecard with formulas and tracking columns, or a CSV KPI pack, and go from research to working deliverable in hours instead of weeks.
Formerly the Flevy KPI Library, KPI Depot is trusted by teams at organizations including Accenture, EY, IBM, PepsiCo, Samsung, and Vodafone.
Got a question? Email us at [email protected].
Key factors include customer creditworthiness, economic conditions, and industry trends. Changes in any of these areas can significantly impact the expected loss calculation.
Regular reviews are essential, ideally on a quarterly basis. This frequency allows organizations to adapt to changing market conditions and customer behaviors effectively.
Yes, higher expected loss may necessitate stricter credit terms. Organizations often adjust their credit policies to mitigate risk and protect cash flow.
While it is particularly critical in finance and lending, expected loss metrics are relevant across various sectors. Any business that extends credit should monitor this KPI to manage risk effectively.
Advanced analytics and machine learning can enhance the accuracy of expected loss models. These technologies allow organizations to process large datasets and identify patterns that inform risk assessments.
A lower expected loss can lead to improved ROI by reducing bad debt and enhancing cash flow. Effective risk management practices contribute to better financial performance and strategic investments.
Each KPI in our knowledge base includes 13 attributes.
A clear explanation of what the KPI measures
The typical business insights we expect to gain through the tracking of this KPI
An outline of the approach or process followed to measure this KPI
The standard formula organizations use to calculate this KPI
Insights into how the KPI tends to evolve over time and what trends could indicate positive or negative performance shifts
Questions to ask to better understand your current position is for the KPI and how it can improve
Practical, actionable tips for improving the KPI, which might involve operational changes, strategic shifts, or tactical actions
Recommended charts or graphs that best represent the trends and patterns around the KPI for more effective reporting and decision-making
Potential risks or warnings signs that could indicate underlying issues that require immediate attention
Suggested tools, technologies, and software that can help in tracking and analyzing the KPI more effectively
How the KPI can be integrated with other business systems and processes for holistic strategic performance management
Explanation of how changes in the KPI can impact other KPIs and what kind of changes can be expected
NEW Mapping to a Balanced Scorecard perspective (financial, customer, internal process, learning & growth)