Project Overview

Introduction

A major headline across Victoria highlights the rising cost of living, with more households struggling to pay bills and facing financial hardship.

This analysis examines performance indicators from the Compliance and Performance Reporting Guideline (CPRG) to assess whether there is evidence that cost-of-living pressures are driving financial hardship among residential electricity customers. The findings will provide data-driven insights to inform policy reforms aimed at strengthening consumer protections and reducing financial strain.

Objectives

  • Assess Disconnection Risk – Are more residential electricity customers at risk of being disconnected (received a disconnection notice) or being disconnected because of non-payment of their bills?
  • Analyse Arrears Growth – Are arrears (debts) increasing for residential electricity customers who receive financial assistance in the form of tailored assistance?
  • Measure Tailored Assistance Uptake – Are more residential electricity customers accessing tailored financial assistance?

By the end of this analysis, we will have a clear understanding of how affordability challenges impact electricity customers, helping decision-makers respond proactively.

Impact

The insights from this analysis will support targeted policy recommendations to help both consumers and energy providers navigate financial challenges:

  • Enhanced Consumer Protections - If affordability issues are worsening, regulators may introduce stronger safeguards to prevent unnecessary disconnections.
  • Improved Assistance Programs - Identifying trends in arrears and financial assistance uptake can help optimize support mechanisms for vulnerable customers.
  • Retailer Stability & Market Resilience - Understanding arrears growth and disconnection patterns will allow retailers to anticipate risks and adapt their strategies accordingly.

By providing data-driven evidence, this analysis will inform decision-making for policymakers, regulators, and energy retailers, ensuring that financially vulnerable customers receive the necessary support.


Note: This report utilizes toggle buttons to enhance readability, allowing stakeholders to easily digest key insights while providing the option to explore technical details as needed.


Data Understanding

Data Source

The dataset used in this analysis comes from the Essential Services Commission’s Compliance and Performance Reporting Guidelines (CPRG). It contains monthly performance indicators reported by energy retailers to track customer affordability and financial distress in the Victorian electricity market. The data is reported separately for electricity and gas, with customer and retailer segmentation by size (small, medium, large).

Performance Indicators

Below are the key performance indicators used in this analysis, categorized by focus area.


Data Preprocessing

Data Inspection

Install Packages & Libraries


Import Dataset


Data Validation


Column Breakdown

Column Name Type Description Observations
fuel Character Type of energy (Electricity or Gas). All values: “Electricity”
yearmonth Integer Year and month of the record (YYYYMM format). Range: 202107 - 202406 (approx. 3 years)
retailer_id Character Unique identifier for the energy retailer. Coded retailer IDs (e.g., “RET_17”)
indicator_common_id Character Performance indicator code (e.g., D050A, AR031). Indicator codes (e.g., “AR070”)
indicator_common_name Character Name of the performance indicator. Description of performance indicators
customer_type Character Type of customer (Residential or Business). All values: “Large business”, “NULL”, “Residential”, “Small Business”
value Numeric The recorded metric for the given indicator. Min: -248.6, Max: 1,274,863, Median: 1, Mean: 2,551.1
retailer_size Character Size of the retailer (Small, Medium, Large). “Small”, “Medium”, “Large”


Dataset Overview

  • Number of observations: 149,033 rows
  • Number of variables: 8 columns
  • Data type distribution:
    • 5 categorical columns (chr type)
    • 1 integer column (yearmonth)
    • 1 numeric column (value)
  • All datatypes correct.
  • Column headers follow snake_case naming conventions, ensuring consistency.

Data Investigation Summary

During the data investigation phase, the dataset was explored to identify potential cleaning requirements and gather key insights before proceeding with data processing. Below are the initial observations:

1. Unique Values & Data Distribution

  • Fuel Type: All values in the dataset are Electricity, meaning there is no need to filter out gas-related records.
  • Retailers: The dataset contains 51 retailers (ID range 0-52), with RET_47 missing.
  • Customer Type: Found 4 unique values – Large business, NULL, Residential, Small business.
  • Retailer Size: Found 4 unique values – Large, Medium, NULL, Small.
  • NULL Values:
    • Present in the customer_type and retailer_size columns.
      • All NULL values in customer_type are linked to B220, which falls outside the scope of our assigned KPIs and does not impact the analysis.
      • NULL values in retailer_size appear in 9.41% to 13.66% of associated KPIs, several of which are relevant to this analysis. However, since retailer_size is not a critical factor in assessing cost-of-living impacts on bill payments, these values will be retained to prevent unnecessary data loss.


2. CPRG Discrepancy with D161 and D162 Indicators

  • D161(a–e) are mislabeled, with indicator_common_name values and thresholds that do not align with CPRG definitions.
  • D162(a–e) exist in the dataset but are missing from the CPRG—however, their indicator_common_name values correctly align with D161 definitions.
  • CPRG defines D161 indicators as (c–g), but they should be (a–e), indicating a clear labeling error.
  • Example discrepancy:
    • D161(d) = ResidentialArrearsAtDisc_2000to3000 (incorrect, does not match CPRG’s 4th item).
    • D162(d) = ResidentialArrearsAtDisc_2000to5000 (correctly matches CPRG’s 4th item).
  • Impact: Resolving this issue requires removing D161(a–e) and relabeling D162(a–e) as D161(a-e), resulting in a 28.67% reduction in the D161/D162 disconnections data and 1.36% total dataset reduction.
  • Final Check: All other high value indicator_common_ids were verified and match CPRG requirements.


3. Missing Values & Data Integrity

  • Zero missing values, but many instances of ‘NULL’ as a category
  • No duplicate records were detected.
  • No whitespaces detected


4. Outlier Detection

  • value Column: Identified multiple outliers:
    • 1 lower outlier.
    • 28,509 upper outliers.
    • Further investigation is required to determine their relevance to key performance indicators (KPIs).
  • Negative values all associated with average total arrears of small business accounts receiving payment assistance (AR060).


Data Cleaning

Action Steps

Correct mislabeled indicators:

  • Remove D161(a–e) records, as their values do not align with CPRG definitions, causing a 28.67% reduction in D161/D162 disconnections data and 1.36% total dataset reduction.
  • Relabel D162(a–e) as D161(a–e) to align with CPRG standards.

Transform yearmonth for better time-series analysis:

  • Split the yearmonth column (YYYYMM format) into separate Year and Month columns.
  • Create a standardized Date column by combining the Year and Month columns into a proper YYYY-MM-DD format, setting the day as the first of the month for consistency.

Filter dataset to focus on relevant indicators:

  • Create a cleaned dataframe (customer_data_cleaned) containing only performance indicators for disconnections, arrears, and financial assistance uptake, including D050A, D140, D161(a to e), D170(a & b, AR031(a to f), ASO22(a & b), ASO31(a & b), AS061, AS080.
  • Exclude rows where customer_type is Large business, NULL, or Small business, as they do not pertain to residential customers.


Disconnections Analysis

To answer the question, “Are more residential electricity customers at risk of being disconnected (received a disconnection notice) or being disconnected because of non-payment of their bills?”, this section examines whether residential electricity customers are increasingly at risk of disconnection due to unpaid bills. The analysis focuses on two key areas:

  1. Risk of Disconnection – Trends in disconnection warning notices to assess whether more households are approaching disconnection.
  2. Actual Disconnections – Trends in service disconnections due to non-payment, including variations across arrears levels.

By evaluating these indicators over time, this analysis aims to determine whether financial hardship is escalating and to provide insights that can inform consumer protection measures and support programs.


1. Reminder & Disconnection Warning Notices

“Are Reminder Notices (D170(a)) and Disconnection Warning Notices (D170(b)) Increasing Over Time?”



Key Insights

Yes, the data reveals a significant rise in reminder notices for unpaid bills, while disconnection warnings have increased at a much slower pace.

  • Reminder notices (D170(a)) have increased by 46.4% over the analysis period, with an average of 656 additional notices issued each month. This suggests a growing number of households struggling to pay on time.
  • Disconnection warning notices (D170(b)) have increased by only 7.4%, with an average increase of 39 per month. This indicates that while more customers are missing payments, fewer are reaching the final warning stage.
  • The gap between reminder notices and disconnection warnings is widening, suggesting that some households are able to resolve overdue bills before facing service disconnection.


3. Gap Analysis Between Notices & Disconnections

“What is the gap between reminder notices (D170a), disconnection warning notices (D170b), and actual disconnections (D050A)?”



Key Insights

The gap between reminder notices (D170a), disconnection warnings (D170b), and actual disconnections (D050A) has widened over time, indicating that most overdue accounts do not escalate to disconnection.

  • Reminder notices far outnumber both disconnection warnings and actual disconnections, showing that most customers do not progress beyond initial notices.
  • The reminder-warning gap peaked at 66,101 accounts, suggesting that many customers resolve arrears or enter payment plans before reaching the warning stage.
  • The warning-disconnection gap remains stable, with 19,480 more accounts receiving a final warning than being disconnected, reinforcing that few customers experience actual service termination.
  • Overall, disconnections have declined by 54.8% and remain low.


4. Additional Insights: Retailer Breakdown


Summary of Disconnection Insights

“Are more residential electricity customers at risk of being disconnected (received a disconnection notice) or actually being disconnected due to non-payment?”

📌 More customers are at risk, but actual disconnections remain low.

Despite a 46.4% surge in reminder notices, actual disconnections remain low, indicating that while more households are struggling to pay on time, most do not progress to disconnection. Disconnection warnings have risen at a much slower rate (+7.4%), and the widening gap between notices and disconnections suggests that many customers are resolving overdue balances before service termination. Customers with arrears between $300 and $1,999 face the highest disconnection risk, particularly those owing $1,000+, but relatively few are ultimately disconnected.

Large retailers issue the majority of notices, yet few follow through with disconnections, indicating that a significant number of overdue customers avoid service loss—whether through payments, retailer policies, or other factors. However, disconnections among customers without financial assistance closely mirror overall trends, suggesting that either support programs are not significantly reducing disconnections, or many at-risk customers are not accessing available assistance. This raises the need to evaluate how effectively financial support programs prevent service terminations and whether outreach or eligibility adjustments are necessary.

Metric Value
Reminder Notices Increase (D170a) +46.4%
Disconnection Warnings Increase (D170b) +7.4%
Peak Reminder-Warning Gap 66,101 accounts
Peak Warning-Disconnection Gap 19,480 accounts
Highest Disconnection Risk Group $300 - $1,999 arrears
Disconnections Trend Volatile, but down by 54.8%


Arrears Growth Analysis

To answer the question, “Are arrears (debts) increasing for residential electricity customers who receive financial assistance in the form of tailored assistance?”, this section examines whether financial hardship is escalating among customers enrolled in tailored assistance programs. The analysis focuses on three key areas:

  1. Overall Arrears Trend – Are arrears increasing over time for customers on financial assistance, indicating growing financial strain?
  2. Arrears Growth by Bracket – Are higher arrears ($2,000+) growing faster than lower arrears (<$1,000)? And does this indicate debt escalation into higher brackets?
  3. Effectiveness of Assistance by Arrears Bracket – Are customers’ arrears decreasing over time after entering financial assistance, or do debts continue to escalate within each bracket?

By evaluating these indicators over time, this analysis aims to assess whether financial assistance programs are effectively reducing arrears or if additional consumer protections and support measures are needed.


1. Overall Arrears Trend Over Time

“Are arrears increasing over time for customers on financial assistance, indicating growing financial strain?”




Key Insights

No, arrears have not shown a sustained upward trend from the first recorded data point, but there has been an upward trend since mid-2023.

  • Total arrears have fluctuated but declined 5.85% from their initial recorded value, showing no sustained upward trend.
  • Arrears peaked at $18,721 but ended at $14,351, suggesting they are being managed rather than escalating.
  • Volatility remains high, particularly from mid-2022, indicating seasonal or economic factors may be driving temporary spikes.
  • The sharp drop in mid-2023 stands out as a notable anomaly, and understanding its cause could provide critical business insights.


2. Arrears Growth by Bracket

“Are higher arrears growing faster than lower arrears? And does this indicate debt escalation into higher brackets?”




Key Insights

Yes and No. YES, high arrears grew while low arrears declined, but NO, the trends don’t confirm direct debt escalation.

  • High arrears ($1,000+) grew by 22.5% (from $3,558 to $4,358), but this increase is moderate and does not indicate widespread debt escalation.
  • Low arrears (<$1,000) declined by 14.5% (from $11,684 to $9,993), meaning fewer customers hold small overdue balances.
  • Both low and high arrears dipped to lows in mid-2023, then increased together, which does not align with a direct shift from low to high arrears.
  • While some movement into higher arrears is possible, other factors—such as repayments, financial assistance, or seasonal fluctuations—may also be influencing these trends.
  • The overall trend does not show sharp or accelerating growth in high arrears, suggesting that while financial strain exists, debt escalation into higher brackets is not a dominant pattern.


3. Assistance Effectiveness by Bracket

“Are customers’ arrears decreasing over time after entering financial assistance, or do debts continue to escalate within each bracket?”




Key Insights

No, arrears have not broadly reduced after entering financial assistance.

  • The $55-$999 arrears bracket decreased by 19%, indicating that some customers are reducing their debt after receiving financial assistance.
  • All higher arrears brackets ($1,000+) have increased, with the $1,000-$1,999 group rising by 26.7% and the $5,000+ bracket growing by 30.9%, suggesting that some customers struggle to stabilize their debt even with assistance.
  • The overall distribution of arrears remains similar over time, meaning financial assistance has not drastically shifted customers out of higher debt brackets.
  • The number of customers in the lowest arrears category (Below $55) has increased slightly (+4.15%), but this change is minimal compared to growth in higher arrears.
  • As observed earlier, arrears in general have reduced by 5.85%, but this is because the only bracket that decreased ($55-$999) also has the highest count of customers. Remove that bracket and arrears have increased by 15.3%.


Summary of Arrears Insights

“Are arrears (debts) increasing for residential electricity customers who receive financial assistance in the form of tailored assistance?”

📌 No, arrears have not broadly increased for residential electricity customers receiving tailored assistance, but financial strain persists for many.

Total arrears have declined 5.85%, primarily due to a 19% reduction in the $55-$999 bracket, which holds the largest number of customers. However, when excluding this bracket, arrears in all other categories have increased by 15.3%, indicating that while some customers successfully reduce their debt, others continue to accumulate more over time.

The distribution of arrears remains relatively stable, meaning assistance programs have not significantly shifted customers out of higher debt brackets. A sharp drop in arrears in mid-2023 stands out as an anomaly, warranting further investigation into potential economic or policy-driven factors.

While debt escalation is not widespread, the rising arrears in higher brackets indicate that financial assistance may not be effectively supporting all at-risk customers. A targeted review of assistance programs could help improve their impact on long-term debt reduction.

Metric Value
Total Arrears Trend Volatile, down 5.85%
Low Arrears Change (<$1,000) -14.5% (Improved)
High Arrears Change ($1,000+) +22.5% (Increased)
Biggest Arrears Reduction $55-$999 (-19%)
Biggest Arrears Growth $5,000+ (+30.9%)
Notable Anomaly Sharp drop in mid-2023


Payment Assistance Analysis

To answer the question, “Are more residential electricity customers accessing tailored financial assistance?”, this section examines trends in assistance uptake and whether customers successfully complete assistance or struggle to stay enrolled. The analysis focuses on two key areas:

  1. Overall Financial Assistance Uptake – Are more residential customers enrolling in tailored financial assistance over time?
  2. Successful Completion or Struggling to Stay Enrolled - Is financial assistance helping customers regain stability, or are many struggling to meet requirements and being removed from the program?

By evaluating these trends, this analysis determines whether access to financial assistance is expanding and how effectively customers are able to stay enrolled and complete the program.


1. Overall Financial Assistance Uptake

“Are more residential customers enrolling in tailored financial assistance over time?”




Key Insights

Yes, more residential customers are enrolling in tailored financial assistance, but growth has been gradual with fluctuations.

  • Total enrollment in tailored assistance has increased from 95,863 to 101,959 customers (+6.36%), indicating a steady rise in participation over time.
  • Tailored Assistance (Cannot Pay) saw the highest growth (+36.9%), suggesting a growing number of households unable to meet basic payment obligations.
  • Concession Assistance (Can Pay) declined by 25.4%, indicating that fewer concession recipients who can still afford payments are relying on support.
  • Since mid-2022 (it’s lowest point), assistance enrollment has grown by approximately 15.93%, reinforcing the trend of increasing uptake after a period of decline.


2. Successful Completion or Struggling to Stay Enrolled

“Is financial assistance helping customers regain stability, or are many struggling to meet requirements and being removed from the program?”




Key Insights

No, more customers are struggling to stay enrolled in financial assistance than successfully exiting with $0 arrears.

  • The high rate of non-compliance exits (65.4%) vs. successful completions (34.6%) demonstrates that more customers fail to meet requirements than successfully repay debts.
  • The 38.7% decline in successful completions suggests it is becoming harder for participants to fully resolve their arrears.
  • The 5.5% rise in non-compliance removals highlights that financial hardship persists for many enrolled customers.
  • The low success-to-noncompliance ratio (0.53) reinforces that for every customer who exits debt-free, nearly two are removed, showing that the program struggles to retain participants effectively.


Summary of Assistance Insights

“Are more residential electricity customers accessing tailored financial assistance?”

📌 Yes, but participation trends show mixed signals, with enrollment increasing overall while program exits due to non-compliance remain high.

Financial assistance participation has increased by 6.36% overall and 15.93% since mid-2022, reflecting rising demand. However, growth is uneven—assistance for those who cannot pay without a concession surged 36.9%, while participation among concession recipients who can pay fell 25.4%, suggesting worsening financial strain among the most vulnerable.

Despite increased enrollment, program retention is a challenge. 65.4% of exits are due to non-compliance, while just 34.6% exit successfully with $0 arrears. The success-to-noncompliance ratio (0.53) indicates that for every successful completion, nearly two customers are removed due to non-compliance. Additionally, successful completions have dropped by 38.7%, signaling greater difficulty in regaining financial stability. These trends highlight the need to assess whether current assistance structures are effectively supporting long-term recovery.

Metric Value
Total Assistance Enrollment Growth +6.36%
Growth Since Mid-2022 Low +15.93%
Largest Assistance Uptake Cannot Pay (No Concession) +36.9%
Largest Assistance Decline Can Pay (With Concession) -25.4%
Non-Compliance Exits 65.4% of all exits
Successful Completions 34.6% of all exits


Conclusion

“Is there evidence that cost-of-living pressures are driving financial hardship among residential electricity customers?”

📌 Yes, cost-of-living pressures are contributing to financial hardship among residential electricity customers, as reflected in rising financial assistance enrollment, persistent arrears for some, and increasing non-compliance exits.

This analysis set out to answer three key questions:

  • Are more customers at risk of disconnection?
  • Are arrears increasing among those receiving financial assistance?
  • And is tailored financial assistance enrollment growing while effectively supporting customers?

Disconnection risk has risen, with a 7.4% surge in warning notices, signaling more households struggling to pay on time. However, actual disconnections remain low, suggesting many customers resolve overdue balances before service termination.

Arrears trends show financial hardship remains a significant challenge for many, with high arrears ($1,000+) increasing by 22.5%, while overall arrears have fluctuated but not shown a sustained upward trend.

Most notably, financial assistance enrollment has increased by 6.36% overall and 15.93% since mid-2022. However, 65.4% of exits are due to non-compliance, suggesting that many customers either struggle to meet assistance program requirements or disengage from structured repayment plans.

These findings highlight growing financial strain among residential electricity customers, reinforcing the need to assess whether existing support measures are effectively helping those most at risk.

1️⃣ 7.4% increase in disconnection warning notices.
2️⃣ 22.5% increase in high arrears ($1,000+) (Debt persistence despite assistance)
3️⃣ 15.93% growth in assistance uptake since mid-2022 low (More people seeking help)
4️⃣ 65.4% of exits due to non-compliance (Many struggling to sustain assistance)