Of Australia's big four banks, the Commonwealth Bank of Australia had the highest number of customers. As of June 30, 2020, Commonwealth Bank had approximately 17 million customers, three million more than Westpac Banking Corporation. 

 Commonwealth Bank of Australia 

The Commonwealth Bank of Australia, also named CommBank, is not only the most dominant bank in Australia, but also has a presence in New Zealand, Asia, the United States, and the United Kingdom. The total assets of CommBank exceeded one billion Australian dollars in 2020 and continued to increase through to the 2021 financial year. Along with leading the banking sector in the country, CommBank was also one of the most valuable brands in Australia, just falling behind Telstra and Woolworths.

 Consumer banking   When looking at consumer banking customer satisfaction in Australia, the big four struggled to keep up with the customer-owned mutual bank, Heritage Bank. Nevertheless, Australian consumers seemed to be largely satisfied with their current banks, with less than a quarter of respondents likely to change their primary bank according to a recent survey.

The total assets of National Australia Bank (NAB) amounted to around 1.08 trillion Australian dollars as at the end of September, 2023. NAB is one of the largest four banks in Australia in terms of market capitalization, earnings and customer reach.

In the year ended September 2024, the total liabilities of National Australia Bank (NAB) amounted to just over one trillion Australian dollars. NAB was one of the largest four banks in Australia in terms of market capitalization, earnings and customer reach.

The Numenta Anomaly Benchmark (NAB) is a novel benchmark for evaluating algorithms for anomaly detection in streaming, online applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications. All of the data and code is fully open-source, with extensive documentation, and a scoreboard of anomaly detection algorithms: github.com/numenta/NAB. The full dataset is included here, but please go to the repo for details on how to evaluate anomaly detection algorithms on NAB.

NAB Data Corpus

The NAB corpus of 58 timeseries data files is designed to provide data for research in streaming anomaly detection. It is comprised of both real-world and artifical timeseries data containing labeled anomalous periods of behavior. Data are ordered, timestamped, single-valued metrics. All data files contain anomalies, unless otherwise noted.

The majority of the data is real-world from a variety of sources such as AWS server metrics, Twitter volume, advertisement clicking metrics, traffic data, and more. All data is included in the repository, with more details in the data readme. We are in the process of adding more data, and actively searching for more data. Please contact us at nab@numenta.org if you have similar data (ideally with known anomalies) that you would like to see incorporated into NAB.

The NAB version will be updated whenever new data (and corresponding labels) is added to the corpus; NAB is currently in v1.0.

Real data

• realAWSCloudwatch/

  AWS server metrics as collected by the AmazonCloudwatch service. Example metrics include CPU Utilization, Network Bytes In, and Disk Read Bytes.

• realAdExchange/

  Online advertisement clicking rates, where the metrics are cost-per-click (CPC) and cost per thousand impressions (CPM). One of the files is normal, without anomalies.

• realKnownCause/

  This is data for which we know the anomaly causes; no hand labeling.

  • ambient_temperature_system_failure.csv: The ambient temperature in an office setting.
  • cpu_utilization_asg_misconfiguration.csv: From Amazon Web Services (AWS) monitoring CPU usage – i.e. average CPU usage across a given cluster. When usage is high, AWS spins up a new machine, and uses fewer machines when usage is low.
  • ec2_request_latency_system_failure.csv: CPU usage data from a server in Amazon's East Coast datacenter. The dataset ends with complete system failure resulting from a documented failure of AWS API servers. There's an interesting story behind this data in the "http://numenta.com/blog/anomaly-of-the-week.html">Numenta blog.
  • machine_temperature_system_failure.csv: Temperature sensor data of an internal component of a large, industrial mahcine. The first anomaly is a planned shutdown of the machine. The second anomaly is difficult to detect and directly led to the third anomaly, a catastrophic failure of the machine.
  • nyc_taxi.csv: Number of NYC taxi passengers, where the five anomalies occur during the NYC marathon, Thanksgiving, Christmas, New Years day, and a snow storm. The raw data is from the NYC Taxi and Limousine Commission. The data file included here consists of aggregating the total number of taxi passengers into 30 minute buckets.
  • rogue_agent_key_hold.csv: Timing the key holds for several users of a computer, where the anomalies represent a change in the user.
  • rogue_agent_key_updown.csv: Timing the key strokes for several users of a computer, where the anomalies represent a change in the user.

• realTraffic/

  Real time traffic data from the Twin Cities Metro area in Minnesota, collected by the Minnesota Department of Transportation. Included metrics include occupancy, speed, and travel time from specific sensors.

• realTweets/

  A collection of Twitter mentions of large publicly-traded companies such as Google and IBM. The metric value represents the number of mentions for a given ticker symbol every 5 minutes.

Artificial data

• artificialNoAnomaly/

  Artifically-generated data without any anomalies.

• artificialWithAnomaly/

  Artifically-generated data with varying types of anomalies.

Acknowledgments

We encourage you to publish your results on running NAB, and share them with us at nab@numenta.org. Please cite the following publication when referring to NAB:

Lavin, Alexander and Ahmad, Subutai. "Evaluating Real-time Anomaly Detection Algorithms – the Numenta Anomaly Benchmark", Fourteenth International Conference on Machine Learning and Applications, December 2015. [PDF]

Germany Consumer Price Index (CPI): Weights: F&B: NAB: Coffee, Tea & Cocoa: Coffee & Similar data was reported at 3.280 Per 1000 in 2023. This stayed constant from the previous number of 3.280 Per 1000 for 2022. Germany Consumer Price Index (CPI): Weights: F&B: NAB: Coffee, Tea & Cocoa: Coffee & Similar data is updated yearly, averaging 3.280 Per 1000 from Dec 2020 (Median) to 2023, with 4 observations. The data reached an all-time high of 3.280 Per 1000 in 2023 and a record low of 3.280 Per 1000 in 2023. Germany Consumer Price Index (CPI): Weights: F&B: NAB: Coffee, Tea & Cocoa: Coffee & Similar data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.I032: Consumer Price Index: Weights: Annual.

Brunei Consumer Price Index (CPI): FB: NAB: CC: Coffee & Tea data was reported at 115.200 Jan2005=100 in Aug 2013. This records an increase from the previous number of 114.700 Jan2005=100 for Jul 2013. Brunei Consumer Price Index (CPI): FB: NAB: CC: Coffee & Tea data is updated monthly, averaging 107.950 Jan2005=100 from Jan 2009 (Median) to Aug 2013, with 56 observations. The data reached an all-time high of 118.100 Jan2005=100 in Jan 2012 and a record low of 100.800 Jan2005=100 in Jan 2009. Brunei Consumer Price Index (CPI): FB: NAB: CC: Coffee & Tea data remains active status in CEIC and is reported by Department of Economic Planning and Statistics, Ministry of Finance and Economy. The data is categorized under Global Database’s Brunei – Table BN.I008: Consumer Price Index: Jan 2005=100.

Italy Consumer Price Index (CPI): FN: NAB: Tea data was reported at 108.000 2010=100 in Dec 2015. This records a decrease from the previous number of 108.100 2010=100 for Nov 2015. Italy Consumer Price Index (CPI): FN: NAB: Tea data is updated monthly, averaging 92.190 2010=100 from Jan 1996 (Median) to Dec 2015, with 240 observations. The data reached an all-time high of 108.100 2010=100 in Nov 2015 and a record low of 81.760 2010=100 in Jan 1996. Italy Consumer Price Index (CPI): FN: NAB: Tea data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Italy – Table IT.I007: Consumer Price Index: 2010=100: Whole Nation.

India National Australia Bank: Return on Investments Adjusted to Cost of Funds data was reported at -11.210 % in 2018. This records a decrease from the previous number of 8.020 % for 2017. India National Australia Bank: Return on Investments Adjusted to Cost of Funds data is updated yearly, averaging 12.105 % from Mar 2013 (Median) to 2018, with 6 observations. The data reached an all-time high of 21.530 % in 2014 and a record low of -11.210 % in 2018. India National Australia Bank: Return on Investments Adjusted to Cost of Funds data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Banking Sector – Table IN.KBR031: Foreign Banks: Selected Financial Ratios: National Australia Bank.

Germany Consumer Price Index (CPI): Weights: F&B: NAB: Mineral Waters, Soft Drinks & Juices data was reported at 10.010 Per 1000 in Jul 2025. This stayed constant from the previous number of 10.010 Per 1000 for Jun 2025. Germany Consumer Price Index (CPI): Weights: F&B: NAB: Mineral Waters, Soft Drinks & Juices data is updated monthly, averaging 9.610 Per 1000 from Jan 2000 (Median) to Jul 2025, with 307 observations. The data reached an all-time high of 10.010 Per 1000 in Jul 2025 and a record low of 7.940 Per 1000 in Dec 2019. Germany Consumer Price Index (CPI): Weights: F&B: NAB: Mineral Waters, Soft Drinks & Juices data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.I031: Consumer Price Index: Weights.

Germany Consumer Price Index (CPI): 2005=100: F&B: NAB: Coffee, Tea and Cocoa data was reported at 119.400 2005=100 in Dec 2012. This records an increase from the previous number of 119.000 2005=100 for Nov 2012. Germany Consumer Price Index (CPI): 2005=100: F&B: NAB: Coffee, Tea and Cocoa data is updated monthly, averaging 103.000 2005=100 from Jan 1991 (Median) to Dec 2012, with 264 observations. The data reached an all-time high of 121.800 2005=100 in Mar 2012 and a record low of 89.900 2005=100 in May 1991. Germany Consumer Price Index (CPI): 2005=100: F&B: NAB: Coffee, Tea and Cocoa data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.I014: Consumer Price Index: by COICOP: 2005=100.

Colombia Consumer Price Index (CPI): Weights: Mid Income: FNB: NAB: Coffee, Tea & Cocoa (CTC) data was reported at 0.440 % in 2024. This stayed constant from the previous number of 0.440 % for 2023. Colombia Consumer Price Index (CPI): Weights: Mid Income: FNB: NAB: Coffee, Tea & Cocoa (CTC) data is updated yearly, averaging 0.440 % from Dec 2019 (Median) to 2024, with 6 observations. The data reached an all-time high of 0.440 % in 2024 and a record low of 0.440 % in 2024. Colombia Consumer Price Index (CPI): Weights: Mid Income: FNB: NAB: Coffee, Tea & Cocoa (CTC) data remains active status in CEIC and is reported by National Administrative Department of Statistics. The data is categorized under Global Database’s Colombia – Table CO.I014: Consumer Price Index: by Class of Good and Services: COICOP: Dec2018=100: Weights.

Brunei Consumer Price Index (CPI): Weights: FB: NAB: Coffee, Tea & Cocoa (CC) data was reported at 76.000 Per 10TH in May 2019. This stayed constant from the previous number of 76.000 Per 10TH for Apr 2019. Brunei Consumer Price Index (CPI): Weights: FB: NAB: Coffee, Tea & Cocoa (CC) data is updated monthly, averaging 76.000 Per 10TH from Aug 2013 (Median) to May 2019, with 70 observations. The data reached an all-time high of 76.000 Per 10TH in May 2019 and a record low of 76.000 Per 10TH in May 2019. Brunei Consumer Price Index (CPI): Weights: FB: NAB: Coffee, Tea & Cocoa (CC) data remains active status in CEIC and is reported by Department of Economic Planning and Statistics, Ministry of Finance and Economy. The data is categorized under Global Database’s Brunei – Table BN.I006: Consumer Price Index: Jan 2010=100: Weights.

Italy Consumer Price Index (CPI): FN: NAB: Mineral Waters & Non Alcoholic Beverages data was reported at 128.100 1995=100 in Dec 2010. This records an increase from the previous number of 127.900 1995=100 for Nov 2010. Italy Consumer Price Index (CPI): FN: NAB: Mineral Waters & Non Alcoholic Beverages data is updated monthly, averaging 118.700 1995=100 from Jan 1996 (Median) to Dec 2010, with 180 observations. The data reached an all-time high of 128.200 1995=100 in Jan 2010 and a record low of 104.300 1995=100 in Jan 1996. Italy Consumer Price Index (CPI): FN: NAB: Mineral Waters & Non Alcoholic Beverages data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Italy – Table IT.I008: Consumer Price Index: 1995=100: Whole Nation.

India National Australia Bank: Operating Expenses: Depreciation on Bank's Property data was reported at 3.455 INR mn in 2018. This records a decrease from the previous number of 13.296 INR mn for 2017. India National Australia Bank: Operating Expenses: Depreciation on Bank's Property data is updated yearly, averaging 9.608 INR mn from Mar 2012 (Median) to 2018, with 7 observations. The data reached an all-time high of 16.440 INR mn in 2015 and a record low of 1.635 INR mn in 2012. India National Australia Bank: Operating Expenses: Depreciation on Bank's Property data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Banking Sector – Table IN.KBQ031: Foreign Banks: Income Statements: National Australia Bank.

India National Australia Bank: Profit or Loss data was reported at 98.919 INR mn in 2018. This records a decrease from the previous number of 156.087 INR mn for 2017. India National Australia Bank: Profit or Loss data is updated yearly, averaging 116.261 INR mn from Mar 2012 (Median) to 2018, with 7 observations. The data reached an all-time high of 156.087 INR mn in 2017 and a record low of -88.207 INR mn in 2013. India National Australia Bank: Profit or Loss data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Banking Sector – Table IN.KBQ031: Foreign Banks: Income Statements: National Australia Bank.

According to a survey conducted in 2020, Australia’s banking customers were overall satisfied with their banks. During the survey period, Heritage Bank received the highest overall customer statisfaction rating at 872 out of 1,000. Comparatively, the satisfaction ratings of the largest four banks in the country, ANZ, Commonwealth Bank, Westpac, and NAB, were all lower than 780.

Consumer banking preferences

Despite the slightly lower satisfaction ratings, in a survey about consumers considering taking out a new banking product, the big four banks in Australia dominated. These banks have historically been at the forefront of Australia’s banking and finance scene, attracting new customers due to their reputation, robustness, and repertoire of products and services. Banks in Australia, large and small, have had to diversify their offerings to remain competitive with changing population preferences. A generational comparison of mobile banking and branch banking usage in Australia showed that younger generations were much more willing to use mobile banking services over in-house banking.

COVID-19 and the future of banking

The coronavirus pandemic has certainly made its impact on the Australian banking industry. The big four banks have been forced to react to the country’s biggest economic contraction in a century. The market cap of these banks seemed to have been seriously impacted by the economic uncertainty in 2020. Furthermore, large banks were not the only financial institutions affected. Indeed, the share of financial and insurance businesses anticipating adverse impacts due to the coronavirus in Australia was considerable.

India National Australia Bank: Assets: Advances data was reported at 1,750.000 INR mn in 2018. This records a decrease from the previous number of 2,422.380 INR mn for 2017. India National Australia Bank: Assets: Advances data is updated yearly, averaging 1,868.997 INR mn from Mar 2013 (Median) to 2018, with 6 observations. The data reached an all-time high of 3,791.342 INR mn in 2014 and a record low of 1,030.771 INR mn in 2016. India National Australia Bank: Assets: Advances data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Banking Sector – Table IN.KBP028: Foreign Banks: Assets and Liabilities: National Australia Bank.

Germany Consumer Price Index (CPI): 2000=100: F&B: Non Alcoholic Beverages (NAB) data was reported at 108.900 2000=100 in Dec 2007. This records an increase from the previous number of 108.100 2000=100 for Nov 2007. Germany Consumer Price Index (CPI): 2000=100: F&B: Non Alcoholic Beverages (NAB) data is updated monthly, averaging 100.000 2000=100 from Jan 1991 (Median) to Dec 2007, with 204 observations. The data reached an all-time high of 108.900 2000=100 in Dec 2007 and a record low of 89.200 2000=100 in Mar 1991. Germany Consumer Price Index (CPI): 2000=100: F&B: Non Alcoholic Beverages (NAB) data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.I016: Consumer Price Index: by COICOP: 2000=100.

India National Australia Bank: Financial Ratio: Capital Adequacy Ratio data was reported at 169.700 % in 2018. This records a decrease from the previous number of 228.150 % for 2017. India National Australia Bank: Financial Ratio: Capital Adequacy Ratio data is updated yearly, averaging 225.170 % from Mar 2012 (Median) to 2018, with 7 observations. The data reached an all-time high of 423.740 % in 2012 and a record low of 96.080 % in 2013. India National Australia Bank: Financial Ratio: Capital Adequacy Ratio data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Banking Sector – Table IN.KBR031: Foreign Banks: Selected Financial Ratios: National Australia Bank.

Germany Consumer Price Index (CPI): 2010=100: F&B: Non Alcoholic Beverages (NAB) data was reported at 116.300 2010=100 in 2018. This records an increase from the previous number of 114.100 2010=100 for 2017. Germany Consumer Price Index (CPI): 2010=100: F&B: Non Alcoholic Beverages (NAB) data is updated yearly, averaging 93.750 2010=100 from Dec 1991 (Median) to 2018, with 28 observations. The data reached an all-time high of 116.300 2010=100 in 2018 and a record low of 82.200 2010=100 in 1991. Germany Consumer Price Index (CPI): 2010=100: F&B: Non Alcoholic Beverages (NAB) data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.I013: Consumer Price Index: by COICOP: 2010=100: Annual. Rebased from 2010=100 to 2015=100 Replacement series ID: 412819437