Explore the top 7 online banking KPIs

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Introduction

Run a more efficient online bank by tracking online banking key performance indicators (KPIs). It is important for banks to measure KPIs in order to make informed business decisions, reduce risk and evaluate their performance. Here, we discuss the top seven key performance metrics in online banking, how to track and calculate them, and dive into some best practices.

The seven main online banking KPIs are:

  • Net interest margin
  • Adoption rate
  • Loan/deposit ratio
  • Fraud detection rate
  • Customer retention rate
  • Average cost per acquisition
  • Total operating expenses per employee

Net interest margin

Definition

Net interest margin (NIM) is a bank performance metric that measures the difference between interest income earned on a bank’s investments and interest expense incurred on its liabilities. It is an indication of a bank’s ability to take advantage of its interest rate risk.

Benefits of Tracking

NIM is an important indicator of a bank’s financial health and profitability. It also helps identify potential areas for improvement and gives a better understanding of the bank’s competitive position in the market.

  • It provides an overall assessment of the bank’s ability to generate income from its investments.
  • It can help identify areas of opportunity to improve bank performance.
  • It can provide a benchmark against which to compare the bank’s performance to its peers in the industry.

Industry Benchmarks

The average NIM for banks in the United States was 2.80% in 2019. The average NIM for large banks was 3.09%, while the average NIM for small banks was 2.75%.

How to calculate

NIM is calculated by dividing net interest income (NII) by total interest assets (TEA). The formula is:

Nim=(nii/iea)*100

Calculation example

For example, if a bank has net interest income of 0 million and total interest assets of billion, the NIM would be 10%:

NIM = (100 million dollars / 1 b) * 100 = 10%

Tips and Tricks for KPIs

  • Focus on increasing net interest income by increasing interest assets, as this will lead to a higher NIM.
  • Monitor changes in the industry average NIM, as this can help identify opportunities for improvement.
  • Analyze the impact of different interest rate scenarios on the bank’s NIM.
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Adoption rate

Definition

Adoption rate is the percentage of users who have registered and/or activated an online banking account. It is a key performance indicator (KPI) that helps measure the success of an online banking platform.

Benefits of Tracking

  • It helps in understanding user engagement levels with the online banking platform.
  • It helps measure the effectiveness of marketing campaigns and user onboarding.
  • It helps identify user experience issues and identify areas for improvement.

Industry Benchmarks

The average adoption rate for online banking is estimated at around 40-50%. The actual rate varies of course depending on the size of the institution and the type of users.

How to calculate

The adoption rate can be calculated using the following formula:

Adoption rate = (number of users who have registered and/or activated an account / total number of users) × 100

Calculation example

For example, if the total number of users is 1000 and 500 of them have registered and/or activated their online banking account, the adoption rate would be 50%.

Adoption rate = (500/1000) × 100 = 50%

Tips and tricks

  • Track adoption rate over time to track progress.
  • Compare the adoption rate with industry benchmarks.
  • Analyze data to identify areas for improvement.

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Loan/deposit ratio

Definition

The Loans to Deposits Ratio (LDR) is a financial ratio that measures the amount of money lent to the amount of money it has taken as deposits. This ratio measures how efficiently a bank uses its deposits to generate loans and is often used as an indication of a bank’s financial health.

Benefits of Tracking

Tracking the loan to deposit ratio is an important tool for bank managers as it can help them assess the risk of the institution and make better lending decisions. Tracking this metric can also help a bank identify areas where it is not using its deposits effectively and make adjustments accordingly.

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Industry Benchmarks

Generally, a healthy loan to deposit ratio should not exceed 1:1. This means that the amount of money loaned should not exceed the amount of money considered deposits. A ratio that is too high could indicate that the bank is taking on too much risk and could lead to financial difficulties.

How to calculate

The loan to deposit ratio is calculated by dividing total loans outstanding by total deposits.

LDR = total loans / total deposits

Calculation example

For example, if a bank has 0 million in total loans outstanding and 0 million in total deposits, its loan-to-deposit ratio would be 0.5.

LDR = 0 million / 0 million = 0.5

Tips and tricks

  • A healthy loan to deposit ratio should not exceed 1:1.
  • Monitoring the loan-to-deposit ratio can help a bank identify areas where it is not using its deposits effectively.
  • The loan to deposit ratio can be used as an indication of a bank’s financial health.
  • It is important to remember that the loan-to-deposit ratio is just one of many metrics that should be monitored to gauge a bank’s financial health.

Fraud detection rate

Definition

Fraud detection rate is a KPI metric that measures the rate of successful fraud prevention. It is calculated as the percentage of fraud attempts that are successfully detected and prevented. This metric helps identify the effectiveness of a bank’s fraud prevention system.

Benefits of Tracking

Monitoring the fraud detection rate helps banks identify and improve weak points in their fraud prevention systems. It also helps banks identify fraud trends and adjust their systems accordingly. Additionally, tracking this metric can help banks reduce fraud losses.

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Industry Benchmarks

The industry benchmark for fraud detection rate is typically around 90%. Banks should strive to meet this benchmark to ensure that their fraud prevention systems are up to date and effective.

How to calculate

The formula for calculating the fraud detection rate is:

Fraud detection rate = (number of detected frauds / total number of fraud attempts) x 100

Calculation example

For example, if a bank detects 10 fraud attempts in a month and successfully prevents 8, the fraud detection rate is:

Fraud detection rate = (8/10) x 100 = 80%

Tips and tricks

  • Banks should regularly review their fraud prevention systems to ensure they are up to date and effective.
  • Banks should also use analytics and data to identify any fraud trends and adjust their systems accordingly.
  • Banks can also use machine learning and AI technologies to further improve their fraud detection systems.

Customer retention rate

Definition

Customer retention rate (CRR) is a metric used to measure the number of customers who remain loyal to a business over a certain period of time. It focuses on the percentage of customers who do not undress or leave the business, comparing the number of customers at the start of the period to the number at the end.

Benefits of Tracking

  • Identifies customer loyalty trends and indicates which customers are most likely to stay.
  • Helps predict customer behavior and identify any issues with the customer experience.
  • Provides insight into customer satisfaction and helps develop better customer retention strategies.
  • Enables businesses to identify gaps in customer service and make necessary adjustments.

Industry Benchmarks

The average customer retention rate for online banks is around 70%. However, this may vary depending on the size of the bank, the type of services offered and the clientele.

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How to calculate

The formula for calculating customer retention rate is:

Crr = ((ce – cn) / cs) x 100

Or:

  • CE = number of customers at the end of the period
  • CN = number of new customers acquired during the period
  • Cs = number of customers at the beginning of the period

Calculation example

For example, if a bank had 1000 customers at the start of the period and gained 100 new customers during the period, but 1100 customers at the end, the customer retention rate would be calculated as follows:

CRR = ((1100 – 100) / 1000) x 100 = 90%

Tips and tricks

  • Better analyze customer data to better understand customer behavior.
  • Focus on customer experience and take high quality service.
  • Engage customers through personalized marketing campaigns.
  • Encourage customer feedback and use it to improve services.

Average cost per acquisition

Definition

Average cost per acquisition (CPA) is a key performance indicator (KPI) that measures the average amount spent to acquire a customer or user for a product or service.

Benefits of Tracking

Tracking the average cost per acquisition helps online banks understand the effectiveness of their marketing efforts. By monitoring this metric, online banks can see which campaigns are generating the most customers or users for the lowest cost.

Additionally, tracking this metric can help online banks optimize their spend by understanding which campaigns are most profitable and which need improvement.

Industry Benchmarks

The average cost per acquisition varies greatly from time to time and depends on factors such as the type of product or service being offered and the target market. Generally, online banks should aim for an average cost per acquisition below the industry average.

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How to calculate

The formula to calculate the average cost per acquisition is:

CPA = total cost of acquisition / number of customers acquired

Calculation example

For example, let’s say an online bank spends ,000 on a marketing campaign and acquires 100 new customers. The average cost per acquisition would be 0:

CPA = ,000 / 100 = 0

Tips and Tricks for KPIs

  • Track average cost per acquisition over time to identify trends and areas for improvement.
  • Compare your average cost per acquisition to industry averages to make sure you’re on the right track.
  • Run experiments to test different strategies and tactics to reduce the average cost per acquisition.

Total operating expenses per employee

Definition

Total operating expenses per employee (Tope) is a KPI that measures the amount of money an online bank spends to operate for an employee. It is calculated by dividing the total operating expenses by the total number of employees. This KPI can help online banks better understand their cost structure and identify potential areas for cost savings.

Benefits of Tracking

Tracking total operating expenses per employee is beneficial for online banks as it can provide an accurate picture of the bank’s cost structure. This KPI can help online banks identify areas for cost savings and make more informed decisions about their operations. Additionally, this KPI can help banks understand how their costs compare to industry benchmarks.

Industry Benchmarks

Industry benchmarks for total operating expenses per employee vary by bank size and type. Generally, large banks have a higher tope than small banks. Also, some types of banks, such as investment banks or private banks, may have a higher tope than traditional banks.

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How to calculate

The formula for calculating total operating expenses per employee is as follows:

Tope = total operating expense / total number of employees

Calculation example

For example, if a bank has total operating expenses of ,000,000 and a total of 100 employees, the total operating expense per employee would be ,000.

Tope = ,000,000 / 100 = ,000

Tips and tricks

  • It’s important to track total operating expenses per employee over time to identify areas of potential savings.
  • Compare total operating expenses per employee to industry benchmarks to get an accurate picture of the bank’s cost structure.
  • Monitor total operating expenses per employee on a monthly basis to ensure costs are in line with bank expectations.

Conclusion

The success of an online bank depends on how well it tracks, measures and understands its key performance indicators. By calculating and tracking the seven KPIs discussed, online banks will gain valuable insight into the efficiency of their business and use the information to make informed decisions about their banking operations.

Adopting the correct KPIs, monitoring their performance regularly and interpreting their data accordingly is essential for online banks to remain successful and maximize their output.

  • Home
  • Net interest margin
  • Adoption rate
  • Loan/deposit ratio
  • Fraud detection rate
  • Customer retention rate
  • Average cost per acquisition
  • Total operating expenses per employee