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Keyword density helper – This tool comes with a built-in keyword density helper in some ways similar to the likes of SurferSEO or MarketMuse the difference being, ours is free! This feature shows the user the frequency of single or two word keywords in a document, meaning you can easily compare an article you have written against a competitor to see the major differences in keyword densities. This is especially useful for SEO’s who are looking to optimize their blog content for search engines and improve the blog’s visibility.
You can also easily compare text by copying and pasting it into each field, as demonstrated below.
Ease of use
Our text compare tool is created with the user in mind, it is designed to be accessible to everyone. Our tool allows users to upload files or enter a URL to extract text, this along with the lightweight design ensures a seamless experience. The interface is simple and straightforward, making it easy for users to compare text and detect the diff.
Multiple text file format support
Our tool provides support for a variety of different text files and microsoft word formats including pdf file, .docx, .odt, .doc, and .txt, giving users the ability to compare text from different sources with ease. This makes it a great solution for students, bloggers, and publishers who are looking for file comparison in different formats.
Protects intellectual property
Our text comparison tool helps you protect your intellectual property and helps prevent plagiarism. This tool provides an accurate comparison of texts, making it easy to ensure that your work is original and not copied from other sources. Our tool is a valuable resource for anyone looking to maintain the originality of their content.
User Data Privacy
Our text compare tool is secure and protects user data privacy. No data is ever saved to the tool, the users’ text is only scanned and pasted into the tool’s text area. This makes certain that users can use our tool with confidence, knowing their data is safe and secure.
Compatibility
Our text comparison tool is designed to work seamlessly across all size devices, ensuring maximum compatibility no matter your screen size. Whether you are using a large desktop monitor, a small laptop, a tablet or a smartphone, this tool adjusts to your screen size. This means that users can compare texts and detect the diff anywhere without the need for specialized hardware or software. This level of accessibility makes it an ideal solution for students or bloggers who value the originality of their work and need to compare text online anywhere at any time.
Artificial Intelligence (AI) has increasingly become an integral component of numerous industries, profoundly transforming the landscape of customer interactions, reviews, and feedback mechanisms.
In the financial sector, particularly within Canada's "Big 5" banks — BMO, CIBC, RBC, Scotiabank, and TD — understanding the prevalence and implications of AI customer reviews has become critically important.
Customer reviews play a vital role in shaping public perception, influencing customer decisions, and guiding service improvements. However, the emergence of AI-generated content poses potential challenges regarding authenticity, reliability, and consumer trust.
This study investigates the rates of AI-generated customer reviews from 2018 to 2025 for each of these major Canadian banks.
By quantifying the extent of AI-generated content, we aim to illuminate patterns and trends that may indicate the degree to which these technologies are influencing online review landscapes within the banking sector.
Complementing this analysis, sentiment analysis is employed to evaluate how reviews compare emotionally and tonally across the time period studied.
This dual analytical approach will offer comprehensive insights into:
The findings of this study will help banks, regulators, and customers navigate the evolving complexities introduced by AI, ultimately fostering a more informed and reliable digital consumer feedback ecosystem.
We’ve included a quick reference chart below of the comparative AI review rates for each of these banks in 2025:
The analysis of AI-generated review rates reveals a pronounced shift in customer feedback for Canada’s Big 5 banks from 2018 to 2025.
Beginning uniformly at 0.0% in 2018, indicating no detectable AI-generated content across BMO, CIBC, RBC, Scotiabank, and TD, all institutions experienced emerging and accelerating rates of AI-generated reviews by 2025.
This overarching trend underscores the rapid integration of automated review generation within digital banking ecosystems.
BMO exhibited the most dramatic change, with its AI-generated review rate climbing from 0.0% in 2018 to 13.1% in 2025:
RBC and Scotiabank also entered the double-digit territory by 2025, rising to 11.8% and 11.1% respectively — up 11.8 and 11.1 percentage points from their 2018 baselines.
Meanwhile, CIBC and TD showed more moderate yet still significant increases, reaching 9.0% and 9.7% AI-generated review rates by 2025, representing 9.0 and 9.7 percentage-point gains, respectively.
Although these figures (for CIBC and TD) are lower than those of BMO, RBC, and Scotiabank, they nonetheless reflect a clear upward trend and suggest that adoption of AI-driven reviews is becoming commonplace across the sector.
The variation in growth rates across banks may reflect differences in:
Collectively, the jump from 0.0% in 2018 to rates approaching or exceeding 10% by 2025 signals a transformative shift in how customer feedback is generated and perceived.
Overall, these findings highlight critical implications for authenticity, consumer trust, and regulatory oversight as AI continues to reshape the banking review landscape.
Sentiment analysis of customer reviews from 2018 to 2025 for Canada's Big 5 banks revealed predominantly negative sentiments, with most sentiment scores consistently remaining between -0.16 and -0.4 throughout the eight-year period.
This negative sentiment trend may indicate:
A notable exception occurred in 2020 for RBC, where sentiment scores increased to approximately +0.34, significantly deviating from the otherwise negative baseline observed for all banks.
This positive sentiment shift in RBC's customer reviews aligns closely with the timing of the COVID-19 pandemic.
It could potentially be reflective of favorable customer reactions to RBC's pandemic-related initiatives, such as:
Aside from this temporary positive deviation observed in RBC’s 2020 data, no similar positive sentiment shifts were observed for the other banks during the study period.
The overall sustained negative sentiment highlights a consistent level of critical consumer perspectives, potentially emphasizing areas for improvement in customer experience, satisfaction, and institutional reputation management.
These findings underscore the importance of monitoring sentiment trends over time, especially in response to external, significant events.
In conclusion, this study highlights both the challenges and opportunities that rising levels of AI-generated content and customer sentiment (which this study found to be predominantly negative) pose for Canada's banking sector.
Ongoing negative sentiment underscores the critical areas where banks must focus their improvement efforts.
Simultaneously, RBC's positive sentiment experience during the COVID-19 pandemic may reflect the impact and influence of significant external events on consumer satisfaction.
Banks that effectively address AI-generated content in reviews as well as consumer sentiment as part of their operational and strategic frameworks are likely to strengthen customer loyalty and overall reputation in a competitive financial services landscape.
Do you have concerns over whether a post or review you’re reading might be AI-generated? Use the Originality.ai AI detector to find out.
Read more about the impact of AI on online platforms:
This study analyzed AI-generated customer reviews of Canada’s Big 5 banks — BMO, CIBC, RBC, Scotiabank, and TD — using web scraping methods from prominent review platforms such as ConsumerAffairs and Trustpilot.
Reviews were collected via Python scripts. Specifically, the BeautifulSoup and Requests libraries facilitated automated retrieval of review content and associated metadata (dates, review texts) from these platforms. This data was then structured and saved into CSV files for subsequent analysis.
Reviews with 50+ words were analyzed using the Originality.ai API to assess AI-generation likelihood. A Python script automated API calls, handled errors, and saved results (review content, date, bank, AI scores/classification) after every 500 reviews.
This structured process ensured accurate detection and trend analysis of AI-generated reviews from 2018 to 2025.
No, that’s one of the benefits, only fill out the areas which you think will be relevant to the prompts you require.
When making the tool we had to make each prompt as general as possible to be able to include every kind of input. Not to worry though ChatGPT is smart and will still understand the prompt.
Originality.ai did a fantastic job on all three prompts, precisely detecting them as AI-written. Additionally, after I checked with actual human-written textual content, it did determine it as 100% human-generated, which is important.
Vahan Petrosyan
searchenginejournal.com
I use this tool most frequently to check for AI content personally. My most frequent use-case is checking content submitted by freelance writers we work with for AI and plagiarism.
Tom Demers
searchengineland.com
After extensive research and testing, we determined Originality.ai to be the most accurate technology.
Rock Content Team
rockcontent.com
Jon Gillham, Founder of Originality.ai came up with a tool to detect whether the content is written by humans or AI tools. It’s built on such technology that can specifically detect content by ChatGPT-3 — by giving you a spam score of 0-100, with an accuracy of 94%.
Felix Rose-Collins
ranktracker.com
ChatGPT lacks empathy and originality. It’s also recognized as AI-generated content most of the time by plagiarism and AI detectors like Originality.ai
Ashley Stahl
forbes.com
Originality.ai Do give them a shot!
Sri Krishna
venturebeat.com
For web publishers, Originality.ai will enable you to scan your content seamlessly, see who has checked it previously, and detect if an AI-powered tool was implored.
Industry Trends
analyticsinsight.net
Tools for conducting a plagiarism check between two documents online are important as it helps to ensure the originality and authenticity of written work. Plagiarism undermines the value of professional and educational institutions, as well as the integrity of the authors who write articles. By checking for plagiarism, you can ensure the work that you produce is original or properly attributed to the original author. This helps prevent the distribution of copied and misrepresented information.
Text comparison is the process of taking two or more pieces of text and comparing them to see if there are any similarities, differences and/or plagiarism. The objective of a text comparison is to see if one of the texts has been copied or paraphrased from another text. This text compare tool for plagiarism check between two documents has been built to help you streamline that process by finding the discrepancies with ease.
Text comparison tools work by analyzing and comparing the contents of two or more text documents to find similarities and differences between them. This is typically done by breaking the texts down into smaller units such as sentences or phrases, and then calculating a similarity score based on the number of identical or nearly identical units. The comparison may be based on the exact wording of the text, or it may take into account synonyms and other variations in language. The results of the comparison are usually presented in the form of a report or visual representation, highlighting the similarities and differences between the texts.
String comparison is a fundamental operation in text comparison tools that involves comparing two sequences of characters to determine if they are identical or not. This comparison can be done at the character level or at a higher level, such as the word or sentence level.
The most basic form of string comparison is the equality test, where the two strings are compared character by character and a Boolean result indicating whether they are equal or not is returned. More sophisticated string comparison algorithms use heuristics and statistical models to determine the similarity between two strings, even if they are not exactly the same. These algorithms often use techniques such as edit distance, which measures the minimum number of operations (such as insertions, deletions, and substitutions) required to transform one string into another.
Another common technique for string comparison is n-gram analysis, where the strings are divided into overlapping sequences of characters (n-grams) and the frequency of each n-gram is compared between the two strings. This allows for a more nuanced comparison that takes into account partial similarities, rather than just exact matches.
String comparison is a crucial component of text comparison tools, as it forms the basis for determining the similarities and differences between texts. The results of the string comparison can then be used to generate a report or visual representation of the similarities and differences between the texts.
Syntax highlighting is a feature of text editors and integrated development environments (IDEs) that helps to visually distinguish different elements of a code or markup language. It does this by coloring different elements of the code, such as keywords, variables, functions, and operators, based on a predefined set of rules.
The purpose of syntax highlighting is to make the code easier to read and understand, by drawing attention to the different elements and their structure. For example, keywords may be colored in a different hue to emphasize their importance, while comments or strings may be colored differently to distinguish them from the code itself. This helps to make the code more readable, reducing the cognitive load of the reader and making it easier to identify potential syntax errors.
With our tool it’s easy, just enter or upload some text, click on the button “Compare text” and the tool will automatically display the diff between the two texts.
Using text comparison tools is much easier, more efficient, and more reliable than proofreading a piece of text by hand. Eliminate the risk of human error by using a tool to detect and display the text difference within seconds.
We have support for the file extensions .pdf, .docx, .odt, .doc and .txt. You can also enter your text or copy and paste text to compare.
There is never any data saved by the tool, when you hit “Upload” we are just scanning the text and pasting it into our text area so with our text compare tool, no data ever enters our servers.
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This table below shows a heat map of features on other sites compared to ours as you can see we almost have greens across the board!
We believe that it is crucial for AI content detectors reported accuracy to be open, transparent, and accountable. The reality is, each person seeking AI-detection services deserves to know which detector is the most accurate for their specific use case.
