Skip to main content

Paytm gets banned for these 4 reasons.

Paytm gets banned for these 4 reasons.



With the recent order of RBI many features like Paytm bank, Paytm wallet, and the fast tag will be stopped from 29th Feb but what makes RBI take this huge step knowingly that Paytm plays a major role in Indian digital payment with 30% of market share. Below are those 4 reasons that have been leaked by an insider either from Paytm or a government organization - 


1)Didn't do KYC of lakhs of customers - RBI found out Paytm didn't do KYC of lakhs of customers and opened their savings account which is a direct violation of RBI guidelines.


2)Thousands of accounts opened with single PAN numbers - RBI found out that thousands of savings accounts get opened with a single PAN number which is scary for many customers as maybe their data gets used to open other accounts also which is a big crime.


3)Paytm bank shared details of customers with parent company One97 communication - As per RBI guidelines if you are a Payment bank then you should not share your data with any other parent company, but Paytm payment bank shared its data with its parent company One97 communication.


4)Many customers' account balance breaches above-allowed limit - As per RBI guidelines if you are a payment bank then you should not allow your customers to deposit amounts greater than a certain limit like 1lakh or 2 lakhs, but Paytm allowed many of its customers to deposit and store amounts much more than that. Read more.







Labels:

Comments

Post a Comment

Popular posts from this blog

Free Udemy Course for PowerBI

Free Udemy Course for PowerBI Get This Course for Free. Create beautiful dashboards instead of boring spreadsheets and slides. Make an involving presentation based on an interactive visual story. Create visualizations without programming skills. Learn some interesting tips for simply working with Power BI. Get this course for free. Basic Data Connection: Students will learn how to connect Power BI to simple data sources, gaining an understanding of basic data import techniques. Introductory Data Cleaning: Learners will be introduced to the Power Query Editor for basic data cleaning tasks, such as removing duplicates and filtering data. Fundamentals of Data Modeling: Participants will learn the basics of creating data models in Power BI, including simple relationships between tables. Basic DAX Formulas and Visualizations: Students will acquire foundational skills in writing simple DAX formulas and creating basic reports. Understanding the overall life cycle of building a Power BI Report
Post a Comment
Read more

PowerBI Course Under $5.

PowerBI Course Under $5. PowerBI Course. What is PowerBI ? Power BI is a robust business analytics tool from Microsoft, crafted to convert raw data into compelling, interactive insights. It boasts an array of features such as data connectivity, preparation, modeling, visualization, and collaboration tools. Power BI empowers users to craft interactive dashboards, reports, and visualizations, enabling quick and effective business insights. Use of PowerBI - The value of Power BI stems from its capacity to make data analytics accessible, allowing individuals at every organizational level to base decisions on data. Its intuitive interface and accessible tools help organizations reveal patterns, trends, and connections in their data, fostering better decision-making, operational efficiency, and superior business results. Additionally, Power BI's compatibility with other Microsoft offerings and cloud services renders it an essential asset for businesses aiming to remain competitive in the
Post a Comment
Read more

Importing Data into Power BI: Best Practices and Tips

Importing Data into Power BI: Best Practices and Tips Join My PowerBI Group. Importing data into Power BI is a crucial step in creating reports and dashboards. Here are some best practices and tips to enhance the process: Understand Your Data Sources: Get familiar with the structure, format, and quality of your data sources. Comprehend the relationships between different data tables and the business context of the data. Data Preparation: Clean and preprocess your data before importing it into Power BI. This includes removing duplicates, addressing missing values, standardizing formats, and converting data types. Use Direct Query When Appropriate: For large or frequently updated datasets that may surpass Power BI's data model size limits, consider using Direct Query mode. This mode enables real-time queries to the data source, ensuring reports are current. Optimize Query Performance: Improve data retrieval queries to reduce load times and enhance performance. Employ efficient SQ
Post a Comment
Read more