This case study included information on a sample of fifty credit card accounts. This information, table one, included household size, annual income, and the amount charged to the account. Scatter plots of the data were produced. Figure one shows household size vs. amount charged. This graph shows that the positive linear relationship of the data is somewhat strong. The r squared is 0.56, analyzing the graph there is a correlation of household size to amount charged, but there is a range per household size. Figure two shows annual income vs. amount charged. The linear relationship of the data is weak, with an r squared of 0.398. Though a positive linear relationship is present. The last scatter plot, Figure 3, shows household …show more content…
Spending habits would show us where most of their money is going. Who is making only large purchases with their cards and who is using their cards for daily expenses. The average unpaid monthly balance would help determine who is spending more than they can pay back, and who is using their card and then paying it all off at once. This could be used for interest rate analysis. Lower rates for people paying it all off at once to try to coerce them to make larger purchases on their cards and collect interest payments as well as the processing fees from the companies. Regional cost of living adjustment on the data would help determine the actual value of their annual income and purchases. This would take some of the error out of the data that is collected. For example $1 in California might only be worth $0.93 in Indiana, this isn 't very much but when multiplied into the thousands or tens of thousands in grows very large. Age would also help in determining spending habits. Developing families tend to spend a lot more money on large purchases like appliances and furniture. Lowering their interest rates could coerce them into making more purchases and longer term balances on their cards. Knowing what other outlying debts customers have could be helpful in determining high-risk customers. Along with past credit history this could be helpful in determining customers to reject. There are many factors that affect the amount people charge
Startling numbers from one study show that in the United States, 140 million credit card holders have 1.2 billion retail and credit cards (Lynott, 2008). Outstanding balances of
Credit cards have become increasingly popular world-wide, making it easier to buy now and pay later but are they actually helping or hindering someone’s credit? “Maxed Out” by James D. Scurlock demonstrates how credit cards can hurt someone’s credit, while “Why Won’t Anyone give Me a Credit Card” by Kevin O’Donnell demonstrates how someone may have financial stability to pay off a credit card, but still be consistently denied one by the credit card companies. Owning credit cards is not the problem; the problem is being irresponsible with it.
A consumer may decide on a whim to take a gamble and purchase a four thousand dollar surround sound system only to find out that he cannot cover his bill at the end of the month. This type of spending creates debt and has a bad effect on your credit report. Consumers must learn to control this type of spending and manage their debt properly in order to keep a good credit report and stay ahead of their payments.
Attitudes about spending changed drastically. At this point, more people had access to credit cards because credit card companies stopped limiting their customer base to the wealthy, and began issuing cards to people with moderate to low incomes (Garon, 2012, CNN World). This gave Americans a way to purchase goods and services immediately, even if they didn’t have the cash on hand. The seven to eight percent savings rate maintained in the United States from the 1960s to the 1980s plummeted to less than two percent, and remained so until the first decade of the 21st century (Melicher & Norton, 2014, p. 168).
5. Excessive spending habits: Not everyone is budget savvy. Some individuals let their wants or desires drive their spending habits by purchasing items and services that are not a necessity for basic living. Credit card spending can help fuel this type of habit. Too much credit card debt could ultimately change the borrower’s ability to repay for their mortgage and other liabilities.
Not only for those seeking to retire, the business motivated economy has transfigured how one must live in order to live comfortably. Building credit through credit cards is often perceived to be the only way in order for a buyer to appear credible. Yet in the quest for the optimal credit score people enter into debt. Considering and evaluating the risks and benefits to credit cards may contribute to opinions towards those flimsy pieces of plastic.
6. Based on findings from questions 1-5 we can conclude that the relationship between credit balance and size is linear with positive correlation. That is model is useful for predicting the credit balance using the variable size as a independent variable.
I grew up in a household where personal finances and building good credit was not the main topic of discussion at the dinner table. I was well over 21 years of age when I really started learning anything about credit and how to use my credit score to my advantage. To be honest, my first real encounter with being taught about personal finances and credit came from attending a network marketing meeting. Even though I was invited because of a business opportunity, I learned so much listening to this guy talk about regaining your wealth through your own personal finances.
It is imperative that young adults comprehend the facets of obtaining and maintaining proper credit in order to sustain a sound credit history. For example, the most widely used credit score is Fair Isaac Corp.'s FICO score, which ranges from 300 to 850. A FICO score of 760 or higher reveals an individual’s respectable borrowing power, for even a recently reported late payment can have a substantial effect on a credit score (Holmes). In addition, young adults can learn the importance of securing proper credit and increase their attractiveness in lender’s eyes by aiming to use less than 20% of one’s available credit (“Get”). Since lenders pay close attention to the amount owed on credit cards relative to the limits provided, lenders are able
Pre-retirees with medical debt were expected to accumulate a lower amount of financial resources as compared to pre-retirees not burdened with medical debt. However, the payment of installment loans by the household is not a significant predictor of financial assets in the model. Moreover, the payment on the first line of credit was not a statistically significant predictor of financial assets for pre-retirees. Conversely, vehicle payments and consumer loan payments are statistically significant predictors negatively impacting financial assets. These types of debts consist of items that are consumed quickly or that consistently depreciate over a short period of time. With easy access to these forms of credit, a significant number of pre-retirees are servicing credit card debt and paying
On a periodic basis, the Federal reserve releases key statistics related to credit card debt in America. With almost 2,000,000,000 credit cards in use while in the hands of almost 200,000,000 individual credit card holders, there is no denying the popularity of these little pieces of plastic. Through May of 2015, Americans were responsible for $901 billion in credit
“The average American owns 3.5 credit cards and $15,799 in credit card debt… totaling consumer debt of $2.43 trillion in the USA alone.” (Beckner). Debt forces many people into depression and worrying lives. People struggle to discover happiness through financing goods, but struggle even more to find a way out of debt. Through consumerism, people lose their finances in department stores, car dealerships, and much more. Most of the possessions people buy with credit cards become impractical within a few months. The void they search for is never really filled. Consumerism is just a way to get the economy going, without thinking of a person’s individual finance
As far as credit cards are concerned three good reasons for obtaining one are; they aid you in establishing your credit score as well as history. Credit cards are also great if there is an emergency that requires immediate financial action and assistance. Lastly, credit cards offer many benefits such as cash back, rewards, and discounts. The negative effects of credit cards is that they often come with high fees and interest rates. One other negative drawback to obtaining a credit card is that individuals can get themselves into
The advantages of debit card versus credit cards used by young adults are debit cards will not allow you to mismanage, overspend or go into debt. The most common explanation for credit card debt for people under the age of 25. “Demographic and credit trends show that young people, and in particular students, may be the next segment of credit users that will face difficult financial times. “In the United States, there are 19.1 million students who are attending colleges and universities (US Department of Education 2009).” They account for approximately 6% of a population of 308 million people (US Census Bureau 2011). On average, students possess 4.6 credit cards (SallieMae 2009). They also owe more on their credit cards than they did just a few years ago; in 2004, students owed, on average, $2,900 on credit cards whereas in 2009 this figure soared by 78% to $4,100 (SallieMae 2009). Moreover, young consumers account for the second largest rate of bankruptcy in the United States (Sullivan, Thorne, and Warren 2001). Together, these figures suggest that young adult consumers in America spend more with their credit cards than they should. In addition, research shows that credit card debt is associated with financial stress (Grable and Joo 2006) as well as poor academic achievement (Pinto, Parente, and Palmer 2001). The desire to use credit as a form of payment but with no steady income available to repay the credit line. For
Descriptive research is undertaken for study. Data collection was done from the Credit rating reports & Microfinance sector reports.