Secret Credit Scores Lenders Are Using
Last Updated: September 26, 2017
Credit scores can predict your ability to pay back debts, but new scoring models purport to predict your behavior beyond creditworthiness. Similar to credit scores, these new scoring models are based on the assumption that past behavior can predict future risks.
There is big business in credit cards and knowing who is a good credit card customer and who is not is imperative to the bank looking for new customers. There are companies that furnish this information to the banking industry to drum up business. Ever wonder why you receive certain types of direct mail credit card offers? Wonder why a credit card company suddenly decreases your credit limit despite your perfect payment history? With the advent of the computer, many types of sophisticated modeling is available to the banking industry. The whole point of these models is of course, to maximize profitability.
Your revenue score, calculated by banks, has nothing to do with your income. The revenue score actually has to do with how much money you are expected to make for the credit card issuer. This score predicts how much money a credit card company is likely to make from a specific customer, based on past behaviors and payment history.
You've heard of the term "credit card deadbeat?" A credit card deadbeat is the insider term used by credit card company executives and refers to all of the credit card users who pay off their bill each month promptly; in doing so, such customers pay no interest and prevent the creditor from making any profit.
This score can lead to the ironic situation where a customer with a perfect paying history may find their credit cards cancelled or credit limits lowered. This is because the credit card companies are actually losing money on unprofitable clients.
Behavior scoring is a decision-making customer prediction tool based on customer behavior and life-style. This powerful tool plays an important role in banking, credit card, insurance, and telecommunication industries as it helps solving business issues, such as:
- Contractual credit loss
- Customer attrition
- Account management
With the capability of identifying which customers will turn 'bad' in the future, scoring models can develop proactive strategy to reduce the potential loss months before the customers actually become bad. On the 'good' customer group, different sets of action can be taken to improve the profitability and retain the customers.
Response model helps businesses to better understand and anticipate their customer needs, behavior patterns, and value. With response model, it is possible to design, test, and implement more effective strategies for acquiring, growing and serving customers. Some of the areas that can be addressed with a response model are:
- Product cross-sell and up-sell
- Direct mailing solicitation
- Activation & promotion programs
A transaction score is generated for each purchase you make, and is used to determine whether the transaction should be approved, or whether it might be fraudulent. This score also factors in the risk of whether or not the customer is likely to return the purchase, or whether questions concerning an online purchase will deter the completion of the purchase.
Your transaction score is based on profile data. Some examples of this data are:
- Contain summaries of historical data that include prior customer transaction data.
- Number of times a customer returned a purchase.
- Whether or not the customer will complete the transaction
- Number of previous fraudulent transaction connected to the consumer.
- Probability based on the likelihood that a user customer will terminate the transaction if the user customer is presented with an online shopping cart follow-up question set.
There is no single credit-lending business which has no delinquent customers. The collection scoring system is based on customer's past behaviors in both non-delinquent and delinquent states, the system is able to determine which of delinquent customers has higher chance of collectibility/recovery, who should get harsher treatment, what is the cost-effective medium to use, etc.
This score is beneficial to collection agencies who have large portfolios of debt. Why spend a bunch of time and money on accounts which are unlikely to be collected?
Your application score contains secondary information not factored into your FICO® credit score. Examples of this type of information are:
- Your age
- Where you live
- Your ethnicity
- Your profession
Bankruptcy Risk Score
Your bankruptcy risk score is just what it sounds like: a measure of how likely you are to declare bankruptcy. Analysts at credit reporting agencies say advanced mathematics and data analytics are used to determine the complex score. However, they say, some variables come directly from your credit report, such as how the credit is used, how often a bill payment is late and the number of inquiries made.
Researchers say the score typically surfaces when a consumer gives the bank permission to pull his credit report during the application process for a new loan, bank card or credit card, and during the periodic review of clients' accounts to determine whether to increase a consumer's credit limit.
What goes into a bankruptcy score? Of course, developers of the model are not giving out too many details. However, there are some clues. For instance, where you live can change your bankruptcy risk score. According to Nerd Wallet, the states with the highest amount of consumers to file for bankruptcy in 2016 are:
Attrition Risk Score
An attrition-risk score measures how likely you are to close your account. Lenders use this in combination with other scores to decide whether a customer is worth retaining.
In addition, research has shown that retaining existing customers is more profitable than acquiring new customers due primarily to savings on acquisition costs, the higher volume of service consumption, and customer referrals.