In the finance environment, lending and borrowing money requires a series of processes for a positive outcome for both the consumer and the credit provider. This would mean that the individual will be able to obtain credit in the form of a loan or financing and the lender would be able to issue credit to a responsible and loyal borrower. One critical function which is used to determine this is credit analysis. Analytics is used in all walks of life but is highly developed and very successfully used in the credit space.
Credit analysis plays a critical part when calculating the affordability of anyone who uses credit.
When conducting a credit analysis a possible lender will examine collateral and other sources of repayment as well as credit history and the person’s ability to effectively manage credit. Analysts attempt to predict the probability that a borrower will be able to pay their debts, and also the severity of losses for the credit provider in the event that the borrower is not able to repay their debt or the agreed installment.
Analytics essentially takes a holistic view of the data that is received and converts it into actionable information. The statistical analysis gives an overview of consumer behaviour within the credit space. We are always looking out for interventions to implement to ensure that the calculation and models we create are on par with the client’s needs even before they are realised.
It uses a variety of financial analysis techniques, including ratio and trend analysis. An analyst would, for example, estimate the possible success of opening a franchise in a particular area by conducting research on consumer spending behavior in that geographic location. There are of course many other marketing evaluations that can be carried out by information bureau analysts.
The process of creating and evaluating the models which measure credit worthiness are constantly monitored and tested in order to ensure that they are valid and changed if they are no longer predictable. We need to constantly ensure that the measures that we put into place are specific and will allow for the best output for both the individual consumer and client.
Analytics receives information on the credit behaviour of a consumer from various sources as well as the Credit Providers Association (CPA) or the Micro Lenders Association. The information would detail their spending habits, how much credit they have, and how frequently they make payments on their open accounts.
Analytics plays a critical role in the economy as it enables credit providers to grant sensible credit to consumers or businesses. Careful analysis will determine whether or not the recipient of the credit is able to receive credit and finally the credit providers are then with this information provided by the bureau able to determine whether or not the individual or organisation is able to repay the loan.
Sensible credit must be granted on a win/win basis both for the lender and the borrower. Analysts within an information bureau also conduct calculations for their clients to assess and predict various aspects of consumer behaviour:
The circumstances in which information is used varies. From calculating an individual’s credit score, to providing data for a credit provider, to assessing the success of a new product that they wish to take to market. We cannot use the same yardstick for every consumer or client as each one is different. Analytics therefore plays a critical role in giving us a holistic overview of consumer credit behaviour and allows for us to be able to provide this information to our clients in a clear and actionable manner.
We use the data on consumers and companies that is available to us and is verified by the CPA. We look into the consumers’ credit habits and read the trends or isolated occurrences, put this information into an actionable format and deliver it to the prospective credit grantor. The credit grantor ultimately decides on whether or not the consumer is able-, and can afford to receive credit or financing. This decision isn’t made by the information bureau.
Ultimately the weight of the decision on credit eligibility for a loan, finance or credit depends on the consumer’s own attitude and behavior toward their credit.