DESCRIPTIVE CHARACTERISTICS

There are characteristics that quantitatively and qualitatively describe the profile of the coun­terparty. Think of this as metadata, which helps in understanding counterparties, irrespective of their contracts.

There are some typical characteristics used in counterparty description such as, for indi­viduals: age, place of leaving, income, gender, job, educational background, or even religion. For business entities, e.g., SME, corporate, they are profit, sales, expenses, industry, sector of business, region of operations, and others. A sample of counterparty descriptive characteristic is shown in Table 7.1.

Descriptive characteristics may also be used to reflect possible financial behavior and credit needs. For instance, a young person with a good educational background has most likely the need for medium to long-term loans as well as credit lines (credit cards), whereas an SME will require credit facilities and short to medium-term loans.

The most useful characteristics in counterparty systemic, concentration and correlation analysis are the ones referring to the business sector in which a counterparty operates—for instance, the industry, region and country. Note also that some of the descriptive characteristics change over time. This is a great challenge because such information needs to be retrieved and updated on a frequent basis which is not always feasible. Thus, practitioners are trying to focus on those characteristics with a high likelihood of being fixed and most available.

TABLE 7.1 Sample of counterparty descriptive characteristic

Descriptive

Source: Lending Club

In marketplace lending, the descriptive characteristics are similar as illustrated in Table 7.2.

Online lending platforms may collect more data. These characteristics are quite similar to the ones that banks use. However, the credit scoring algorithm of platforms may be markedly different. They often take into account alternative data such as payment history on bills, and so- called fringe alternative data, such as posts on social networks, friends, and others. Platforms often consider more data than banks when scoring their borrowers. They may be more precise because counterparties know each other in real life as well. They may also be more transparent and easier to maintain and update as they work within a bilateral scale.

7.3