Scores let you know where you stand, whether it is a test score in academics or the final score of the Super Bowl, they are a quick way to measure past performance. Past performance is an important indicator for future performance and using scoring rules in business decisions can help predict the probability of certain outcomes.
Scoring rules are specific types of business rules that use scores to measure how likely a prediction is to come true. They are common tools in making business decisions and are often used to evaluate risk and prioritize opportunities. For example, scoring rules can measure the likelihood that:
- A borrower will pay back a loan
- A buyer of insurance is going to make a claim
- A credit card transaction is fraudulent
- Any single investment will provide a good return
- A patient has a certain condition
With these metrics, business leaders can better allocate resources and take action to optimize outcomes.
Implementing Scoring Rules
One of the great things about scores is that they summarize much larger sets of data. Simple scores may just incorporate a few data elements. More sophisticated scoring rules may aggregate scores from multiple more focused scoring rule sets and incorporate additional important metrics. For example, a risk scoring system that determines if an individual gets a mortgage may take into account a credit score as well as debt-to-asset ratio, and a score that measures the risk based on location and type of property being purchased.
With the ability of scoring rules to summarize data, decisions and actions can be made much quicker. For example, investment opportunities can be ranked and managers can allocate capital appropriately. Thresholds can also be easily set up. If the fraud score for a certain transaction falls outside a certain parameter, it can be denied and workflows that conduct greater security checks can be initiated.
