Business Intelligence

The core of Predictive Analytics is to analyze current and historical data to make predictions about future events. By mining your data, we can find patterns in the data to identify risks, spot opportunities, and help predict future behavior.

TechRim ITE clients have leveraged Predictive Analytics in the following manner:

SALES - Help maximize cross-sell & up-sell conversion rates
The power of this technology is that it can be used to identify cross-sell or up-sell opportunities during a live transaction with a customer. This leads to higher profitability per customer and can help strengthen the customer-agent relationship. In order to best decide which products and services could be of interest to the customer, our predictive models will analyze:

• The customer’s spending habits
• Purchase history
• Customer profile (male/female, age, education level, household income, etc.)

UNDERWRITING – Help predict future risk of default.
Understanding exposure to risk is essential for many businesses

• Auto Insurance Providers – Predict the chance of an auto accident or traffic violation by evaluating the person’s driving record, claims and personal profile to determine a premium amount to charge.
• Financial Services Companies – Predict the chance of default or bankruptcy by analyzing a borrower’s credit score and assets and liabilities before granting a loan.

COLLECTIONS – Help predict which customers are the most or least likely to pay.
Every portfolio has a set of delinquent customers who do not make their payments on time. It is the job of the financial institution to recover the amounts owed as quickly as possible. Unfortunately, significant resources are wasted trying to collect from customers who have a very low probability of actually paying. Also, it’s important to allow deserving clients some flexibility to work through their financial issues. Now you can better predict which customers are going to pay the fastest by analyzing the following:

• Default history of the consumer
• The last contact with the consumer
• Law suits pending
• Most effective contact strategies
• Past success of the collection agency