However, making informed decisions about the future can be difficult for many financial institutions amidst the pressures of day-to-day work. These pressures include the need to attract and retain members and customers in a competitive environment whilst dealing with internal and external pressures to deliver value to all stakeholders. In order to do this, financial institutions need to control credit risk whilst achieving other business objectives.

Traditionally, many organisations have tended to manage credit risk somewhat passively. This has meant assessing a customer or member’s credit-worthiness at the point of application – on the basis of anecdotal evidence of past performance, the personal experience of the person making the decision and usually without a detailed analysis of past credit behaviour. With the initial assessment complete, companies then monitor the customer’s account on an exception basis.

Similarly, the way in which organisations manage customer relationships has typically been reactive. Lacking an understanding of customers’ potential risk and value at any given point in time, organisations have often found their own financial circumstances have been impacted by those customers who have faltered and failed to pay. Given this limited understanding, organisations’ cash flow, costs and risks become similarly difficult to predict. In other words, without the ability to determine how each individual customer affects the performance of the credit portfolio, companies have struggled to predict the performance of the portfolio itself.

More recently, credit risk has been managed by organisations taking ownership of each relationship. This ownership often involves assigning risk to each customer at the point of application and monitoring this throughout the life of the relationship, using powerful behavioural scoring models, which enable companies to predict customers’ performance, along with their own profitability. With this knowledge, organisations can build stronger customer relationships, choosing to target those customers with potential value. In turn, collection strategies based on risk, churn and propensity models can be employed to examine the behaviour of customers encountering problems with payment. The need to recover customer value no longer means necessarily losing the actual customer, but offering services that meet the credit risk appetite of the customer and the organisation.

For the best results in managing credit risk, Baycorp Advantage recommends a combination of automated decisioning, statistical scorecards and a range of third party data (credit bureaux). This ensures that credit providers can then manage the credit they extend in a consistent and controlled way. Customer applications referred for subjective underwriting or that override the system recommendation can then be tagged for future monitoring purposes. Following this approach, credit providers can maximise opportunities to cross-sell and up-sell to existing valuable customers while managing poorly performing accounts. As the quality of credit information improves, so does the quality of an organisation’s decisionmaking process.

By establishing such systems, organisations can put in place a prudent credit risk framework that can support not only the underlying process operations of the business, but also provide sound information to management and the board on the performance of risk and profitability. In turn, this framework can also meet the needs of Basel II in assisting with reporting the credit risk pillar to regulatory authorities such as APRA (Australian Prudential Regulation Authority).

To find out more information on ways to control credit risk, please contact us via our website.  Alternatively visit our website to learn more about value based decisioning.