Tag: customer management

Consumers' financial behaviors are constantly changing. Event triggers enable lenders to quickly respond before their portfolio takes a hit.

For lenders, mitigating first payment default requires data, advanced analytics, customer engagement, and agile risk management.

The average turnaround time to make a lending decision varies materially between financial institutions. Institutions with low-level automation are typically less competitive on price due to the higher cost of manual reviews. For customers, it leads to high levels of dissatisfaction, complaints and switching of institutions. To learn more practical insights and best practices for key areas of business banking and to look at the features of a leading-edge approach to customer management, download the full white paper. Source: Strategic customer management for business banking portfolios by Experian's Global Consulting Practice.

By: Wendy Greenawalt Large financial institutions have acknowledged for some time that taking a more consumer-centric versus product-centric approach can be a successful strategy for an organization. However, implementing such a strategy can be difficult, because inherently organizations want to promote a specific product for one reason or another. With the current economic unrest, organizations are looking for ways to improve customer loyalty with their most profitable and lowest risk customers. They are also looking for ways to improve offers to consumers to provide segment of one decisioning, while satisfying organizational goals. Customer management, and specifically cross-sell or up-sell strategies, are a great example of where organizations can implement what I call “segment of one decisioning”.  In essence, this refers to identifying the best possible decision or outcome for a specific consumer when given multiple offers, scenarios and objectives. Marketers strive to identify the best strategies to maximize decision-making, while minimizing costs. For many, this takes the form of models and complex strategy trees or spreadsheets to identify the ideal offering for a segment of consumers. While this approach is effective, algorithm-based decisioning processes exist that can help organizations identify the optimal decisioning strategies, while considering all possible options at a consumers level. By leveraging an optimization tool, organizations can expand the decision process by considering all variables and all alternatives to find the most cost effective, most-likely-to-be-successful strategies. By optimizing decisions, marketers can determine the ideal offer, while quantifying the ROI and adhering to budgetary or other campaign constraints. Many organizations are once again focusing on account growth and building strategies to implement in the near future. With the limited pool of qualified candidates and increased competition, it is more important than ever that each consumer offer be the best to increase response rates, achieve portfolio growth goals and build a profitable portfolio.

By: Kari Michel Bankruptcies continue to rise and are expected to exceed 1.4 million by the end of this year, according to American Bankruptcy Institute Executive Director, Samuel J. Gerdano.  Although, the overall bankruptcy rates for a lender’s portfolio is small (about 1 percent), bankruptcies result in high dollar losses for lenders.  Bankruptcy losses as a percentage of total dollar losses are estimated to range from 45 percent for bankcard portfolios to 82 percent for credit unions.  Additionally, collection activity is restricted because of legislation around bankruptcy.  As a result, many lenders are using a bankruptcy score in conjunction with their new applicant risk score to make better acquisition decisions. This concept is a dual score strategy.  It is key in management of risk, to minimize fraud, and in managing the cost of credit. Traditional risk scores are designed to predict risk (typically predicting 90 days past due or greater).  Although bankruptcies are included within this category, the actual count is relatively small.   For this reason the ability to distinguish characteristics typical of a “bankruptcy” are more difficult.  In addition, often times a consumer who filed bankruptcy was in “good standings” and not necessarily reflective of a typical risky consumer.   By separating out bankrupt consumers, you can more accurately identify characteristics specific to bankruptcy.  As mentioned previously, this is important because they account for a significant portion of the losses. Bankruptcy scores provide added value when used with a risk score. A matrix approach is used to evaluate both scores to determine effective cutoff strategies.   Evaluating applicants with both a risk score and a bankruptcy score can identify more potentially profitable applicants and more high- risk accounts.