Using Loan Portfolio Analytics to Generate Revenue as a Financial Institution
March 2016

Loan portfolio analytics offer financial institutions incredible capability to create organizational efficiency, mitigate risks, and avoid compliance snags. But just as important, a robust program can do wonders to generate revenue.

The need for better data management can’t be underestimated. In recent years, as computing power, analytics providers, and nontraditional competitors all have exploded, implementing a system has transitioned from a tool that provides a business advantage to a necessary component of financial services business for three reasons on the defensive side alone:


1. By addressing data integrity concerns, eliminating input redundancies, and creating a wealth of customizable reports, these loan portfolio analytics programs can provide immediate cost and time savings.

2. The ability to better identify, track, and correct the root causes of delinquencies and charge-offs, through methods such as better credit risk monitoring and optimized underwriting standards, also can shore up the bottom line.

3. The capability to recognize early warning signs of compliance missteps in this heightened regulatory climate minimizes a potential drain on resources.

On the other side of the ledger, data analytics can open the door to new or expanded revenue channels by affirming intuitions held by decision makers or shedding light on market trends and consumer needs that have gone unnoticed or unappreciated.

To take advantage of these opportunities, financial institutions must align their internal structures with their goals. The foundational elements include:

  • An experienced, open-minded and observant lending and senior management team and board that both recognize the possibilities data provide and are comfortable testing hypotheses based on data aggregation, statistics, economic data and demographic trends;
  • An empowered staff that understands the integral importance of lending to the success of the institution, and works directly (lending officers and staff) or indirectly (front-line and call-center employees) to identify members’ needs and match them with the financial institution’s services and products.
  • A refined omnichannel capability that can respond deftly to consumers’ growing desire to conduct their banking when, where, and how they desire, and proactively present personalized, targeted offers.
  • An understanding of data that crosses all departments in the organization. Every department needs to understand what data are available for analysis, how they can access the data, and how to translate data into a strategic advantage.
  • An astute marketing function that creates defined, eminently attractive strategic campaigns to capture greater wallet share among existing members and provide incentive for other consumers to switch from their current financial institution.

The exact mix of product offerings will vary depending on a financial institution’s size, philosophy, and the demographics of its consumer base. But let’s look at two areas that have generated results thanks to heavy mining of data analytics: loan recapture and risk-based pricing.

Statistics show that consumers often fail to shop around for loans and educate themselves on the finer points of various products, even as the number of options and available information escalates rapidly. That means that many people – yes, even some of your members – lock in on loans with terms less favorable than what you offer. Then, to steal a line from infomercial legend Ron Popeil, they set-it-and-forget-it, either unaware that better options exist or unwilling to take the initiative to refinance their loan.

Armed with data showing members’ internal and external financial obligations, a sleek recapture team can produce quick and substantive results. The soft-sell approach, combined with a customer-friendly options to execute the switch, often is the only push people need.

Meanwhile, risk-based pricing has come into its own in recent years, the product of more reliable data analytics evaluation of consumers’ financial situation, and a large base of people whose financial outlook remains less than rosy due to fallout from the financial crisis and the uneven recovery.

Recent studies indicate that 56% of the U.S. population can be classified as subprime borrowers. The figure rings true across a wide majority of states, rather than in certain pockets of the country. Many of these consumers have ample ability to repay loans but either have been unable to shore up their credit scores or, in the case of the millennials whose entry into the job market was delayed by the slow economy, simply lack much of a credit history.

The subprime market contains a lot of promise, with the proper controls and a robust data analytics program in place. By adjusting interest rates to reflect the higher level of risk in serving these consumers, credit unions can increase their returns exponentially, while staying true to their ideals in serving a market that otherwise might not have access to traditional financial services.

These represent two of the many ways loan portfolio management systems offer not just peace of mind, but a return on investment.

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