As the lending environment becomes more competitive, credit unions need access to appropriate risk information in real time, in order to serve their members well and make quick, data-based lending decisions.
With loan portfolio analysis by Lending Insights, loan managers can easily identify risks and opportunities, and to measure and monitor these over time.
Minimize risk of loss
With Lending Insights, credit unions have access to a powerful set of tools to manage loan portfolio risk. Key metrics, scorecards and detailed report templates within the Lending Performance Management System can produce a range of fully automated reports to highlight areas of concern by loan and product type.
For example, dealer management reports allow credit unions to determine loss and delinquency performance by dealer and further drill into the dealer loan profiles by collateral type, member type, credit tier and a variety of other dimensions. This enables credit unions to accurately pinpoint loss and delinquency trends over time, and monitor their impact on the overall loan portfolio.
Increase loan opportunities
By analyzing each factor contributing to profit and loss, Lending Insights helps identify ways credit unions can boost profitability while reducing risk. Detailed reporting and research tools help pinpoint the greatest profit sources and highlight future loan growth opportunities. The market intelligence and CUDL benchmark reports included in the system allow credit unions to assess loan originations and performance against credit union peers.
Real-time risk analysis can help users decide whether to underwrite a particular loan. With greater insights from business data, credit unions may find that they need to review current underwriting criteria. By establishing more risk factors, loan managers can look deeper into an individual loan application to understand how it will perform in a portfolio.
Manage credit risk
Lending Insights helps credit unions manage credit risk by providing powerful and intuitive business analysis. Reports that track and evaluate characteristics and trends of delinquent loans give credit unions insight into future performance of a loan, and allowing them the opportunity to act before the loan is charged off.
To maintain balance in a loan portfolio, credit unions must achieve diversification, without becoming too dependent on a single source. The multi-dimensional portfolio analysis (MDPA) capabilities of the system can pinpoint historical risks within a portfolio and uncover connections between seemingly unrelated categories that may produce higher risk.
Credit unions can rely on loan portfolio analysis by Lending Insights to increase profitability and efficiency, while mitigating risk and satisfying member expectations.
For assistance on understanding how to use Lending Insights for loan portfolio analysis, contact firstname.lastname@example.org.
Current Expected Credit Loss (CECL)
The introduction of the Current Expected Credit Loss (CECL) model, presented by The Financial Accounting Standards Board (FASB), requires the vigorous efforts of credit unions to adequately and efficiently comply with new requirements.
On the heels of the financial crisis, the FASB concentrated on the ideas of forward-looking, capital planning, and stress testing, with the goal to replace the incurred loss approach with a lifetime expected loss model. In anticipation of its release, it is imperative for credit unions to get ahead of the curve, as the transition will impact the mindset and operations, in addition to a credit union’s reporting and disclosures.
Expected CECL Challenges
ALLL Impact: CECL is expected to change the loan loss reserve calculation, creating implications across day-to-day operations.
Historical Loss Rates: It is important to understand and incorporate historical loss rates, while also including forward-looking assumptions into the calculations.
Comprehensive Accounting and Credit View: This will be necessary to communicate the method and information used to calculate the reserve, as well as projected forecast.
How to Prepare for CECL
Boost Data Collection: Historical balances, risk ratings, charge-offs, and recoveries should be collected. The more portfolio data collected, the better a credit union can calculate expected losses.
Switch to Migration Analysis: This allows credit unions a more granular loss methodology, while gathering risk rating by individual loan, loan duration, individual loan balance, individual charge-offs and recoveries, and individual loan segmentation.
Model Flexibility: Adapt current models to accommodate the new guidelines.
Explore Forecasting: With data just being half the battle, it is important to create and revise forecast models that support all requirements.
Lending Insights’ Compliance Reports
CU Direct’s Lending Insights is actively preparing for CECL requirements ahead of its anticipated release. In preparation, Lending Insights will offer clients a CECL compliant report in the support of this transition.
The reports are designed to provide default probabilities based on multi-variant linear regression analysis. Simply put, it is the analysis of multiple risk attributes working together to determine how we can expect a loan to perform based on historical experience.
For additional information on how Lending Insights is helping credit unions during the CECL transition, please fill out and submit an inquiry request.
With Lending Insights business data software from CU Direct, users can instantly generate static pool reports to isolate problem areas, analyze losses and repayment speeds, identify potential new profit centers, and provide the documentation that regulators are requiring.
After collecting, formatting and warehousing all of a credit union’s data in the cloud-based Lending Insights data storage system, it’s easy to begin creating and analyzing static loan pools, with just a few clicks.
Static pools are "pools" of similar loans that were originated during a given time period, usually one quarter or one year. By combining two different sorting factors, for instance, year of loan initiation vs. loan type, the software can create a report showing key metric performance of the static pools over time.
For a typical static pool report, the rows of the chart might be labeled: 2010 mortgage loans, 2011 mortgage loans, 2012 mortgage loans, etc. The columns of the chart can be set to show a selected key metric, for example, the 60-day delinquency, risk concentration, or the total remaining balance of the loans, year by year.
Identify problem areas
By stratifying and comparing static pools in this way, users can analyze each pool separately from new (or old) loans, to identify problem areas that may require further investigation. For example, a report may show that 2011 mortgage loans had a much higher delinquency rate than either 2010 or 2012 loans. To find out why that pool is underperforming, a user can drill down deeper by clicking on the pool name in the report (e.g., 2011 mortgage loans) to bring up that pool’s complete performance history.
When compared with outside factors, such as the economy, interest rates, and changes in credit union underwriting policies, reasons for the poor pool performance may become clear, allowing for correction.
While comparison of static pools can be a powerful loan management tool, Lending Insights can also track and analyze a single pool’s performance over time, from its inception. Single pool analysis gives a view of key metric trends, such as delinquency ratio, net yield, or average interest rate, as of a given date, in order to help forecast rates of return based on estimated prepayments and charge-offs.
Develop new business
In addition to forecasting risk and highlighting problem areas, static pool analysis can also discern the factors contributing most to a credit union’s profitability, such as fees, credit scores, LTVs and operating expenses. Once these are identified, managers can use them to develop new business, and better serve its members.
Note: For more detailed analyses, Lending Insights offers Advanced Filters to help credit unions further slice and dice their data using Multi-Dimensional Portfolio Analysis (MDPA).
Static pool analysis by Lending Insights is a strategic portfolio management tool, helping credit unions make data-driven decisions to increase profitability, decrease losses, and meet regulatory requirements with ease.
With Lending Insights from CU Direct, credit unions can manage and analyze their portfolios by multiple risk dimensions, creating reports that drill down into loan data to isolate problem areas, as well as identify potential new profit centers, while satisfying the demands of NCUA examiners.
In order to identify risk exposures in ever-changing loan portfolios and drive future lending strategies, Lending Insights contains Multi-Dimensional Portfolio Analysis (MDPA) capabilities, which allow detailed portfolio segmentation and stratification to analyze internal portfolio risk.
Once a credit union has uploaded its data to the Lending Insights cloud-based warehouse, it can begin using powerful MDPA analytics to derive meaningful insights that can be used to propel the business to a whole new level.
The Lending Insights system has built-in algorithms to calculate key loan analysis metrics, such as risk concentration, combined LTV, and probability of default. Users can add advanced filters to these static pool reports, which allow them to isolate certain sections of that report, and then run it again with two additional dimensions selected.
For example, to create a 60-day delinquency report by segmented by dealer for all indirect auto loans, users can select the 60-day delinquency metric and run a Current Balance report using the “dealer” dimension. In just a few clicks, this report shows which dealers have a much higher than expected delinquency ratio, but it does not show specifically where that delinquency is coming from.
Using MDPA capabilities, credit unions can add another risk dimension criteria, such as dealer personnel code, to the report. This gives users the ability to drill down to the level of a specific salesperson, and even follow that person if they migrate from dealer to dealer.
Isolate areas of risk
Once a problem has been isolated using MDPA, credit unions can take corrective action, for example, by refining underwriting policies or updating loan origination techniques and strategies.
MDPA advanced filters can be used to build expressions that will be used for regular reports with updated data, such as credit scores and collateral values. Users can create “watch lists” for at-risk loans, for example. Report criteria, including advanced filters, can be saved and scheduled to run every month, and emailed to a mailing list.
With Lending Insights, credit unions can perform a wide range of multi-dimensional portfolio analysis, including:
Allowance For Loan Loss
Static Pool Loss Projections
24-Month Historical Average Loss Projections
Global Dynamic Reports
Combined LTV Calculations
Applying LTV Across Products
Identifying Portfolio Risk Concentrations
With advanced filtering capability and multi-dimensional portfolio analysis, credit unions can fine-tune their portfolios, increase their competitiveness, and better serve their members.
For assistance on understanding how to use Lending Insights for multi-dimensional portfolio analysis, contact email@example.com.
Concentration Risk Analysis
Lending Insights, the business intelligence software designed specifically for credit unions, calculates concentration risk metrics, such as loans by geography, product type, or credit score tier—sliced and diced for the entire portfolio or segments within it. Too many loans in any single category, or group of related categories, could be catastrophic if outside forces cause significant destabilization in a specific market area.
Regular concentration risk analysis helps you keep tabs on loan concentrations that may put the credit union at risk, giving you more time to take action. For example, if analysis shows too much risk concentration in one particular type of loan, such as residential real estate, the credit union may consider cutting back on marketing for that product, increasing rates, or even shutting down the product offering temporarily.
NCUA examiners want to see that credit unions are accurately assessing and managing risk concentration limits, commensurate with the percentage of a portfolio concentrated within a loan or product type.
Satisfy NCUA examiners
All responsible parties need accurate, current data in order to calculate the concentration risk for each of its products, including categories that may seem unrelated, but may be threatened by common risk events. Maintaining this data in a centralized location, such as the Lending Insights cloud-based data warehouse, along with the ability to easily access and report on regularly updated metrics, allows accurate concentration risk analysis and will help satisfy NCUA examiners.
Lending Insights allows credit unions to track and report on the number of loans by business type, sector, geography, or credit ratings, for example. The software can then calculate the relative concentrations of each loan or type of loan as a percentage of total loans, total assets, or net worth.
Actively monitor concentration risk
Our Key Performance Index (KPI) scorecard feature lets credit unions set performance levels for each metric, including concentration risk, and makes it easy to actively monitor those goals with a red-yellow-green icon to indicate which metrics have exceeded, or are in danger of exceeding, the credit union’s limits for each concentration.
If the icon appears yellow or red, the Lending Insights advanced filters feature and multi-dimensional reporting analysis capability allows you to dive deeper into the data to determine where the risk is occurring and what changes should be made.
With the Lending Insights, users can set up a reporting schedule that will deliver saved reports to an email distribution list in a printable format. This keeps credit union management aware of concentration risks as they arise, giving them the opportunity to develop contingency plans and prudently manage the risks.
More and more, credit unions are relying on data analytics to drive business decisions and maintain a competitive edge. One of the biggest challenges for credit unions is accessing data spread out in a number of different places, including the core operating system (where it may be archived and inaccessible), a Loan Origination System (LOS), a paper spreadsheet, or with a third party.
In order to efficiently and effectively use this data, it must be collected in a single, secure location, where it can be easily accessed and used to extract valuable insights and provide NCUA-compliant reports. At Lending Insights, our credit union data warehousing system allows users to push all their data into a central cloud-based location, creating a single source of the truth—which is key to consistent reporting and analytics.
With 20 years of experience and over 1,100 credit union clients nationwide, CU Direct understands what credit unions need and what they can afford, in terms of cost and staff time required for data collection and reporting. We make it easier for every credit union to use data analytics, no matter their level of expertise.
Uploading to our cloud-based data warehouse
Credit unions upload their loan data in a formatted data file, similar to an Automated Integrated Regulatory Examination System (AIRES) file, over secure connections to our cloud-based CU Direct data warehouse. To begin the process, we work with new clients to customize the data fields best suited to analyzing their particular portfolios, including the types of loans offered.
Most of the metrics (no matter how complicated) that will be calculated are based on just a few data points, which are already available in each loan application file. After the initial data upload, at the end of every month our credit unions upload a new data file, which acts as a snapshot of their portfolio at that moment in time. This snapshot allows users to see a historical perspective over time.
Cloud data software available 24/7/365
Our clients receive an unlimited number of user licenses, and each user downloads Lending Insights' Smart Client to their own PC, laptop or mobile device equipped with Windows 8 Pro. The data and software are available 24 hours a day, seven days a week, and are accessible from anywhere with an Internet connection.
Lending Insights uses the uploaded data to pre-calculate the metrics that every credit union needs for its day-to-day operations, such as delinquencies, losses, loan growth, profitability, and LTV ratios.
Each time a user opens the Lending Insights software in an Internet browser, the product updates itself, and the data and reports become easily accessible through a dashboard, complete with customizable report templates designed specifically for credit unions. Once a report is generated, it can be saved, printed off, emailed, and/or added to a regularly scheduled report list.
Lending Insights can help credit unions improve profitability and mitigate losses with high-level, customized recurring reports that deliver accurate and timely analysis for decision making. By monitoring various internal yield metrics, credit unions can determine which loans have been most profitable over time, and adjust their strategies accordingly.
The Lending Insights system can:
Perform historic cash flow analysis, which tells you when and how profitable you are.
Segment categories into smaller and smaller sections for more accurate measurement, using our multi-dimensional analysis capability.
Identify areas of a loan portfolio experiencing increased losses and delinquency.
By helping identify the specific areas of portfolio loss—and why those losses are occurring—lenders can more closely monitor the performance of the loans over time to minimize their risk of loss.
The Lending Insights system provides a powerful set of tools, including metrics, scorecards and detailed reporting, that can highlight key performance indicators that are falling below pre-set goals.
Discover your most profitable loans
The software calculates risk concentrations, delinquencies, losses and profitability. Multi-dimensional portfolio analysis, with advanced filters, allows users to drill down into specific loan profiles by collateral type, member type, credit tier and a variety of other dimensions.
Lending Insights enables lenders to quickly and efficiently perform calculations that would be difficult, if not impossible with simple spreadsheet software, or on a credit union core operating system. One such metric is the historic rate of return (yield) on a loan from its origination. Another is net yield, derived by looking at all of the income and all of the expenses, including losses and initiation fees, for the portfolio over time.
Lending Insights can run a Yield Metrics Report based on a static pool of loans, taking into account the cost of funds, charge-off, origination or servicing costs, and net yield. The user can then select any risk dimensions and determine if loans in that pool have been profitable throughout their entire lifecycle. By applying the “dealer” dimension to a report on indirect loans, for example, lenders could discover which of the car dealers they partner with have been the most profitable.
These tools help credit unions take a much deeper look into their loan portfolios, to more accurately pinpoint loss and delinquency trends over time. Credit unions can minimize their overall risk of loss by reviewing loan loss trends over time with fully automated reports that highlight areas of concern by loan and product type.
One of the best ways to identify new loan opportunities, while minimizing portfolio losses, is to track and analyze changes in credit scores over time, called credit score migration. Often, lenders will manage their portfolios based on the borrower’s credit score at origination. However, by conducting regular credit score migration analysis, lenders can take action to better mitigate future losses and discover new opportunities for growth.
A borrower’s credit score, no matter what model a credit union uses, is intended to predict the probability of borrowers in a particular score band defaulting on a loan. The most common, generic models predict the probability today of an applicant defaulting—going 90 days or more delinquent—in the next 24 months. Other models predict different probability measures, so it is important that a lender understand the model being used.
Often, lenders view credit scores similarly to the certification on a piece of beef. The term “Grade A” in meat processing signifies that the meat has met a certain standard of quality. “Grade A” meat will always be “Grade A,” but a borrower will not necessarily maintain the same credit score over time.
Credit risk changes over time
Add to that the fact that a credit score of 680 today could be associated with a 2 percent probability of default, but two years from now, the exact same score may carry an 8 percent probability of default. This is because, even though the models do not change, overall borrower behavior changes within those score intervals. In cases of a severe recession—as recently experienced in the United States—even the most reliable borrowers can have trouble making timely payments.
Knowing a borrower’s score at origination, and analyzing how borrowers in a particular origination score interval perform over time, should inform future lending decisions.
But by managing a portfolio purely based upon the risk at origination, lenders may miss the fact that an “A” member has dropped to a “D” score over a two year period, while at the same time, the current LTV of their property has increased, leading to hidden risk.
Update credit scores to analyze current risk
For this reason, it is important to measure a portfolio’s current risk by obtaining new scores for each borrower at regular intervals. With Lending Insights, credit unions can upload new credit scores, typically either quarterly or annually, to our cloud-based data warehouse. Our proprietary algorithm then re-calculates the current risk in your portfolio, based on current credit scores and current LTV, which the software can estimate.
Using credit score migration analysis helps credit unions regularly re-establish the risk in their portfolios, isolating those loans with the lowest credit scores and the highest LTVs. This enables them to focus collection strategies on those loans that are going to cost the most money, and act accordingly to help prevent default.
For assistance on understanding how to use Lending Insights for credit score migration analysis, contact firstname.lastname@example.org.