Category Archives: FICO

Are You in the Half of Firms with No Tested Data Breach Plan?

Last week alone, a New York hospital, a US car washing business and a UK online retailer all suffered headline-making data breaches. There is no fool-proof cybersecurity defence, so businesses of all sizes need to consider not only how they can prevent breaches but also determine what they will do should the worst happen.

Additional losses are heaped on companies that fail to manage the fallout from a breach well. Poor customer communication, disastrous PR and a slow or ineffective response all damage reputation, lose customers and worry shareholders.

Despite this, a new, independent cybersecurity survey we commissioned with independent research and consultancy firm Ovum shows that only 51% of companies surveyed have a tested data breach response plan.

Looking across the six countries we surveyed, it’s clear that some are doing better than others, though none had excellent coverage on this question. The Norwegians are top of the class – 62% of respondents have a tested data breach response plan; the UK is at the other end of the scale with just 41%.

Cyber survey chart 1 Are You in the Half of Firms with No Tested Data Breach Plan?
There was less variation when we looked at the industries surveyed across all countries: e-commerce/retail had the lowest figure at 49%, and telecommunications were the highest with 54%. Looking at the industry data at a country level did yield interesting anomalies. In the UK only 25% of e-commerce/retail companies had a tested data breach response plan, while 78% of Norwegian media services companies do. Size of company didn’t seem to be a factor in whether firms had a tested data breach response plan.

The General Data Protection Regulation (GDPR) is about to be enforced, and it impacts organizations not only in Europe but worldwide. GDPR means that regulators can demand bigger fines from those that lose customer data; in the UK, for example, the ICO will be able to fine an organization up to £17 million or 4% of global turnover.

With this in mind all businesses should review their cybersecurity practices and think hard about the implications of a breach and how they will respond should the worst happen – a good, well-rehearsed plan could become a matter of survival.

Our cybersecurity research has produced a great deal of interesting information on attitudes to cybercrime across the industries and countries involved – we’d like to share more of it with you so join our Tweet Chat using the hashtag #cybertrends on 1st June 2017 at 4 pm BST / 8 am PDT.

Do you know if you’re likely to suffer a data breach in the next year? Find out with the FICO Enterprise Security Score.

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NCAP Record Removals Have No Material Impact to FICO Scores

The National Consumer Assistance Plan (NCAP) is a comprehensive series of initiatives intended to evaluate the accuracy of credit reports, the process of dealing with credit information, and consumer transparency. As a result of NCAP, in July 2017, the three credit reporting agencies (CRAs) are scheduled to make required changes to the criteria used to accept the reporting of a tax lien and/or civil judgment.

It is anticipated that civil judgments and some tax liens will be removed from consumer reporting agency (CRA) data when this goes into effect, including previously reported tax liens and/or civil judgments that do not meet the new NCAP-related reporting requirements.  All credit scores that utilize CRA data will be impacted, including but not limited to FICO® Scores.

FICO recently conducted research on the most widely used FICO® Score versions at all three CRAs to assess the impact of the NCAP-driven removal of public records on the FICO® Score, and results were similar in each instance.

(Note that, as opposed to analyzing a worst-case scenario, where all judgments and tax liens were removed from the credit file, this analysis is based on each CRA’s detailed assessment and representation of the judgments and tax liens that would be removed after the NCAP-related public record standards are implemented by the CRAs in July 2017.)

Our results showed that NCAP-related public record removals have no material impact on the aggregate population to the FICO® Score’s predictive performance, odds-to-score relationship, or score distribution.

For example, the figure below compares the FICO® Score 9 distribution on the total US population before vs. after NCAP-related public record removal; the two distributions are nearly identical.

NCAP Chart NCAP Record Removals Have No Material Impact to FICO Scores

Based on FICO’s analysis, only 6-7% of scorable credit files are impacted, and these files are very likely to have additional derogatory information on their credit file. Therefore, impacted files tend to score relatively low, even after these public records are removed, and more than 75% of FICO® Score increases are less than 20 points.

Since we determined that few consumers were impacted, and the vast majority of those impacted consumers had other derogatory information and FICO® Scores that remained low, the ability of FICO® Scores to rank-order risk on the total population prior to these public records being excluded is almost identical to what lenders would experience with these public records excluded.

Our analysis also showed that volumes above or below score cut-offs remained virtually unchanged on the aggregate, and there was no material impact to the bad rate at a given FICO® Score. While lenders are encouraged to conduct analyses quantifying the impact of NCAP-related public record removals on their own portfolios, they may find that they do not need to make notable changes to their strategies.

For more information, read our executive brief on the impact of NCAP to FICO® Scores.

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Application Fraud, Analytics – and Gamecocks?

Gamecocks Application Fraud, Analytics – and Gamecocks?

I was looking over my blog archives the other day and read this chestnut from December 2015: “With the introduction of EMV in the US, both [card not present and application fraud] are up – especially the sophistication of the synthetic identities used in application fraud.”

Well, isn’t that the truth. Fast-forward a year, to the fourth quarter of 2016, when financial losses stemming from application fraud, which includes the creation of synthetic identities, grew by 42%. Online lenders are being hard-hit; fraudsters are applying for multiple loans within minutes, with no intentions of repaying them.

Customer expectations create fraud opportunities

Here’s what’s happening: Consumers expect instant gratification and there are many, many companies willing to indulge them: Uber, Amazon, Seamless, ad infinitum. Those expectations have transferred directly to lending; customers expect ever-faster loan approvals, and online lenders are happy to oblige.

Loans that used to take three days to get approved at the local branch can now be approved in less than a minute over the internet. You can even get approved for a mortgage in just eight minutes.

But the ease and speed of new loan origination systems, optimized for use on consumers’ mobile devices, have led to catastrophic fraud losses for many institutions. As lenders promote the ease and speed of the application process, and open up their channels to process the flood of applications, the geometric increase in fraud is arithmetically simple: When you open up your channels to process 10,000 or more loan applications a day, there are that many chances for fraudsters to strike.

How lenders can fight back

In the race to win consumers, lenders have inadvertently made loan fraud easy to perpetrate. But that’s not a reason to let the tail (fraud) wag the dog (the lending operation).

To meet customer expectations for speed and convenience, lenders must upgrade their fraud defenses. Those defenses need to be agile and address weaknesses such as application fraud.

FICO is responding to the surge in application fraud by enabling the tight integration of two of our most powerful solutions: FICO® Application Fraud Manager and FICO® Origination Manager. These products can be easily integrated by customer organizations to map application fraud detection capabilities directly into origination processes to detect first and third-party fraud. In this way, lenders can take significant steps toward reducing runaway application fraud.

And on that note, I’d like to close with a shout-out to a different kind of “runaway” — the 2017 runaway success in NCAA basketball of the South Carolina Gamecocks. What a year! The men’s team making it to the Final Four and the women’s team being the winners of the 2017 NCAA Division 1 women’s basketball title (Surprise––the University of South Carolina is my alma mater.) Congratulations!

Follow my latest commentary on fraud, payments and the occasional sports championship on Twitter @FraudBird.

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How Do FICO Scores Bounce Back After Negative Credit Info Is Purged?

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FICO Score logo 2 597x372 How Do FICO Scores Bounce Back After Negative Credit Info Is Purged?

In the depths of the Great Recession, tens of millions of consumers had lapses in meeting their credit obligations. Some seven years down the line, those missed payments are being purged from credit reports in accordance with the Fair Credit Reporting Act, and these consumers may now be looking at a clean (or at least cleaner) slate.

To find out how the FICO® Scores of these consumers might be impacted by this negative information being purged, FICO conducted research on a random representative sample of the 28 million US consumers who had a serious delinquency (defined as 90 or more days past due) between 2009 and 2010. This sample was divided into two groups:

  • Those who had a delinquency removed from their credit report between May 2016 and July 2016. We’ll refer to this group, which numbers about 6 million nationally, as the “delinquency purge” population.
  • Those who did not have a delinquency removed from their credit report between May 2016 and July 2016, presumably because their delinquencies were removed either before or after the May-July period. We’ll refer to this group, which numbers about 22 million, as the “delinquency baseline” population.

Our top findings were:

  • The removal of a serious delinquency was correlated with positive score movement. The average score in the “delinquency purge” population increased 14 points, while there was no change in the average score in the “delinquency baseline” population.
  • Consumers who had all of their remaining serious delinquencies removed between May 2016 and July 2016, which we’ll call the “full recovery” population, had even higher positive score movement, with a 33-point increase in the average score.

How Much Do Scores Improve?

In Figure 1, we see that on the “delinquency baseline” population, 53% of consumers had a score increase between May 2016 and July 2016.  45% of the population, the vast majority of the score increasers, had a relatively modest score increase of 1-29 points, while just 3% had a score increase of at least 50 points.

Delinquencies FICO Scores 1 How Do FICO Scores Bounce Back After Negative Credit Info Is Purged?

Consumers in the “delinquency purge” population were more likely to have a score increase, and more likely to have a large score increase, but the overall impact was still fairly modest. Even in this group, many more consumers had moderate score increases of less than 30 points than large score increases of 50+ points. From May-July 2016, 71% of consumers with a delinquency purge had a score increase, 49% had a score increase of 1-29 points, and 11% had a more sizeable increase of at least 50 points.

Some 22% of those consumers in the “delinquency purge” population were part of the “full recovery” population. These consumers tend to have much larger score increases: 28% have a score increase of 50 or more points, compared to just 11% of the “delinquency purge” population.

Why Don’t Scores Rise More?

In the “delinquency purge” population, 29% of consumers had no score change or a score decrease, despite the removal of a major negative item from their credit report. This may seem unusual, but keep in mind that we’re examining score change over a three-month window, so the score change is not due solely to the purged information. A lot can happen – a new delinquency, or running up credit card balances, for example.

We also suspect that the impact of the removed delinquencies is reduced by two main factors:

  • The FICO® Score gives considerable weight to how recently the delinquency occurred. If a consumer’s removed delinquency was from 7 years ago, its impact was already diminished compared to a very recent delinquency.
  • Some of these consumers have other, more recent serious delinquencies or derogatory information on their files, which means the removal a serious delinquency would not improve their score a great deal.

Do These Score Rises Improve Credit Availability?

Credit availability would increase if the consumers’ score rises resulted in the consumers now meeting lenders’ baseline score thresholds. Figure 2 shows the movement of consumers across some key score thresholds that relate to common score cutoffs for lenders.

Delinquencies FICO Scores 2 How Do FICO Scores Bounce Back After Negative Credit Info Is Purged?

In the “delinquency baseline” population, movement over these thresholds is relatively infrequent. In the “delinquency purge” population, larger volumes of consumers are crossing each of these thresholds, yet the increases are still relatively small, with volumes in the hundreds of thousands. For the higher thresholds, we can see that the majority of the increases come from the “full recovery” population. For example, the proportion of consumers scoring above 700 in the “delinquency purge” population increased by 5.9 percentage points. Yet most of these additional consumers — 287,000 out of 358,000 — belong to the “full recovery” population, who have a much greater tendency to cross these score thresholds.  “Full recovery” consumers have put the credit struggles from a period of extreme economic stress behind them, re-established credit, demonstrated responsible management of that credit, and have experienced higher FICO® Score increases as a result.

For those with financial distress over multiple years (who have other serious delinquencies that have yet to be purged), we anticipate that FICO® Scores will increase similarly when those delinquencies are purged.  In the next blog post in this series, we’ll assess whether these different groups of consumers have differing appetites for new credit.

The post How Do FICO Scores Bounce Back After Negative Credit Info Is Purged? appeared first on FICO.

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What is it Costing You to Collect? Are the Odds in Your Favor?

CollectionsTCO 1 What is it Costing You to Collect? Are the Odds in Your Favor?

If you are considering a new collections platform, you are probably already aware that the upfront price isn’t the only cost that you will pay over the lifetime of the system. How much time and effort you actually want to spend calculating the potential total cost of ownership (TCO) as part of your purchase is an individual choice. Many organizations tend to generalize, knowing that TCO isn’t an exact science, and that a new system’s benefits tend to outweigh other factors.

As a starting point you should spend some time understanding where common, easily-avoided pitfalls lurk. With this knowledge you will be able to make the right choices that can shift the TCO odds in your favor.

Two areas—a platform’s flexibility and security—can have a huge impact on an organization’s exposure to risk and result in unforeseen expenses if not properly supported.

Flexibility
The ability for a platform to easily integrate with an organization’s existing systems is an important consideration for keeping long-term costs down. The platform also needs to be able to adapt to change easily. Some platforms are agile and can be modified by internal teams, and others are more rigid and require vendor support or specific IT expertise. Naturally, a more agile system results in lower TCO.

Here are some key areas that you should look for:

  • The platform should be able to access and work with your current data warehouse and create reports in whatever format is needed.
  • It should interface with existing communication and imaging systems. If those systems change, it should be able to easily integrate with whatever new systems are chosen.
  • Especially important with respect to platform agility is the ability to adjust quickly and easily to compliance and regulatory changes.
  • Additional configuration changes should be just as easy and you should not have to rely on the vendor for implementation.

Security
Security is paramount in a modern collections platform. A single security breach not only adds extra cost, it can permanently damage a business’s reputation. Threats can come from internal sources as well as external—a robust security feature set that addresses both is important.

Important security features include:

  • Integration with all internal authentication mechanisms
  • Creation of granular user roles and access privileges
  • Encryption and masking for all data
  • Auditing and monitoring of all user activity

Costs Across the Lifecycle
Hidden costs in relation to flexibility and security can present themselves at any stage of the platform lifecycle—not just at one particular stage. To understand potential impacts to TCO it is important to look across the entire spectrum.

Organizations should then spend time determining the architecture of a platform to understand if it will introduce new risks at any of these stages because of its lack of agility. From a security perspective, organizations should research today’s standards across the platform lifecycle and then try to match them directly to the features offered by prospective vendors. Both of these steps will go a long way in assuring that the platform you work with provides the features needed to effectively safeguard against hidden risks and mitigate unforeseen costs.

There are many benefits that a modern platform can bring to a debt management organization. Effectively managing TCO by uncovering hidden costs can help an organization improve return on investment. You’ll want to partner with a vendor who will be transparent—one with the expertise needed to help you navigate common TCO pitfalls. To learn more about managing the TCO of a new collections platform, view our on-demand webinar.

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2016 UK Fraud Figures Show Disturbing Trend

Financial Fraud Action UK (FFA UK) recently released their 2016 UK fraud performance report. Whilst there were some logical changes between 2015 and 2016, I was surprised at the fluctuation and significant shifts fraudsters have made in order to circumvent existing controls. Here are some highlights and lowlights I took from the report.

Overall, UK fraud losses were up again and this is due to a combination of shifts between fraud types and an increase in the number of victims of fraud (cases). What did surprise me was the rate at which the gross losses increased compared to the value prevented had decreased. For example, Industry losses increased by £13 million (2%), yet the value prevented was reduced by a staggering £380 million (22%). This means that we prevented far less of the overall fraud attack in 2016 than we did in 2015.

Here are some other interesting stats:

Card fraud was up by 9% from £568 million to £618 million, and the number of victims increased by 22%, yet a large proposition of this was successfully mitigated. We have seen many of our clients upgrading their solutions over the past 12-18 months, and in particular to FICO Falcon Fraud Manager 6. This should be evidence that transaction detection tools are working.

FFA 1 2016 UK Fraud Figures Show Disturbing Trend

 
Remote banking fraud (via internet, telephone and mobile app) saw a 19% reduction. Case volumes remained flat compared to 2015 yet the losses went down by £32 million. Well done to the digital teams and security professionals out there for sqeezing the level of opportunity for fraudsters.

FFA 2 2016 UK Fraud Figures Show Disturbing Trend

Mobile banking fraud through apps, while part of remote banking fraud, rose 104%, the largest increase. It’s great to see the adoption of mobile banking apps increasing, but let’s make sure we keep a very close eye on this fraud type.

FFA 3 1 2016 UK Fraud Figures Show Disturbing Trend

Fraud has never been more cross-pollenated than it is now. Fraudsters are exploiting the customer instead of individual products. Social engineering ‘scams’ have never been more challenging. We always knew that fraudsters target the weakest link, and now that weakest link truly is us. It’s humans over technology, emotion and trust over malware.

Our focus should remain on tackling card fraud and e-banking risks. At FICO, we believe that the most effective way of fighting fraud is by having an enterprise fraud strategy. The FICO® Falcon® Platfom has the ability to combine fraud risk decisions at a customer level and removes the silos that have been in place for far too long. It’s not just about the transaction anymore, we have to consider all data sources.

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A New Way to Score Credit Risk – Psychometric Assessments

When young Russians apply for their first credit card at Sovcombank, they go through a fun, interactive survey that starts with the question, “How do you feel today?” What they’re doing is participating in a new type of psychometric credit scoring that could expand credit in markets worldwide.

The scoring methodology was developed by EFL Global and marketed by FICO as part of our FICO Financial Inclusion Initiative, designed to open up credit markets around the world to a larger number of unbanked and underserved consumers. Sovcombank, a universal bank with more than 2 million customers, is using the score to “gamify” the credit application process.

The EFL credit risk score is created through a dynamic behavioral design and psychometric assessment that analyzes character traits with a proven relationship to credit risk. It’s an ideal approach for applicants who do not have a credit history and therefore cannot be scored using traditional methods.

EFL 1 A New Way to Score Credit Risk – Psychometric Assessments

EFL has been part of providing more than $ 1.3 billion to nearly 1 million entrepreneurs and individuals around the world. Many of these people would have been unable to obtain credit by traditional means.

Gamification and surveys are fun ways to score people, but the approach itself is backed by rigorous science. EFL was founded in 2006 when Drs. Bailey Klinger and Asim Khwaja created the Entrepreneurial Finance Lab Research Initiative at the Harvard Center for International Development. This project set out to develop low-cost credit screening tools to help stimulate entrepreneurial finance in emerging markets by addressing information asymmetry.

Expanding credit worldwide

The innovative approach taken by EFL is one way we are working to facilitate credit access for the more than 3 billion consumers that are unbanked or underbanked.

EFL 2 A New Way to Score Credit Risk – Psychometric Assessments
Through the FICO Financial Inclusion Initiative, we offer new, innovative FICO solutions, which incorporate a wider range of data sources. We are also partnering with companies such as EFL that are committed to expanding credit access and have products that meet our strict expectations and requirements.

For example, when assessing a new data source or scoring approach, we apply a six-point test to make sure the approach will deliver in the real world. Many people think that all you need is a predictive score — in fact, that is just one of six characteristics a strong scoring system needs.

EFL 4 A New Way to Score Credit Risk – Psychometric Assessments

We apply a similarly rigorous approach when exploring alternative data sources for credit risk scoring. As part of this, we will look at the data hierarchy. Clearly, the most powerful data on credit performance is credit data, but where that’s not available, bill payment data, non-financial data, or consumer-contributed data will be relevant.  Any new solutions using alternative data — that is, data other than financial account data — require an empirical analysis of the value that data will bring for specific segments of the market.

EFL 3 A New Way to Score Credit Risk – Psychometric Assessments

The data evaluated and ultimately used in any FICO solution must always comply with territory-specific regulations in the country in which it will be used. Additionally, for data collected from mobile and social networks, the consent of the consumer is always received prior to use in any FICO solution.

It may be surprising to some that FICO, the world leader in crunching credit data, would sell a partner’s score that starts with a question on the applicant’s mood. But we feel this approach offers a whole new way to bring more people into the credit mainstream. Our work with Sovcombank is just the first in a series of exciting opportunities to progress this partnership in Russia and in other countries.

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EnterCard Moves Fraud Protection to the Cloud

EnterCard EnterCard Moves Fraud Protection to the Cloud

In another sign of the growing use of the cloud for fraud protection, EnterCard — one of the leading Scandinavian finance companies — will use the FICO® Falcon® Platform to combat card fraud and communicate with its 1.7 million customers.

EnterCard is upgrading to a cloud-based version of Falcon to protect customers in Sweden, Norway and Denmark from fraud.

“The cloud-based version of Falcon gives us greater flexibility to serve our customers with better fraud protection,” said Yannick Leclerc, head of fraud in EnterCard Group. “We will have greater control over how we communicate with customers when fraud is suspected, which will help us improve the customer journey in a fraud context.”

For more information, read our news release.

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Behavioral Analytics Attack Fraud, Cyber and Financial Crime

Analytics Hand Behavioral Analytics Attack Fraud, Cyber and Financial Crime

Economies of scale is one of my favorite economic principles. It’s especially cool to see how FICO customers can realize associated benefits by using our behavioral analytic technology.

IDC predicts that in 2017, behavioral analytics across compliance, fraud, and cyber detection and prevention will be in place at 15% of banks, helping them to avoid losses, regulatory fines and sanctions.

Banks have already made a big start in the fraud space. FICO introduced behavioral analytics in the early 1990s and we currently analyze two-thirds of the world’s payment card transactions, in real time, for fraud.

Now, FICO’s proven behavioral analytics can be applied by forward-thinking institutions to fight a wide range of financial crimes. In doing so, banks can gain powerful technology economies of scale, too, leveraging mature, market-proven analytic models to benefit new domains within their business.

How do behavioral analytics work?  

A quick search may tell you that “behavioral analytics” measure the behavior of consumers on ecommerce platforms, online games, web and mobile applications or Internet of Things (IoT) devices. In fact, “behavioral analytics,” from a pure data science point of view, help us to understand much more:

  1. what an individual person or device does, and
  2. what they don’t do, but might in the future.

The first comparison is of the customer or device in the context of their own history of events, where one can determine changes from historical behaviors. A second comparison is done by grouping customers or devices into similar clusters, and then analyzing how much the behaviors of individuals deviate from their associated groups.

Depending on the degree of variance, we can assess how likely the behavior is to be aberrant and thus potentially fraudulent or criminal — or, in the case of a network device, how likely that endpoint is to have been compromised by a cyber attacker.

Power at scale: Enhancing fraud, compliance and cyber security defenses 

Behavioral analytics are a mature technology in fraud prevention. Behavioral analytics technology allows us to flag potentially fraudulent transactions with pinpoint accuracy, greatly reducing the volume of “false positives,” or transactions flagged as potentially fraudulent that are, in fact, legitimate. FICO has honed its fraud detection technology to identify the needles in the haystack.

In terms of compliance — particularly anti-money laundering (AML) and terrorism financing — the most prevalent transaction monitoring solutions used to identify illicit activity in these domains are extremely imprecise. The compliance solutions generate tens of thousands of alerts for every genuinely criminal transaction requiring a formal suspicious activity report (SAR). The volume is so great that that compliance officers can only investigate a small fraction of suspected SARs. As a result, illegal transactions slip through, continuing through the global payments system.

It’s the same situation with cybersecurity. In any security operations center, there’s a cacophony of alarms, 24-7. It’s impossible for operators to tell which alarms are calling out truly meaningful intrusions, and which are just noise. That’s why so many cyber attacks go undetected for weeks, months or even years.

FICO solutions for compliance and cybersecurity address these shortcomings, dramatically improving the accuracy of AML detection and enabling real-time discovery of cyber threats.

Benefits beyond cost savings

As IDC noted, behavioral analytics technology can help financial institutions to avoid regulatory fines and sanctions. The benefits extend farther: in terms of fraud and compliance, behavioral analytics will allow more illicit transactions to be stopped as they occur, saving untold amounts of financial and reputational loss.

With regard to cybersecurity, the ability to pinpoint cyber attacks more quickly greatly reduces the “dwell time” of malware, ransomware and other malicious code that causes data breaches and other damage. Again, this can significantly reduce the costs of remediation that result from breaches, as well as major financial and reputational losses.

Want to know more? Check out my latest FICO Hot Topic Q&A, “Behavioral Analytics: Boosting Protection across Fraud, Compliance and Cybersecurity.” Follow me on Twitter, too, @ScottZoldi to keep up with my latest analytics rants, raves and musings.

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Examining the Credit Cycle: Is This as Good as it Gets?

More than 70 straight months of US job growth, the official unemployment rate down below 5%, and average hourly earnings growing at a seven-year high of 2.9%. Signs of approaching full employment finally allowed the Fed to see enough stability to inch up rates without being seemingly blown off course by events elsewhere. There will be more rate hikes to come if the economy stays on this course, and in the event the deficits grow, it will pretty much guarantee what we already expect on the interest rate front.

With all this in mind, it’s a good time to ask: Has the US credit cycle reached the bottom? Is it as good as it gets?

Of course, we never know that for sure. This is all opinion (some would say speculation), especially on the economic policy front. But you have to feel that if it isn’t the bottom we are not far off.

Take a look at delinquency stats.

Credit Cycle Delinquency Rates Chart Examining the Credit Cycle: Is This as Good as it Gets?

All of these figures are based on a two-year outcome. Thus, the scoring date for the October 2016 figures would be October 2014.

The most interesting observation is the uptick in origination delinquencies, which we see across the board relative to 2013. Compare that to the broader population, where we see the generally benign to improving economic environment continues to push down rates. (Originations here are trades opened within six months of the scoring date.)

Of course, these figures don’t allow us to separate deterioration from laxer credit standards. It’s fair to say that the latter almost certainly is a key contributor.

In the major product categories, the picture is mixed. At least at the top level, the lid still seems to be on the mortgage market, where delinquency rates remain low. In the card and auto worlds, rates are still a long way below the dark days of 2008 but are up among younger borrowers.

Do YOU think today’s credit cycle is as good as it gets? I invite you to make your case in our comments section.

The truth is that we will only know when we look back and say “I told you so!” For now, the signs suggest we are near that point, and we should keep our eye firmly on the horizon to understand which way this is headed.

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