Tag Archives: natural disasters

Another Rough Summer Ahead?

When I checked the weather for my town in Northern California over the weekend, I saw a “red alert.” What? Sure, it was windy and a bit warm, but a red alert? For what? It turns out that we’re already in fire season: Low humidity, high temperatures and strong winds meant severe danger for wildfires. At the beginning of May.

At the same time, all forecasts seem to be for an unusually active hurricane season in the Atlantic this summer. So, buckle up. As bad as the past few years have been, there’s no reason to think this summer will bring any relief from natural disasters in the U.S.

This forecast on hurricanes calls for not only the sixth consecutive year of more hurricanes than average — following a year when there were so many tropical storms that they ran through the entire alphabet of designated names and made it deep into the Greek alphabet — but also for more that will make landfall in the Caribbean and along the U.S. coast. The reasons for concern are that the La Nina weather pattern is expected to last into the early summer and that sea temperatures are well above average in the Caribbean and Gulf of Mexico.

While wildfires are harder to predict, this Washington Post article reports that structural changes in the weather are making California more vulnerable. The big issue is that the dry season, which lasts roughly from late spring to late fall, is expanding, according to analysis from weather stations around the state from the past 60 years. For instance, Sacramento, near where I live, has seen the onset of its rainy season delayed by three weeks just since 1979. San Francisco has had its dry season expand by 14 days.

About 4.2 million acres burned in the state last year, an area larger than Connecticut and twice as extensive as the previous worst season on record. (In a bizarre story, authorities allege that one of the major fires was set by someone who had killed a woman and wanted to hide the evidence of how she died; the fire killed two men whose homes lay in its path.)

It’s been a dry winter, so who knows how bad this year will be?

Technology is finally being deployed that uses sensors to track the progress of fires and help with deployment of resources — firefighting has been described as “100 years of tradition, unimpeded by progress” — but that seems to be a few years away from making a major difference.

For now, we seem to need to brace for a wet, stormy summer in the Caribbean and along the Atlantic coast and a long, hot summer in my neck of the woods.

Keep your fingers crossed.



P.S. Here are the six articles I’d like to highlight from the past week:

Gateway to Claims Transformation

Claims management is a perfect use case for just how critical platforms and ecosystems can be in achieving transformation.

Nonstandard Auto Insurance’s Key Role

Customers, insurance carriers and their distribution need nonstandard auto protection for drivers now more than at any time in history.

Transformation of the Risk Landscape

Insurers of all sizes need to take note of changes in the risk landscape and continuously improve their ERM practices.

Bring Certainty to Remote Injury Claims

The reality is that injuries occur all the time in any environment, at home just as they do in a conventional workplace.

Way Beyond Comparative Raters

Distribution in commercial lines is in play. Companies are rethinking strategies to reach preferred segments and drive more profitable business.

How Well Did Agents Cope With COVID?

Both brokers and carriers give themselves high marks on retaining and servicing existing policyholders. But new business is a different story.

How CAT Models Are Extending to Cyber

The insurance industry relies heavily on catastrophe modeling to set capital adequacy, adhere and respond to evolving regulatory requirements and stress test portfolios. The same is now increasingly true of the cyber catastrophe sphere, in which key areas of focus include how models can help with capital allocation, stress testing and informing development of underwriting guidelines and insurance products. Parallels can be drawn from the cyber catastrophe and natural catastrophe risk management sectors when modeling these risks.

The introduction of models provided critical insight into the potential for catastrophic claims for all risk policies or policies without clear exclusionary language. Historical events such as the April 1906 San Francisco earthquake (leading to unanticipated claims for fire policies), 2005 Hurricane Katrina flooding (resulting in unanticipated claims for homeowners wind policies) or the 9/11 U.S. terrorist attacks (experiencing unanticipated war exclusion interpretation and definition of a single event), and the current unfolding of the coronavirus pandemic crisis highlight the criticality of understanding the triggers and correlation of potential loss due to a single event.

In many cases, insurers paid losses to avert “reputational risk” and have since used models to provide insight into realistic structuring of policy, reinsurance and other risk transfer vehicles. Clear exclusionary language, endorsements and coverage-specific terms evolved over the decades in concert with evolving scientific knowledge of the risks and modeled loss potential. 

Today, we are seeing the same evolution with respect to insuring cyber risk, but over a highly compressed period, without the decades of experience of systemic insured loss events. Many cyber catastrophe risk managers attempt to apply the same lens of current natural catastrophe model availability of data resolution, data quality, catastrophic event knowledge and model validation expectations. But by embracing the commonality of lessons learned from the evolution of the property catastrophe insurance market, we can prepare for an event considered to be a case of not “if” but “when.”

The role of data in models

A first common theme is to recognize that the understanding and availability of information for a rapidly evolving risk means that there is value in aggregate data in the absence of detailed data. This has been and is still the case for property catastrophes and is also the case for cyber catastrophe risk models. Confidentiality obligations in portfolio data as well as the lack of high-quality data is an issue for all models. However, new sources of data as well as sophisticated data science and artificial intelligence analytics are being incorporated into models that provide an increased confidence in assessing the potential risk to an individual company or entity. 

See also: Coronavirus Boosts Cyber Risk

A second related common theme is the ability of catastrophe risk models to augment lack of risk-specific data capture at the time of underwriting. This is where all catastrophe risk models add significant value, where context for what should be captured as well as what can be captured is provided. In the case of cyber, this can include access to both inside-out (behind the firewall) and outside-in (outside the firewall) data. Inside-out data refers to aggregate data for segments of the economy, measuring the anonymized trends of security behaviors (such as frequency of software patching). Outside-in data is made up of specific signals that can be identified from outside an organization and that give indications of overall cybersecurity maturity (such as the use of unsupported end-of-life products). 

A third commonality is the value in extrapolating the impact of past events into the future given evolving available data on the changing causes of frequency and severity of cyber events. The property catastrophe arena is grappling with very similar issues relative to the rapid and uncertain evolution of climate models. For cyber risks, history is not a predictor of the future in terms of modeling threat actors, the methods they deploy and the vulnerabilities they exploit. However, it is possible to examine historic data and the types of cyber incidents that have occurred while addressing the challenges in the way that information is collected, curated and used. This historic data is used against the backdrop of a near-term threat actor and technological trends to understand future potential systemic losses due to large-scale attacks on bigger and more interconnected entities. 

The role of probabilistic models

At the enterprise level, the market is struggling with how to assess potential aggregations within and across business lines. Event clash due to a single event causing multiple loss triggers to policies and reinsurance treaties is a key concern across all lines of business. Use of common cyber and other catastrophe risk loss metrics that can be combined across perils and lines of business are being explored. In addition, regulatory groups are considering requirements similar to property catastrophe risk to address solvency requirements relative to cyber risk. 

In this environment, consistent and structured definitions of risk measures are critical for assessing and communicating potential systemic catastrophic loss. Both deterministic cyber scenario event analyses as well as probabilistic stochastic cyber event analyses are required. Given this context, cyber catastrophe risk models that can withstand validation scrutiny similar to property catastrophe risk models require the same level of rigorous attention to transparency in communication of model methodology.

Similarities… but some differences

There are some key differences between the systemic risks of natural disasters and cyber events. One material contrast is that cyber perils manifest with active adversaries seeking to cause malicious damage to individuals and companies globally. The factors affecting modeling include the changing nature of geopolitical threats, the dramatic increase in the use of digital means for criminal enterprises, the hyperconnectivity of developed economies and an ever-increasing reliance on networked technologies. Cyber event scenarios are developed to represent a range of potential systemic events in which technological dependencies affect individual insured companies, due to a common vulnerability or a “single point of failure.” Examples include common cloud service providers, payment systems, mobile phone networks, operating systems and other connected technologies. 

See also: Risks, Opportunities in the Next Wave  

There are limitations in any model relating to cyber risk, given the inherent uncertainties. Nevertheless, these models provide valuable insights to better decision-making relating to capital planning, reinsurance and addressing regulatory issues. By learning from previous insurance shocks, we can support a more stable and resilient cyber risk insurance market.

New Era in Modeling Catastrophic Risk

The 2018 hurricane season opened with the arrival of subtropical storm Alberto on the coast of Florida. Natural disasters such as these regularly imperil human lives and trillions of dollars of infrastructure. Although we can’t stop them, we can limit their financial repercussions through the development of more accurate predictions based on an updated approach to modeling catastrophic risk.

The Flawed Assumption

Stationarity is the name for the concept of data remaining unchanged—or stationary—over time. When applied to climate science, it refers to the assumption that the earth’s climate is not changing. The vast majority of climate scientists believe the stationarity assumption is incorrect, and any approaches based on this assumption are fundamentally flawed.

Yet traditional catastrophic climate risk models are built on the assumption of stationarity. They project the future based on past statistics and the assumption of a static climate. Insurers actually use this approach with reasonable success for regional, national and international insurance policy portfolios. However, when stationarity is applied to risk analyses for specific structures or large commercial properties, the model breaks down.

Localized Assets

The problem is that risks to localized assets are not homogeneous across regions and properties. Localized predictions require data that accounts for the dynamics of the local environment.

Those dynamics include not only a changing climate but human-engineered alterations, as well. Simply breaking ground for a new building affects potential flooding scenarios. To accurately assess and mitigate potential risk, developers, municipalities and insurance companies need models for the individual block and street and are not constrained by stationarity.

Creating a dynamic model that collects and analyzes data with such localized resolution is not a simple matter of “downscaling” old methods. It requires a different strategy and discipline, with single-site analysis as a core objective.

See also: Role of Big Data in Fighting Climate Risk  

Risk Modeling Reimagined

Incorporating natural and human-architected factors in a dynamic, integrated model is fundamental to an asset-focused solution that delivers accurate, actionable information. Such a solution requires comprehensive and current data, powerful big data analytics and a flexible design that can easily incorporate new modeling techniques as they become available.

At Jupiter Intelligence, our solution is built on a cloud-based platform designed specifically for the rigors of climate analysis and links data, probabilistic and scenario-based models and advanced validation. ClimateScore runs multiple models based on a changing climate, such as weather research and forecasting. ClimateScore’s models are continuously fine-tuned using petabytes of constantly refreshed data from millions of ground-based and orbital sensors. Novel machine learning techniques reduce local biases of scientific simulations and help the system continually improve as new observations become available.

Forgoing stationarity and adding the flexibility of a cloud model, current data from multiple sources and state-of-the-art analytics, machine learning and artificial intelligence technology produces asset-level predictions that are accurate from two hours to 50 years in the future.

Case Study: Miami

Understanding how developed Miami’s coast has become with localized data down to the individual block and street can help insurance companies, municipalities and developers assess the potential risk and determine cost-effective solutions.

Engineering firms need this data to evaluate the potential effects of flooding at a particular site and simulate how effective individual coastal protection measures are in protecting properties and neighborhoods from flooding over the life of these structures.

Public agencies also need this granularity to figure out how vulnerable their assets (ports, airports, transit, waste water treatment and drinking water facilities) are to a changing climate. Similarly, private entities want to assess exposed assets (substations, buildings, generators and data centers) and critical systems that may need to be redesigned to handle changing conditions. One critical condition to evaluate is the capacity of the electrical grid to handle peak demand during longer and more intense heat waves.

See also: Low-Risk Doesn’t Mean No-Risk 

New Risk-Transfer Mechanisms

Stationarity-based catastrophic risk models were never intended to assess risks to specific assets. To mitigate asset-level risk, all aspects of the private sector, as well as government bodies at the international, national and local levels, must make informed decisions based on accurate, current, highly localized data.

Property values, liability risk and lives are at stake. With dynamic models, current data and modern analytics, mitigating risk is feasible. This type of information resource also will support new risk transfer mechanisms, including private insurance—and help reform obsolete mitigation strategies.

This article was originally published at Brink News, here.

Natural Disasters and Risk Management

For many people, their first thought about natural disasters is the devastating property damage that is extremely visible and highlighted by the media. However, the impact of natural disasters goes far beyond property damage and includes the impact to your workforce, your supply chain and the operations of your business.

During a recent Out Front Ideas webinar, we were fortunate to get the perspectives of leaders from three different segments of our industry on the impact of natural disasters on risk management. Our guests included:

  • Tom Best, deputy general counsel for Home Depot
  • Ryan Brannan, commissioner of workers’ compensation for the Texas Department of Insurance
  • John Hinz, vice president of Vericlaim

Types of Disasters

There are two basic types of natural disasters – those with warning and those without. With hurricanes and flooding, you typically have some degree of warning that allows you to initiate disaster response protocols and to prepare for the disaster. However, with events such as tornados, earthquakes and other sudden events, there is no warning and no opportunity for advance preparation to minimize the impact and maximize the response. Both types of disasters benefit from developing a disaster response plan in advance.

Workplace Injuries

One of the first employer concerns has to be preventing and responding to employee injuries when a disaster occurs. At Home Depot, they work with vendors on a daily basis to identify any potential weather that could affect their stores. When there is a potential event, they pull together their response team, led by a disaster captain. Their response team has functional members of all their critical business areas, including human resources, legal, supply chain and business operations. These teams meet every year before the start of hurricane season to make sure everyone understands their role and the disaster response protocols. They also connect with state, local and federal authorities to coordinate response efforts. Because Home Depot has a very important community role in disaster preparedness and response, they keep stores open as long as possible and reopen them as soon as possible.

From a workers’ compensation claim standpoint, there are many concerns. Employees can be injured during the disaster itself. There is also significant potential for injuries sustained by first responders and the National Guard during the response and recovery. Texas deployed 14,000 National Guard troops in response to Hurricane Harvey, and those troops are all considered employees of the state of Texas when deployed. Traumatic physical injuries are not the only concerns. There are also occupational disease concerns because of the toxic chemicals that were in the floodwaters of Houston. Furthermore, there are concerns about post-traumatic stress. Because of the occupational disease exposure, there could be a very long claims tail from this natural disaster.

Workforce Disruption

Home Depot is a major employer, but they are also an essential element in any disaster response because people depend on them for building materials and other supplies. Their command center is focused on taking care of both their employees and the community as a whole.

The Texas Workers’ Compensation Commission closed five field offices at various times in response to Hurricane Harvey. Their primary focus was the safety of their staff, but they were also concerned about being able to conduct the business of the commission.

See also: 6 Reasons We Aren’t Prepared for Disasters  

It is important to give your employees time off during a natural disaster to take care of their families and personal needs. Employers often bring in workers from other locations to assist in the affected areas so that the employees living in the area can tend to their personal needs first, then come back to work when able to do so. This allows the business to continue serving the community while also making sure that employees are settled.

Workers’ Compensation System Impact

Keeping the workers’ compensation system running during a natural disaster is important and challenging. In Texas, the governor suspended certain regulations and extended or tolled deadlines in affected areas to ensure that workers were receiving timely care and benefits and that carriers were focused on benefit delivery instead of bureaucratic issues. Social media was very useful in keeping people updated on when field offices were open and providing other important information to all stakeholders.

Healthcare Impact

One thing people do not often think about in natural disasters is the impact on the healthcare delivery system. The healthcare delivery system is disrupted in many ways:

  • Technology: With electronic medical records and a wide variety of equipment powered by electricity, a prolonged period without power can make delivery of care very challenging.
  • Continuity of care: Patients are often forced to treat at facilities outside their areas during natural disasters. Facilities need to not only be able to handle the influx of patients, but to deal with the potential HIPAA considerations.
  • Supply chain: One impact of the hurricane that hit Puerto Rico was a significant disruption to the pharmaceutical industry, which accounts for more than 70% of Puerto Rico’s exports. There was a nationwide shortage of saline IV bags after the hurricanes, for instance, because most of these were manufactured in Puerto Rico, and those factories were shut down for a time.
  • Life and death issues for patients: During Hurricane Katrina, healthcare workers and patients in New Orleans were trapped for many days without power. Providers had to make decisions around which patients to evacuate first and which patients were in such bad shape that they could not be saved.
  • Litigation costs: There is always a big spike in litigation against healthcare facilities following a natural disaster because of care disruption and other challenges.

Supply Chain

Supply chain is important to most businesses, and a natural disaster can significantly disrupt the normal supply chains. This was especially challenging on an island like Puerto Rico. Getting the supplies to the island was only the first step. Supplies sat for days in the ports because there were no dock workers to unload them and no trucks to deliver them. There are many lessons to be learned about disaster responses to islands after the events of 2017.

On the mainland, supplies can be staged out of harm’s way in advance of a hurricane so that the trucks can start rolling in once the area is safe. Additional products are purchased in advance so there are ample supplies available. Home Depot works with local, state and federal authorities to coordinate the distribution of disaster relief supplies.

Disaster Preparation

Mitigating the risks and challenges from disasters takes extensive planning and practice. Every location and each facility is different and has varying needs. But as John Hinz explained, planning for emergencies can be the difference between staying in business and losing everything. There are several essential elements that should be included in any emergency preparedness plan.

  • Focus on prevention: If there is any way to prevent a disaster from happening, that is your best defense. The first step in the process is to assess your risk and the potential impact to see how you can be more effective in disaster planning. Once you know the type of disasters for which you are most at risk, take steps to minimize potential damage to your facility and harm to your employees. Think of the actions you might need to take and what you would need in the event of a fire, flood, severe storm or other disaster.
  • Evacuation plan: Every facility should have primary and secondary routes and exits that are well-lit, marked and easily accessible. There should be an outside area designated as a meeting place for employees to gather once they are out of the building. Staff members that may require assistance during an evacuation due to physical limitations should be noted in the plan.
  • Communication: In addition to emergency contact information for local police, fire and ambulance numbers, you should have a contact list that also includes information for your customers, suppliers and distributors. This list should be updated continually, and copies kept both in your files and in offsite locations so you will be able to access them regardless of the situation. You may want to preset conference call numbers in case that is needed. Be sure you have a way to contact key players in and outside the organization.
  • Protect vital company information and critical data and programs that are imperative to keep your operation running. Make sure these things are backed up and that the backup is kept in a location separate from the primary facility.
  • Understand your insurance coverage: Review your insurance policies with your agent or broker so you know your deductibles and how they are applied to your coverages. You should know the limits and nature of your insurance, including coverage specifics. You may want to make changes to some policies, as all coverages are subject to limits and exclusions.
  • Keep insurance information handy: The names and numbers of your insurance representatives should be kept in a safe, accessible place, as this will expedite the claims process when the time comes.
  • Plan for contingencies: Despite your best efforts, your preparation may not be enough. Have an offsite location or allow personnel to work from home, if necessary, to keep the business running.

See also: Cognitive Biases and Risk Management  

Final Thoughts

There is no foolproof plan that will protect your organization from every disastrous situation, but you can be well prepared for most emergencies. If your company does not yet have such a plan, you can work with carriers or agents and brokers to begin the process. There are also a number of consultants that specialize in this area.

After developing a disaster preparedness plan, you need to continually review and update it to make sure that it is current and that everyone understands his or her role if there is a disaster.

You can listen to the archived Out Front Ideas with Kimberly and Mark webinar on this topic here.

Why #Insurtech Doesn’t Matter

Last week, I included my summary of what we do in Insurance:

Insurance is a business where we provide people with peace of mind, allowing them to know that there will be a monetary solution provided when they suffer a major loss/accident (or minor, depending on coverage purchased). This loss/accident can either in the form of health, death or to some sort of property, and the solution is at a time when a person typically needs it most. That is the core of our business. 

This summary also relates to the three pillars of Insurance, which I mentioned a few weeks ago:

  1. Pricing –  Was the policy I purchased priced properly to take care of the costs of the insurance company running its business, and will it have enough?
  2. Reserves – to pay my
  3. Claims – in a timely manner.

As with many of us, I read and follow a lot of news on insurance and insurtech. Every day, my LinkedIn feed and email inbox is flooded with insurtech news, including new investments in startups, new insurtech partnerships formed, expansion of startups into new markets/states, etc.

I love reading all of this – as it shows the growing level of awareness of how new technology solutions can enhance the customer experience and also help companies with operational efficiency.  I am a huge fan of what the future entails.

However, I am also cautious of the risks currently present in the world of Insurance (and the world in general!).

See also: Insurtech Innovator – CyberWrite  

Currently, the pace of change and adoption of insurtech solutions is faster than ever before. It seems there are no signs of slowing down. However, as with any good plan, it is important to have risk mitigation and contingency plans.

The new technology solutions that we are building for the insurance industry (i.e., insurtech), are just an enabler. It’s not that these solutions don’t matter…. But, if the risks are not managed properly and plans are not in place for these solutions, then the progress of the many insurtech initiatives may slow down, or in some cases, not be around to matter.

What are some risks as it relates to insurtech? I will focus on three, which have been themes in the news for the past couple of months. In fact, these are risks that exist in our industry regardless of insurtech.

By no means are these the only risks that need to be mitigated, yet I do see these as some of the big ones:

  1. Macroeconomics
  2. Weather/Natural Disasters
  3. Regulation


Since 2008, global stock markets have been on a tear. It’s no wonder that there is so much money pouring into insurtech investments.

What happens if there is a market correction and we go into another global recession? Will we see the same sort of investment in insurtech solutions as we have been seeing?

And that’s just the equities market. What about fixed income?

In this FT article from August, Chubb’s CEO Evan Greenberg warns about the low interest rate environment and its effect on insurers. He says, “Many companies are not earning their cost of capital — and many are losing money, or will lose money in the future.” This is a big deal. This may have an impact on an insurer’s ability to pay claims in the future. Obviously, insurers will have to keep their solvency requirements due to regulation, but if this continues, we could see massive premium increases for customers and withdrawal from certain product lines.

Stock markets and fixed income aside, the next big risk that could affect the progress in insurance and insurtech has to do with climate change.

Weather/Natural Disasters

Over the past few months, we have seen Hurricanes Irma, Maria and Harvey ravage much of the Southeastern U.S. and islands nearby. California has been blazing in fire. In other parts of the world, there have been many natural disasters, too. I’ve seen a number of articles on this subject. They range from “how to claim from your insurance company in wake of natural disaster” to “how much insurers will be out of pocket for weather-related claims.” With climate change increasing, the unknowns also grow. I’ll admit, I’m not an expert in catastrophe pricing, but I would suspect that this increasing factor will make it much more difficult to price products.

So, equities may fall. Interest rates may not come up. And natural disasters could be on the rise. These risks are big, but the last one could take the cake: regulation.


President Trump has signed two executive orders – one that will allow customers to purchase cross state border and one that limits funding for Obamacare (though that has seemed to change course).

The impact that these have on the U.S. healthcare and insurance market is unknown for now. This is a topic that deserves its own write-up, and I plan to cover this sometime in the near future.

Regulation can really screw things up; if not looked at properly. I wrote about government collaboration a few weeks ago. Some governments are more open to collaborating with incumbents to better understand fintech and insurtech. However, for those of us who have worked with regulators, we know that their minds can change quickly, and knee-jerk reactions can be made, forcing our plans to change.

Different product lines have different opportunities and different risks

For some lines of insurance, mainly P&C, insurtech has a huge play, and there are many opportunities to disrupt and change the current Insurance value chain. If autonomous cars come into existence, the whole auto Insurance industry will change. For property insurance, smart homes and devices to monitor buildings will help to better optimize pricing and policies for consumers.

For travel Insurance, insurance to protect material objects (mobile phones, electronics, etc), UBI and insurance for the sharing economy, there will be opportunities to disrupt and enhance the customer proposition, too.

For life, health and catastrophe, it becomes a different story.  We see a lot of term life online, but what about whole life, universal life, annuities, etc? What about other, more complex products for individuals/businesses (disability, long-term care, commercial)?

See also: Innovation — or Just Innovative Thinking?  

My biggest worry comes from within these types of products. My years in insurance have primarily been on the life, health and annuities side. The pricing structures of these types of products have a longer tail than P&C. Health is annually renewable, but the cost of healthcare and frequency of visits to doctors have been increasing, which will make pricing more difficult.

So what can we do about this?

First and foremost, every startup and incumbent needs to have a risk mitigation strategy and contingency plan as it relates to their insurtech initiatives. It is easy to get caught up in the excitement of what we are doing, and talking about risk is not always the most fun. The risks above are just a few macro ones. Each company and each initiative will carry its own set of risks, which need to be assessed accordingly.

Second, collaboration continues to be key. Especially cross-border collaboration. We need to share best practices globally. Regulators will also need to continue to work with incumbents and startups to understand the solutions being put in place and risks to customers.

Third, actuaries need to get with it – quick. They need to use their skills of actuarial modeling and work with the data scientists out there to better understand all the data points available to them and how this can be incorporated into pricing models.

The marrying of actuarial pricing principles and data science will be one of the most powerful forces of change in our industry. Incumbents have been managing risk for hundreds of years. The nature of managing risk has changed with the explosion of data. It’s no longer about just looking at what has happened in the past and predicting what will happen. Let’s also get underwriters in this conversation.

We need to find opportunities to know what is working where, and what is also not working, so we can plan accordingly. We are all in this together, and we need to help enhance our industry together. We all have a collective responsibility, ultimately, for our customers.

This is a repost of my article on Daily Fintech. I look forward to reading your comments on this article and engaging in some discussion.