Tag Archives: loan

How to Create Risk Transparency

There was a time not long ago when a bank originated a loan and kept that loan on the balance sheet until it was repaid. The amount banks could lend was limited to the deposits they had on hand and the banks’ own ability to borrow. Today, credit risk is traded regularly, with specialized data and analytical services giving investors confidence they understand the risks they are assuming. But there has been limited opportunity for investors to deploy capital against specific pools of insurance risks, because of a lack of that sort of transparency. With the vehicles that do exist, it has been difficult to structure the transfer of risk to meet investors’ respective objectives and risk tolerances.

However, insurance may be reaching a point in its evolution where the information gap will begin to narrow. Up until today, insurance risk had often been opaquely and highly subjectively valued. Today, actuaries set reserves based on highly summarized data, and underwriters set premiums based on claims experience that is extrapolated forward using historical loss development patterns and subjective future “trend” projections (or ad hoc substitute measures for risk), neither of which may represent future risk of loss. Outside of property catastrophe risk, where the data elements are generally available in some detail, granular risk data simply has not existed. However, rapid change could now be approaching. Vehicle telematics, wearable sensors, connected machines and other components of the Internet of Things (and Beings) are producing real-time data that allow us to look at risk in real time, rather than relying on current industry practices.

See Also: A Better Way to Assess Cyber Risks?

Credible, data-driven risk indices may create a variety of opportunities, including:

  • Capital Providers: Investment in specific index-based structured insurance pools that are aligned with respective objectives and relative risk tolerances could improve on the alternatives available today, where those who want to invest in insurance risk are often restricted to investing in insurance companies or risk pools that involve assuming underlying exposure to the operational, asset and credit risk, as well as the insurance risk of the originating insurer’s business.
  • Insurance Clients: Clients are likely to observe premium and associated underwriting decisions more transparently and could thus anticipate the cost/benefit implications of decisions taken to reduce risk.
  • Regulators: Regulators could gain greater confidence in the balance sheet valuation disclosed by insurance companies, which has the potential to decrease the regulator’s view of risk capital necessary to support risk.

One could argue that straightforward consumer and commercial loans are much simpler than the risks underwritten by insurers. However, when taking a critical look at the complexity of the financial projects currently being traded by investors, that notion is hard to support. In fact, many of the underlying risks facing lenders are very closely related to the risks facing insurers. Perhaps the biggest differentiating factor is the lack of standardization of contracts, which creates a degree of complexity.

From a contractual perspective, however, complex derivatives, other hard-to-value instruments and non-transparent assets can be at least as opaque and complex. Yet the core elements for assessing risk are available, and credible calculations exist within the valid range of assumptions.

The insurance industry could benefit from the increasing availability of relevant data. That data could be the byproduct of other applications, such as route data from fleet management software; vehicle data from predictive maintenance applications; traffic density data from road management applications; or environmental data from various sources. Or, it could be data that has been custom-generated for insurance applications, such as the data from telematics devices used by personal auto insurers to capture driving behavior. I see the biggest promise in using the data exhaust from other applications. I suspect clients would be averse (in many cases) to additional data capture specifically for insurance but would be open to sharing data already captured—as long as there are appropriate safeguards to ensure that it does not disadvantage them as clients.

The industry will need to invest in new analytical techniques to leverage these new data sources. In many other sectors of the economy, “big data” is having a real impact. This has required new tools and algorithms that might be unfamiliar to most analytical professionals within insurance. David Mordecai and Samantha Kappagoda, co-founders of the RiskEcon Lab at Courant Institute of Mathematical Sciences, which is among the world’s leading applied mathematics and computer science research institutions, explained the necessary evolution:

“The increasingly pervasive proliferation of remote sensing and distributed computing (e.g. wearable tech, automotive telematics), and the resulting deluge of ‘data exhaust’ should both necessitate and enable the emergence of digitized risk management programs. Ubiquitous peer-to-peer interactions between human ‘crowds’ and machine ‘swarms’ promise to dominate commercial and consumer activity, as already observed within omni-channel advertising exchanges and high-frequency algorithmic stock trading platforms. Financing and insurance functions involving risk-transfer, risk-sharing and risk-pooling will increasingly be facilitated by and executed seamlessly within code. Among others, Bayesian statistical and adaptive process control methods (e.g. neural networks, hidden Markov models)—originally employed within the telecommunication, electricity, chemical industry and aviation during the mid-20th century, and more recently adapted for voice, visual and text recognition, along with other supervised and unsupervised data mining and pattern recognition methods—will need to be widely adopted to identify, monitor, measure and value underlying risk factors.”

In my opinion, new data and new techniques are likely to create a degree of transparency in insurance risks that has never existed. That transparency could benefit capital providers (both insurance company investors and direct investors in insurance risk), clients and regulators. A new era is quickly approaching where information and analysis have the potential to remove the cloud engulfing insurance risk. There are likely to be substantial benefits for those forward-thinking companies that exploit the opportunity.


3 Questions About On-Demand Economy

Last year, as Airbnb’s $25.5 billion valuation surpassed Hilton Hotels’ and Uber became the world’s most valuable privately owned company, it became clear the on-demand economy is no passing fad but is, in fact, a force to be reckoned with.

The on-demand marketplace is growing at a dizzying pace as new companies emerge daily, helping connect a diverse workforce of tradespeople, licensed professionals and unskilled laborers to a market of willing buyers through the company’s platforms. Intuit projects the population of U.S. on-demand workers will more than double by 2020, which means that, if you can’t already summon a doctor, lawyer, babysitter or dog walker right now via an on-demand app, then sit tight—they’re coming soon to a smartphone near you.

But the scale and speed of the on-demand economy’s growth also means policymakers, regulators, insurers and on-demand companies will have to huddle quickly to resolve the issues that arise with this expanding marketplace and its workforce. Here are the three key questions we need to address immediately:

  1. When the safeguards of the traditional corporation no longer exist, how do we protect the on-demand workforce?

Uber is currently appealing a case it lost against the California Labor Commissioner last summer regarding whether a driver is an independent contractor or an employee. While establishing this distinction is a critical issue, we still need to address some big questions about the vast self-employed workforce in the on-demand economy.

A good primer question: How do we get the information we need to make informed policy decisions? Independent contractors in the on-demand economy are classified as part of a larger pool of temporary, seasonal, part-time and freelance workforce called “contingent” workers. A 2015 U.S. Government Accountability Office report cites this workforce as somewhere between less than 5% and more than one-third of the country’s overall labor pool. The big gap in this measurement is because it depends on how jobs are defined and on the data source; the broad definitions and lack of clear data on this workforce makes on-demand independent contractors and their needs tough to track and evaluate. How much of this workforce depends on this income for supplementary purposes as opposed to relying on this income as a full-time living?

According to Intuit’s study, contingent workers will make up 40% of the U.S. workforce by 2020. That’s a lot of people working without the safeguards provided by the traditional corporation—guaranteed minimum wage, steady income, unemployment insurance, healthcare, workers’ compensation and disability insurance. What kind of safety nets do we need to put in place to protect this workforce? And what does this growing workforce mean in terms of policy development? How does the social contract change?

  1. How should we regulate hybrid commercial/consumer activities?

A sticky issue surrounding the on-demand economy is how to regulate commercial activities that are conducted by individuals rather than by traditional businesses.

While some argue that an Airbnb property should be as heavily regulated as a hotel if a host is accepting payment for lodgings, drawing an apples-to-apples comparison between the two is a challenge. For example, treehouses, yurts, igloos and lighthouses were among the top-10 most desirable vacation destinations on Airbnb shopper’s wish lists last year, some fetching upward of $350 a night. Who exactly should you call about making sure the igloo is up to code before guests arrive?

Some of the services and products offered by the individual through on-demand platforms have never been available through traditional enterprises; they’re unique, intimate experiences and, before on-demand platforms made them accessible, were difficult to find. We’re entering a new frontier where many tourists covet a culinary experience they can book at a local’s house via apps such as Feastly or Kitchensurfing rather than a fine dining restaurant, or they prefer offbeat accommodations booked through Airbnb to a 5-star hotel. We can’t assess how to best regulate these individual commercial activities until we have more data and understand the risks. How do we collect that data? How do we ensure the safety and protection of the individuals operating and participating in these activities until we have the information necessary to adequately regulate them?

  1. How can a square peg workforce function in a round hole system?

Mortgages, loans, credit cards, leases … these are just a few of life’s niceties (or necessities) that are challenging for an on-demand independent contractor to secure. Our current financial services, systems and policies were built to work for employees who collect a regular paycheck as well as freelancers who have reliable cash flow through long-term contracts and monthly retainers. Independent contractors working through on-demand platforms tend to rely on short-term gigs often generated through multiple sources, and they have difficulty predicting their day-to-day income, never mind their annual net or gross.

This isn’t a niche workforce. If independent contractors represent 40% of the U.S. working population in 2020, they’re significant drivers of the economy. They generate income and pay taxes; they need homes, cars, work equipment and all the other stuff that keeps their businesses running and makes their lives worth living. We can’t dismiss their needs, because we are measuring their 21st century income with a 20th century yardstick. How do we retrofit our round-hole systems to include this square peg workforce?

If we want a thriving economy in which people enjoy the benefits of the on-demand economy, and doctors, lawyers, drivers, plumbers and everyone else serving the on-demand marketplace have equal opportunity to succeed, then the time to talk about these questions and issues is now.