Tag Archives: risk framework

Digital Insurance, Anyone?

The digital banking conversation is alive and kicking within the FinTech world, focused on discussing the merits, definitions and initiatives around what it means for a bank to become digital across its entire technology and business stacks. I have yet to find the same level of discourse and vibrancy within the insurance world.

Spurred by Yan Ranchere’s latest blog post, I am adding my own thoughts to the insurance narrative or, dare I coin it, the “digital insurance” narrative.

First, let’s frame the discussion by attempting to define the evolution of the insurance model from old to current and future or digital:

Old Insurance Model:  This model is mostly paper-based with an application collected from the customer by the agent and sent to the carrier. The agent quote is not binding and may indeed change once the carrier has reviewed the application. I would qualify this model as carrier-centric. The carrier does all the heavy lifting with data verification and underwriting, with little stimuli from external data feeds in real time; the agent merely serves as a conduit.  As result, underwriting and closing a policy may take several days or even several weeks.

Claims management and customer service are cumbersome. Arguably, this delivers poor service in today’s age of instantaneous expectations. Not only can the old model be considered carrier-centric, I would also venture it is product-centric (in the same way that the old banking model is product-centric). The implications from a technology point of view are the same as in the banking world: a thin front end, shaky middleware and a back end that is silo-driven and that makes it difficult to optimize underwriting or claims.

Current Insurance Model:  The current model optimized the old model and made the transition from carrier-centric to agent-centric, which means that things are less paper-based and more electronic and that there is more process pushed onto the agent to be closer to the customer. In this model, the agent is empowered to issue policies under certain limits and risk frameworks—the carrier is not the gating factor and central node anymore.

Instead of batch-processing policies at the carrier level, the system has moved to exception processing at the carrier level (when concerned with nonstandard data and policies), thereby leveraging the agent. The result is faster quotes and policies signed more quickly, with the time going from days and weeks to hours or just a day. Customer service will go the same route. Claims management will still remain the central concern of the carrier, though.

Digital Insurance Model:  This is the way of the future. It is neither carrier- nor agent-centric, and it certainly is not product-centric any more. This model is truly customer- and data-centric—very similar to what we witness in digital banking. The carrier reaches out to the customer in an omni-channel way. Third-party data sources are readily available, and the technology to process and digest the data is extremely effective and delivers fast and furiously. Machine learning allows for near-instantaneous underwriting at a carrier or agent level, any time, anywhere. The customer can now get a policy in minutes.

Processes after policy-signing follow a similar transformative route. The technology implications are material: new core systems of record, less silo effect, more integration, massive investments in data warehouses and in products and services that act as layers of connection between data repository centers, core systems, claims management platforms, underwriting platforms and omni-channel platforms.

Picture the carrier effectively plugged in to the external world via data sources, plugged in to the customer in myriad ways that were not possible in the past and plugged in to third-party providers, all of this in real (or near-real) time. That means no more of the old linear prosecution of the main insurance processes: customer acquisition, underwriting, claims management. Furthermore, with a fast-changing world and more complex customer needs, delivering a product is not the winning formula any more. Understanding the customer via data in a contextual manner is.

To be fair, insurance carriers have nearly completed massive upgrades to their database architecture and can claim the latest in data warehouse technology. Some carriers have gone the path of renovating their channels and going all-out digital. Others are refining the ways they engage new customers. Most are thinking of going mobile. Still, much remains to be done. These are exciting times.

Boiling down what a digital insurance model means, we can easily see the similarities with digital banking; digital insurance must be transparent, fast, ubiquitous and data-focused, and there must be an understanding that the customer is key and is not a product.

Once you digest this new model, it is easier to sift through the key trends that are reshaping and will reshape the industry. I am listing a few that we followed at R66.  By no means is this an exhaustive list, nor is it ordered by priority, impact or size of opportunity:

1) Distribution channel disruption: There are three sub trends here—a) the consolidation of brokers and agents, b) channels going all-out-digital and disrupting the brick and mortar and c) carriers continuing to go direct and competing with brokers.

2) Insuring the sharing/renting economy: Think about Uber, Airbnb and the many other start-ups that are building the sharing economy. All of them need to or already are creating different types of coverage through their ecosystems. Carriers that focus on the specific risks, navigate the use cases, gather the right data and are forward-thinking will win big. James River is an insurance carrier that comes to mind in this space.

3) Connected data analysis: I do not use the term “big data” any more. Real-time connected data analysis is the right focus. Think of the integration of a series of hardware devices, or think of n+1 data sources. These are powerful, mind-blowing and will affect the trifecta of insurance profits: underwriting, claims management and customer acquisition.

4) Technology stack upgrades:  This means middleware to complement data warehouse investments, new systems of record, software platforms for underwriting (or claims management) and API galore. It’s the same story with banking; there is just a different insurance flavor.

5) Technology externalities: GPS, telematics, AI, machine learning, drones, IoT, wearables, smart sensors, visualization and next-generation risk analysis tools—you name it, these will help insurance companies get better at what they do, if they adopt and understand.

6) Mobile delivery:  How could I not list mobile delivery? Whether it is to improve customer acquisition; policies or claims management; or customer service, we are going mobile, baby.

7) A la carte coverage: Younger generations are approaching ownership in different ways. As a result, a one-size-fits-all insurance policy will not work any more. We are already witnessing a la carte insurance based on car usage, homes or commercial real estate connected via sensors or IoT.

8) Speciality insurance products:  We live in a digital world, baby, which means cyber security, fraud and identity theft.

It should be noted that the above describes changes in the P&C industry and that the terms “carriers” and “reinsurers” can be used interchangeably. Furthermore, I have not focused on health insurance—I know next to nothing in that field.

Any insurance expert is welcome to reach out and educate me. Anyone as clueless as I am is welcome to add their thoughts, too!

This article first appeared on Pascal Bouvier’s blog, here.

11 Things That Matter Most in Managing Risk

Having just returned from another industry gathering where practitioners are trying to get a read on the keys to success in risk management, I thought I’d share some thoughts that I often include in my presentations and RIMS workshops.

Suffice it to say, no two practitioners are doing exactly the same thing nor following a template-based strategy if they’re having much success. I offer this introduction  to say two things: There is no one right way to practice risk management, and, by extension, the best risk strategies are those that are aligned with, if not custom-designed to fit, the priorities of the organizations for which they are intended.

One thing is nearly certain: A risk strategy can’t be successfully executed without a risk framework to make actionable those strategies that inform success. A framework might best be guided by one of the risk standards that are increasingly informing how the work can best be done, but a standard is not a prerequisite to success. By contrast, a risk culture is a prerequisite.

Your corporate culture represents the ways in which management and governance prefer employees to behave. It is typically tied to a set of values such as honesty, integrity and excellence. But do you realize that you also have a risk culture, even if you haven’t purposely defined and implemented one?

Whether your organization is risk-averse, risk-assumptive or somewhere in between these two extremes, your employees have risk taking and managing behaviors that, without a specific design and strategy for the risk culture you desire, will not likely be the behaviors or culture you most need and ideally desire. Therefore, communicating on risk culture can be most valuable to your long-term risk-management effectiveness.

What matters most in achieving this desired state? Well, rather than produce another list of top 10 items, here are 11 things that, in my opinion, matter most in effectively managing risk. If you operate with these elements in place, you will be more likely to have an effective strategy that other leaders will both contribute to and enable through resources.

Downside Protection: This is job one. The first priority is to make sure reasonably preventable loss is addressed through both mitigations and financing tactics. Management and governance rightly assume this is under way.

Influence and Gumption: Every senior risk leader must have the respect to be heard and the gumption to push back on risk owners and stakeholders with whom he may disagree.

Consistency: With risk process and sub-processes being the way in which the work gets executed, it is essential that they are consistently applied by all users.

Process Rigor: Processes that produce results and have impact require a rigorous approach to how they are designed, measured for effectiveness and continuously improved.

Data Interpretability: There must be actionable information about results and impact.

Communication Clarity: Beginning with a clear definition of risk itself, an entire sub-strategy for communicating your messaging will ensure you reach the ”right recipients at the right time with the right message.”

Reliable Measurability: Not every risk can or should be quantitatively measured, but, when you do, make sure the measure is as believable as possible.

Value Creation: Recognizing and leveraging risk for gain is the necessary evolution of the discipline’s practitioners if they ever hope to move beyond the tactical.

Embedded Risk Culture: Driving consistent and aligned risk-taking behaviors and decisions across the enterprise can only be achieved by embedding a well-defined and disciplined risk culture.

Managing to Appetite and Capacity: Risk cannot be effectively managed without a clear view into how much risk you are taking, want to take and have the capacity to take or assume.

Aligning Risk and Performance: The ultimate outcome for risk professionals is to manage risk relative to performance. Alignment, if not integration, between risk and performance is essential to achieving short- and long-term goals.

So there you have it: the 11 things that matter most in managing risk effectively. Sure, there are many other tactical elements of a good risk strategy and framework, but I believe they will naturally flow out of these elements when put into practice with the  proper senior level mandate and regular reinforcement of the strategy.