Tag Archives: financial services

A Mental Framework for InsurTech

Digital transformation has become a major challenge for insurance companies all over the world. In Italy, this transformation is exemplified by the adoption of vehicle telematics. According to the latest IVASS data, black box became an integral part of 16% of new policies and renewals during the third quarter of 2015.

The insurance sector is now seeing the same dynamics already experienced in many other sectors, including financial services: with start-ups and other tech firms innovating one or more steps of the value chain traditionally belonging to financial institutions. InsurTech has seen investments of almost $2.65 billion coming in during 2015, compared with $740 million in 2014. Like FinTech in 2015, it’s now InsurTech’s turn to define the elements to be included in the observance perimeter, this being a main point of debate among analysts.

In my opinion, all players within the insurance sector will have to become InsurTech-centered in the coming years. It’s unthinkable for an insurance company not to pose the question of how to evolve its own model by thinking which modules within its value chain should be transformed or reinvented via technology and data usage. This digital transformation can be achieved by building the solutions in-house, by creating partnerships with other players—both start-ups and incumbents—or through acquisitions.

Based on this view that all the players in the insurance arena will be InsurTech—meaning organizations where technology will prevail as the key enabler for the achievement of strategic goals—the way to analyze this phenomenon is via a cross-section view of the customer journey and the insurance value chain. This mental framework, which I regularly use to classify every InsurTech initiative—whether it’s a start-up, a solution provided by established providers or a direct initiative by an insurance company—is based on the following macro-activities:

  1. Awareness: Activities that generate awareness in the client—whether person or firm—regarding the need to be insured and other marketing aspects of the specific brand/offer;
  2. Choice: about an insurance value proposition, which, in turn, is divided into two main groups:
    1. Aggregators, which are characterized by the comparison of a large number of different solutions;
    2. Underwriters, which are innovating the way to construct the offer for the specific client, irrespective of the act to compare different offers.
  3. Purchase: Focuses on innovative ways in which the act of selling can be improved, including collection of premiums;
  4. Use of the insurance product: clarifies three very distinct steps of the insurance value chain: policy handling, service delivery (which is acquiring an ever-growing significance within the insurance value proposition) and claims management;
  5. Recommendation: Part of the customer journey that is becoming a key element in the customer’s experience with a product in many sectors;
  6. The Internet of Things (IoT), which can be included in the category of activities—though transversal  to the activities described above. The IoT covers all  the hardware and software solutions representing the enablers of connected insurance (the motor insurance telematics is the most consolidated use case);
  7. Peer-to-peer (P2P): Initiatives that, in the last few years, have started to bring peer-to-peer logic to the insurance environment, in a manner similar to the old mutual insurance.

 

Based on my interpretations of the evolution of the InsurTech phenomenon, I would say:

  • on the one hand, there is a tendency toward ecosystems in which each value proposition becomes the integration of multiple modules belonging to different players;
  • on the other hand, the lines between the classical roles of distributor, supplier (coming even from other sectors), insurer and reinsurer are getting blurred.

In a scenario like this, the balance of power (and consequently the profit pool) among various actors is bound to be challenged, and each one of them may well choose to collaborate or compete depending on context and timing.

My friends at InsurTech News represented – based on my framework described above – a map of the InsurTech newcomers and will continue to map the most interesting initiatives. Please feel free to comment adding more InsurTech newcomers you know.

FinTech: Epicenter of Disruption (Part 1)

It is difficult to imagine a world without the Internet or mobile devices. They have become core elements of our lifestyle and have brought a high degree of disruption to virtually every area of business. The financial services (FS) industry is no exception; the digital revolution is transforming the way customers access financial products and services. Although the sector has experienced a degree of change in recent years, the constant penetration of technology-driven applications in nearly every segment of FS is something new. At the intersection of finance and technology lies a phenomenon that has been accelerating the pace of change at a remarkable rate and is reshaping the industry’s status quo—it is called FinTech.

What is FinTech?

FinTech is a dynamic segment at the intersection of the financial services and technology sectors where technology-focused start-ups and new market entrants innovate the products and services currently provided by the traditional financial services industry. As such, FinTech is gaining significant momentum and causing disruption to the traditional value chain. In fact, funding of FinTech start-ups more than doubled in 2015, reaching $12.2 billion, up from $5.6 billion in 2014, based on the companies included on our DeNovo platform. Cutting-edge FinTech companies and new market activities are redrawing the competitive landscape, blurring the lines that define players in the FS sector.

Our objectives and approach

This report assesses the rise of new technologies in the FS sector, the potential impact of FinTech on market players and those players’ attitudes toward the latest technological developments. Additionally, the report offers strategic responses to this ever-changing environment.

Our analysis is based on the following:

  1. Primary data derived from the results of a global survey that includes feedback from a broad range of players in the world’s top financial institutions—For this study, we surveyed 544 respondents, principally chief executive officers (CEOs), heads of innovation, chief information officers (CIOs) and top-tier managers involved in digital and technological transformation. Our survey was distributed to leaders in various segments of the FS industry in 46 countries.
  2. Insights and proprietary data from DeNovo, PwC’s Strategy& platform, composed of a 50-member team of FinTech subject matter specialists, strategists, equity analysts, engineers and technologists with access to more than 40,000 public and proprietary data sources.

In the first section, we explore FS market participants’ perspectives on disruption. Next, we’ll highlight the main emerging FinTech trends in the various FS industries and the readiness of the market to respond to these trends. Finally, we’ll offer suggestions about how market players should strategically approach FinTech.

The Epicenter of Disruption

New digital technologies are in the process of reshaping the value proposition of existing financial products and services. While we should not underestimate the capacity of incumbents to assimilate innovative ideas, the disruption of the financial sector is clearly underway. And consumer banking and payments, already on the disruption radar, will be the most exposed in the near future, followed by insurance and asset management.

Disruption targets mostly consumer banking and payments

In keeping with the changes already underway, the majority of our survey participants see consumer banking as well as fund transfer and payments as the sectors most likely to be disrupted over the next five years.

In consumer and commercial lending, for example, the emergence of online platforms allows individuals and businesses to lend and borrow between each other. Lending innovation also manifests in alternative credit models, use of non-traditional data sources and powerful data analytics to price risks, rapid customer-centric lending processes and lower operating costs.

In recent years, the payments industry has also experienced a high level of disruption with the surge of new technology-driven payment processes, new digital applications that facilitate easier payments, alternative processing networks and the increased use of electronic devices to transfer money between accounts.

Screen Shot 2016-04-08 at 1.38.51 PM

Asset management and insurance are also on the disruption radar

Although a high level of disruption triggered by FinTech is already beginning to reshape the nature of lending and payment practices, a second wave of disruption is making inroads in the asset management and insurance sectors. Our survey found that this perception is confirmed by insiders. Nearly half of insurers and asset and wealth managers consider their respective industries to be the most disrupted. When asked which part of the FS sector is the most likely to be disrupted by FinTech over the next five years, 74% of insurance companies identified their own industry, while only 26% of players from other sectors agreed; 51% of asset managers said their industry will be disrupted, while only 31% of other players agreed.

However, there seems to be a perception gap here. Professionals from other industries do not see the same level of disruption in these areas. The fact that only insiders are aware of this situation, while outsiders don’t perceive it, could indicate the disruption is in its very early stages. Even so, venture capitalists are looking very closely at start-ups dedicated to reinventing the way we invest money and buy insurance. Annual investments in InsurTech startups have increased fivefold over the past three years, with cumulative funding of InsurTechs reaching $3.4 billion since 2010, based on companies followed in our DeNovo platform.

The pace of change in the global insurance industry is accelerating more quickly than could have been envisaged. The industry is at a pivotal juncture as it grapples with changing customer behavior, new technologies and new distribution and business models.

The investment industry is also being pulled into the vortex of vast technological developments. The emergence of data analytics in the investment space has enabled firms to home in on investors and deliver tailored products and automated investing. Additionally, innovations in lending and equity crowdfunding are providing access to asset classes formerly unavailable to individual investors, such as commercial real estate.

Customer-centricity is fueling disruption

As clients are becoming accustomed to the digital experience offered by companies such as Google, Amazon, Facebook and Apple, they expect the same level of customer experience from their financial services providers. FinTech is riding the waves of disruption with solutions that can better address customer needs by offering enhanced accessibility, convenience and tailored products. In this context, the pursuit of customer-centricity has become a main priority, and it will help to meet the needs of digital native clientele.

Over the next decade, the average FS consumer profile will change dramatically as the Baby Boomer generation ages and generations X and Y assume more significant roles in the global economy. The latter group, also known as “Millennials” (those born between 1980 and 2000), is bringing radical shifts to client demographics, behaviors and expectations. Its preference for a state-of-the-art customer experience, speed and convenience will further accelerate the adoption of FinTech solutions. Millennials seem to be bringing a higher degree of customer-centricity to the entire financial system, a shift that is being crystallized in the DNA of FinTech companies. While 53% of financial institutions believe that they are fully customer-centric, this share exceeds 80% for FinTech respondents. In this respect, 75% of our respondents confirmed that the most important impact FinTech will have on their businesses is an increased focus on the customer.

This post was co-written by: John Shipman, Dean Nicolacakis, Manoj Kashyap and Steve Davies.

What You Must Know on Machine Learning

I’ve yet to hear a financial services executive focus on machine learning as a key part of his company’s insight strategy.

“Analytics” still dominates Google searches (not only ahead of “machine learning” but far ahead of even “big data”):

Businesses are increasingly looking to hire data scientists, and they leave universities having been taught machine learning together with a mixture of statistics and computer science. When I spoke with data science students at an event in Edinburgh, it was clear they saw machine learning as a key part of their specialty, even if most businesses rarely mention the term.

In the 20 years since I was an R&D manager developing artificial intelligence pilots, I’ve seen few businesses even attempt to apply the techniques I found so powerful (including case-based reasoning, neuro-fuzzy logic and genetic algorithms). But perhaps data science finally has enough momentum to take AI into mainstream commercial application.

So, if you’re looking to keep up with developing data science or (wider) customer insight professions, what should you know about machine learning? Is it too late for you to learn? Do you need to return to university?

Although the social life options of the latter may sound appealing, most leaders don’t have time to put their corporate careers on hold while they retrain. Luckily, there are online resources to help you get up to speed and, at least, understand the language being used by your latest hires. In this post, I’ll share a few online resources and reviews I hope you’ll find useful.

See Also: How Machine Learning Changes the Game

What better place to start than an online tutorial that claims to be the world’s easiest introduction. With the catchy headline “Machine Learning is Fun!”, this two-part blog—published on Medium by Adam Geitgey—is perhaps not as simple as some would like, but it does provide a useful overview of techniques.

Screen Shot 2016-03-24 at 12.06.20 PM

To balance the data science perspective on machine learning, I thought it might also be interesting to share a market research perspective. This balanced and useful review by Kevin Gray in Quirks provides such a perspective. It should help researchers consider where AI algorithms could also be applicable to their quant work.

Screen Shot 2016-03-24 at 12.07.28 PM

If all that education and advice has made you keen to get your hands dirty and try machine learning, the next question is how you can get started. Well, if you are an R coder or have analysts in your team with R programming skills, here’s a handy starting point shared by Jason Brownlee.

Screen Shot 2016-03-24 at 12.08.19 PM

Don’t worry if you can’t, or prefer not to, use R. It seems that, as well as a plethora of machine learning tools, there are some heuristics, too. In this quick-start guide from the same site as above, Brownlee also shares how to understand any machine learning tool quickly (the information is so good I had to include this second link from the same blog.

Screen Shot 2016-03-24 at 12.09.08 PM

Finally, to really get you ruminating on the subject, consider this more philosophical piece by Christopher Nguyen, where he explores our relationship with AI the other way—what can the ways machines learn teach us about our own brains, imaginations and the role of intuition. Thought-provoking stuff

Screen Shot 2016-03-24 at 12.09.47 PM

I hope this post was of interest. If you’ve discovered other great content online that can help us all better understand machine learning, please do share.

Have a great time learning more!

Commercial Insurers Face Tough Times

Beyond the secular forces we described in our “Future of Insurance” series, more immediate and cyclical issues will be shaping the insurance executive agenda in 2016. Commercial insurers (including reinsurers) face tough times ahead, with underwriting margins that are being pressured by softening prices and a potentially volatile interest rate environment.

Recently, reserve releases, generally declining frequency and severity trends, as well as lower-than-average catastrophe losses have allowed commercial insurers to report generally strong underwriting results. However, redundant reserves are being (or have been) depleted, and the odds of a continued benign catastrophe environment are low. For example, one insurance executive recently observed, “The odds of this long of a lucky streak occurring is less than 1%.”

The commercial insurance market has, in recent years, had generally strong underwriting results, but this could change—potentially, very soon.

With varying degrees of focus, commercial P&C insurers have been mitigating the risk environment by taking a variety of strategic actions. In 2016 and beyond, they will need to accelerate their strategic efforts in four key areas: 1) core systems and data quality, 2) new products, pricing discipline and terms and conditions, 3) corporate development and 4) talent management.

Core systems and data quality

93% of insurance CEOs—a higher percentage than anywhere else in financial services—see data mining and analysis as more strategically important for their business than any other digital technology. Nevertheless, many commercial insurers operate with networks of legacy systems that complicate the timely extraction and analysis of data. This is no longer deemed acceptable, and leading insurers continue to transform their system environments as a result. Significantly, these transformations do not focus solely on specific systems for policy administration, claims, finance, etc.

To ensure timely quality data across the entire commercial P&C value chain, commercial insurers also focus on how the various systems are integrated with one another.

To put this into context, when a dollar of premium is collected, it not only “floats” across time until it is paid out in claims, it also “floats” across a variety of functions and their related systems: Billing systems process premium dollars; ceded reinsurance systems process treaty and facultative transactions; policy administration systems (PAS) process endorsement changes; claims systems process indemnity and expense payments.

Actuarial systems in disconnected data environments prevent the timely and efficient extraction and analysis of internal data and also complicate the focused and efficient use of external data, especially unstructured data. “Big data” is becoming increasingly popular considering the insights that insurers and reinsurers can derive from it. However, such insights only become actionable to the extent that companies can assess the external environment in the context of the internal environment—in other words, to the extent that big data can enhance (or otherwise inform) the internal data’s findings.

If all functional and systemic codes are not rationalized on an enterprise-wide basis, it is very difficult to efficiently accumulate and analyze data.

New products, pricing discipline and terms and conditions

Commercial insurers and reinsurers are not generally known as product innovators, but they can be. For example, as the profile of cyber-related risks increases, the need for cyber-related commercial insurance grows, thereby offering numerous opportunities for product innovation.

Because cyber is a relatively new exposure, frequency and severity data are nascent, therefore both pricing and risk accumulation models are in various stages of development. As a result, prescient insurers are carefully tracking and comparing their cyber pricing practices and coverage grants with those of key competitors. To be effective, such practices should be consistent with existing price, terms and conditions and monitoring processes. For example, tracking actual-to-expected premiums and rates is a common practice, which leading insurers perform regularly (i.e., at least quarterly, with monthly tracking common).

Insights from this kind of analysis apply to both new and existing products. The underwriting cycle is inherently a pricing phenomenon, and insurers and reinsurers that have greater and more timely product and pricing insights have a competitive advantage relative to those that do not. To explain, in addition to lower rates, the “soft” parts of the underwriting cycle tend to be characterized by the loosening of policy terms and conditions, which can erode profitability as quickly as inadequate prices. Therefore, the most competitive insurers and reinsurers carefully and continuously track the adequacy of policy terms and conditions. Recurring actuarial analyses and standardized reporting can monitor changes in pricing as well as in terms and conditions. However, identifying emerging underwriting risks is inherently qualitative. Therefore, this analysis can be time-consuming, especially for insurers with suboptimal PAS environments. However, almost all companies find the analysis well worth the effort.

Corporate Development

The combination of historically low interest rates, favorable frequency and severity trends and the relative lack of severe catastrophes has resulted in record policyholder surplus across P&C commercial insurance. Executives have a number of options on how to deploy surplus, one of which is corporate development.

Commonly, “corporate development” means mergers and acquisitions, but it can also encompass book purchases/rolls, renewal rights and runoff purchases. Determining the best option depends on many factors, including purchase price, competitive implications and an assessment of how the acquired assets and any related capabilities can complement or enhance existing underwriting capabilities.

Accordingly, some insurers are beginning to augment traditional due diligence processes (such as financial diligence, tax diligence and IT diligence) with underwriting-specific diligence to help ensure value realization over time.

If a corporate development opportunity offers underwriting capabilities that at least align to—and preferably enhance—existing capabilities, it can help facilitate a smooth integration, thereby mitigating underwriting risk (a key cycle management consideration).

Talent Management

For the most part, commercial underwriting decisions cannot be fully automated because they require judgment. Therefore, it is natural for underwriting talent to be a top priority. However, insurance executives have lamented that it is a major challenge for the industry to attract and retain knowledgeable personnel.

Two trends make commercial insurance talent management particularly challenging. First, experienced underwriters are leaving the industry. According to one study, “The number of employees aged 55 and over is 30% higher than any other industry—and that, coupled with retirements, means the industry needs to fill 400,000 positions by 2020.” Second, underwriting talent is relatively difficult to attract. For example, according to the Wall Street Journal, insurance ranks near the top of the list of least-desirable industries—according to recent graduates. The image of the insurance industry is that it is generally behind the times and offers little in terms of career development. Therefore, developing a performance-driven culture that enables the recruitment, development and retention of underwriting talent is more crucial than ever.

To help accomplish this, insurers should employ and should continuously assess tools and resources that educate and empower underwriters through all phases of their careers. This is important because the expectations in commercial underwriting are high, and the nature of the job requires a diverse range of skills (e.g., analytical, relational, sales, financial and risk). Furthermore, the best commercial underwriters are entrepreneurial, which employers should highlight as they recruit and manage their underwriting staffs.

Commercial insurers face a looming talent crunch and have to find ways to present themselves as—and actually be—a place where young people can have rewarding careers.

Implications

  • The relatively strong underwriting results of recent years are likely to soften in the coming year. Accordingly, commercial underwriters will need to accelerate their strategic efforts in:
  1. Core systems and data quality,
  2. New products, pricing discipline and terms and conditions,
  3. Corporate development
  4. Talent management
  • Core systems transformations go beyond individual system competencies. To ensure timely, quality data across the entire commercial P&C value chain, insurers also are focusing on how the various systems are integrated with each another to facilitate the timely and efficient extraction and analysis of internal data and the focused and efficient use of external data (especially unstructured data).
  • There are opportunities to create new products, but, to be profitable, insurers must exercise pricing discipline and must carefully and continuously track the adequacy of policy terms and conditions.
  • Current surplus levels have enabled insurers to invest in corporate development, and some insurers have augmented traditional due diligence processes (such as financial diligence, tax diligence and IT diligence) with underwriting-specific diligence to help promote value realization over time.
  • Commercial insurers have an aging workforce and are facing an impending talent crunch. Automation cannot replace the judgment that is required for effective underwriting. Therefore, it is vital for insurers to develop a performance-driven culture that enables the recruitment, development and retention of underwriting talent over time.