Tag Archives: Fintech

The Key to Digital Innovation Success

More than a half century ago, Ted Levitt transformed the strategic marketing agenda by asking a seemingly simple question. In his classic Harvard Business Review article “Marketing Myopia,” Levitt declared that truly effective executives needed the courage, creativity and self-discipline to answer, “What business are we really in?”

Were railroads, he asked, in the railroad business or the transportation business? Are oil companies in the oil business or hydrocarbon or energy business? The distinctions aren’t subtle, Levitt argued, and they subverted how companies saw their futures. Marketing myopia blinded firms to both disruptive threats and innovation opportunities.

Levitt’s provocative question remains both potent and perceptive for marketers today. But my research in human capital investment and “network effects” suggests that it, too, needs a little visionary help. Increasingly, successful market leaders and innovators – the Amazons, Apples, Googles, Facebooks, Netflixs and Ubers– also ask, “Who do we want our customers to become?”

That question is as mission-critical for insurance and financial services innovators as for Silicon Valley startups. The digitally disruptive influence of platforms, algorithms and analytics comes not just from how they transform internal enterprise economics but from their combined abilities to transform customers and clients, as well. Successful innovators transform their customers.

See also: The 7 Colors of Digital Innovation  

The essential insight: Innovation isn’t just an investment in product enhancement or better customer experience; innovation is an investment in your customer’s future value. Simply put, innovation is an investment in the human capital, capabilities, competencies and creativity of one’s customers and clients.

This is as true for professional services and business-to-business industries as for consumer products and services companies.

History gives great credence to this “human capital” model of innovation. Henry Ford didn’t just facilitate “mass production,” he enabled the human capital of “driving.” George Eastman didn’t just create cheap cameras and films; Kodak created photographers. Sam Walton’s Walmart successfully deployed scale, satellite and supply chain superiority that transformed “typical” shoppers into higher-volume, one-stop, everyday-low-pricing customers.

Similarly, Steve Jobs didn’t merely “reinvent” personal computing and mobile telephony; he reinvented how people physically touched, stroked and talked to their devices. Google’s core technology breakthrough may appear to be “search,” but the success of the company’s algorithms and business model is contingent upon creating more than a billion smart “searchers” worldwide.

The essential economic takeaway is that sustainable innovation success doesn’t revolve simply around what innovations “do”; it builds on what they invite customers to become. Simply put, making customers better makes better customers.

Successful companies have a “vision of the customer future” that matters every bit as much as their products and services road maps.

Insurance, fintech and insurtech industries should be no different. The same digital innovation and transformation dynamics apply. That means financial services firms must go beyond the “faster, better, cheaper” innovation ethos to ask how their innovations will profitably transform customer behaviors, capabilities and expectations.

In other words, it’s not enough to answer Levitt’s question by declaring, “We’re in the auto/property/life insurance business.” The challenge comes from determining how insurance companies want their new products, innovative services and novel user experiences to transform their customers. How can insurance companies invest in their customers in ways that make them more valuable? Who are they asking their customers to become?

So when insurers innovate in ways that give customers and prospects new capabilities — like Progressive’s price-comparison tools and Snapshot vehicle-usage plug-ins or Allstate’s mobile-phone-enabled QuickFoto claims submission option — they’re not just solving problems but asking customers to engage in ways they never had before.

Who are these companies asking their customers to become? People who will comparison shop; allow themselves to be monitored in exchange for better prices and better service; collaboratively gather digital data to review and expedite claims. These are but the first generation of innovation investments that suggest tomorrow’s customers will do much more.

This is of a piece with how a Jeff Bezos, Steve Jobs, Mark Zuckerberg or Reed Hastings innovates to make their customers — not just their products — more valuable.

Today’s Web 2.0 “network effects” business model — where a service becomes more valuable the more people use it — are superb examples of how smart companies recognize that their own futures depend on how ingeniously they invest in the future capabilities of their customers. Their continuous innovation is contingent on their customers’ continuous improvement. Call it “customer kaizen.”

How rigorously and ruthlessly fintech, insurtech and insurance companies champion this innovation ethos will prove crucial to their success. Being in “the blockchain business” is radically and fundamentally different than asking who we want our blockchain users to become.

See also: ‘Digital’ Needs a Personal Touch  

Giving better, faster and cheaper advice on risk management via digital devices is different than fundamentally transforming how customers perceive and manage risk. It’s the difference between “transactional innovation” and innovation based on more sustainable relationships of mutual gain.

The insurance industry needs to transform its innovation mindset. Start thinking how innovations make customers and clients more valuable. If your innovations aren’t explicit, measurable investments in your customers’ futures, then you are taking a myopic view of your own.

Today’s strategic marketing and innovation challenge is how best to align “What business are we in?” with “Who do we want our customers to become?”

What Blockchain Means for Analytics

I recently had the pleasure of attending #CityChain17 (blockchain conference) at IBM’s SouthBank offices.

Chaired by Paul Forrest (chairman of MBN Solutions), the conference was an opportunity to learn about blockchain and how it is being applied.

In the past, I viewed the hype about blockchain (following excitement about Bitcoin its most famous user) as just another fad that might pass.

However, as more businesses have got involved in piloting potential applications, it’s become obvious that there really is something in this – even if its manifestations are now much more commercial than the hacking by Bitcoin fans.

CityChain17 brought together a number of suppliers and those helping shape the industry. It was a great opportunity to hear voices, at times contradictory,and see what progress has been made toward mainstream adoption. There was so much useful content that I made copious notes and will share a series of two blog posts on this topic.

So, without further ado, as a new topic for our blog, here is part 1 of my recollections from this blockchain conference.

Introducing blockchain and why it matters

The first speaker was John McLean from IBM. He reviewed the need that businesses have for a solution to the problem of increasingly complex business and market networks, with the need to securely exchange assets, payments or approvals between multiple parties. He explained that, at core, blockchain is just a distributed ledger across such a network.

In such a scenario, all participants have a regulated local copy of the ledger, with bespoke permissions to approve blocks of information.

However, he also highlighted that today’s commercial applications of blockchain differ from the famous Bitcoin implementation:

  • Such applications can be internal or external.
  • Business blockchain has identity rather than anonymity, selective endorsement versus proof of work and wider range of assets vs. a cryptocurrency.
  • Blockchain for businesses is interesting because of the existing problems it solves. Broader participation in shared ledger reduces cost and reconciliation workload. Smart contracts offer embedded business rules with the data blocks on the ledger. Privacy improves because transactions are secure, authenticated and verifiable. So does trust because all parties are able to trust a shared ledger – all bought in.
  • Several sectors are currently testing blockchain implementations, including financial services, retail, insurance, manufacturing and the public sector.

Finally, John went on to outline how IBM is currently enabling this use of blockchain technology (including through its participation in the Hyperledger consortium and its Fabric Composer tool).

See also: 5 Main Areas for Blockchain Impact  

Comparing blockchain to databases, anything new?

As someone who was involved in the early days of data warehouses and data mining, I was delighted to hear the next speaker (Dr. Gideon Greenspan from Coin Sciences) talk about databases. Acknowledging that a number of the so-called unique benefits of blockchain can already be delivered by databases, Gideon began by suggesting there had been three phases of solutions to the business challenges of exchanging and coordinating data:

  1. Peer-to-peer messaging
  2. Central shared database
  3. Peer-to-peer databases

He had some great examples of how the “unique benefits” of blockchain could be achieved with databases already:

  • Ensuring consensus in data (B-trees in relational databases)
  • Smart contracts (the logic in these equal stored procedures)
  • Append-only inserts (database that only allows inserts)
  • Safe asset exchanges (the ACID model of database transactions)
  • Robustness (distributed and massively parallel databases)

Even more entertaining, in a room that was mainly full of blockchain advocates, developers or consultants, Gideon went on to list what was worse about blockchain vs. databases:

  • Transaction immediacy (ACID approach is durable, but blockchains need to wait for consensus)
  • Scalability (because of checks, blockchain nodes need to work harder)
  • Confidentiality (blockchains share more data)

After such honesty and frankly geeky database technology knowledge, Gideon was well-placed to be an honest adviser on sensible use of blockchain. He pointed out the need to consider the trade-offs between blockchain and database solutions. For instance, what is more important for your business application:

  • Disintermediation or confidentiality?
  • Multiparty robustness or performance?

Moving to more encouraging examples, he shared a few that have promising blockchain pilots underway:

  1. An instant payment network (using tokens to represent money, it’s faster, with real-time reconciliation and regulatory transparency)
  2. Shared metadata solution (as all data added to the blockchain is signed, time-stamped and immutable – interesting for GDPR requirements, even if the “right to be forgotten” sounds challenging)
  3. Multi-jurisdiction processes (regulators are interested)
  4. Lightweight financial systems (e.g. loyalty schemes)
  5. Internal clearing and settlements (e.g. multinationals)

But a final warning from Gideon was to be on the watch for what he termed “half-baked blockchains.” He pointed out the foolishness of:

  • Blockchains with one central validator
  • Shared state blockchains (same trust model as a distributed database)
  • Centrally hosted blockchain (why not a centralized database?)

Gideon referenced his work providing the multichain open platform, as another source for advice and resources.

Blockchain is more complex, hence the need for technical expertise

A useful complement (or contradictory voice, depending on your perspective) was offered next. Simon Taylor (founder of 11:FS and ex-Barclays innovation leader), shared more on the diversity of technology solutions.

Simon is also the founder of yet another influential and useful group working on developing/promoting blockchain, the R3 Consortium. He credits much of what he has learned to a blogger called Richard Brown, who offers plenty of advice and resources on his blog:

One idea from Richard that Simon shared is the idea that different technology implementations of blockchain, or platforms for developing, are best understood as being on a continuum, from more centralized applications for FS (like Hyperledger and Corda) being at one end and the radically decentralized Wild West making up the other end (Bitcoin, z-Cash and Ethereum). He suggests the interesting opportunities lie in the middle ground between these poles (currently occupied by approaches like Stellar and Ripple).

Simon went on to suggest a number of principles that are important to understand:

  • The shared ledger concept offers better automated reconciliation across markets.
  • But, as a result, confidentiality is a challenge (apparently Corda et al. are solving this, but at the expense of more centralization).
  • No one vendor (or code-base/platform) has yet won.
  • It is more complicated than the advertising suggests, so look past the proof of concept work to see what has been delivered (he suggests looking at interesting work in Tel Aviv and at what Northern Trust is doing).

To close, Simon echoed a few suggestions that will sound familiar to data science leaders. There continues to be an education and skills gap. C-Suite executives recognize there is a lot of hype in this area and so are seeking people they can trust as advisers. Pilot a few options and see what approach works best for your organization.

He also mentioned the recruitment challenge and suggested not overlooking hidden gems in your own organization. Who is coding in their spare time anyway?

In his Q&A, GDPR also got mentioned, with a suggestion that auditors will value blockchain implementations as reference points with clear provenance.

See also: Why Blockchain Matters to Insurers  

Time for a blockchain panel

After three talks, we had the opportunity to enjoy a panel debate. Paul Forrest facilitated, and we heard answers on a number of topics from experts across the industry. Those I agreed with (and thus remembered) were Tomasz Mloduchowski, Isabel Cooke and Parrish Pryor-Williams.

I took the opportunity to ask about the opportunity for more cooperation between the data science and blockchain communities, citing that both technology innovations needed to prove their worth to the C-suite and had some overlapping data needs. All speakers agreed that more cooperation between these communities would be helpful.

Isabel’s team at Barclays apparently benefits from being co-located with the data science team, and Parrish reinforced the need to focus on customer insights to guide application of both technologies. What panelists appear to be missing is that, in most large organizations, blockchain is being tested within IT or digital teams, with data science left to marketing or finance/actuarial teams. This could mean a continued risk of siloed thinking rather than the cooperation needed.

An entertaining, question concerned what to do with all the fakes now rapidly adding blockchain as a buzzword to their CVs and LinkedIn profiles. Surprisingly, panelists were largely positive about this development. They viewed it as an encouraging tipping point of demand and a case that some will need to fake it ’til they make it. There was also an encouragement to use meetups to get up-to-speed more quickly (for candidates and those asking the questions).

The panel also agreed that there was still a lack of agreement on terms and language, which sometimes got in the way. Like the earlier days of internet and data science, there are still blockchain purists railing against the more commercial variants. But the consensus was that standards would emerge and that most businesses were remaining agnostic on technologies while they learned through pilots.

The future for blockchain was seen as being achieved via collaborations, like R3 and Hyperledger. A couple of panelists also saw fintech startups as the ideal contenders to innovate in this space, having the owner/innovator mindset as well as the financial requirements.

It will be interesting to see which predictions turn out to be right.

What next for blockchain and you?

How do you think blockchain develops, and do you care? Will it matter for your business? Have you piloted to test that theory?

I hope my reflections act as a useful contact list of those with expertise to share in this area. Let us know if this topic is something you would like covered more, on Customer Insight Leader blog.

That’s it for now. More diverse voices on blockchain in Part 2….

Innovation: Solutions From… Elsewhere

Insurance is the industry most affected by disruptive change, according to the percentage of CEOs who are extremely concerned about the threats to their growth prospects from the speed of technological change, changing customer behavior and competition from new market entrants.

Insurers know they need to innovate to remain competitive. In fact, 67% of insurance respondents to PwC’s 2017 CEO Survey see creativity and innovation as very important to their organizations, ahead of other financial services sectors and the CEO Survey population as a whole. And, insurance CEOs noted that the area they would most like to strengthen to capitalize on growth opportunities is digital and technological capabilities, followed by customer experience (reflecting the connections between the two).

However, the industry’s traditional conservatism and the dizzying pace of technological change has made it difficult to change. As a result, most insurers are looking outside the industry – typically in the insurtech space (e.g., drones, sensors, internet of things (IoT)) – for the best ways to improve their systems, processes and products. And there is no doubt that industry stakeholders think insurtech has real promise: Annual investment in insurtech startups has increased fivefold over the past three years, with cumulative funding reaching $3.4 billion since 2010, based on the companies that PwC’s DeNovo platform follows.

See also: What Is the Right Innovation Process?  

To facilitate a diverse approach to identifying opportunities and potential partners from different industries and specialty areas, an enterprise innovation model (EIM) is table stakes. An EIM facilitates:

  • New product and service development: Being active in insurtech can help insurers discover emerging coverage needs and risks that require new insurance products and services. As a result, they can improve their product portfolio strategy and design of new risk models.
  • Market exploration and discovery: Prescient insurers actively monitor new trends and innovations, and some have even established a presence in innovation hotspots (e.g., Silicon Valley) where they can directly learn about the latest developments in real-time and initiate innovation programs.
  • Partnerships that drive new solutions: Exploration typically leads to the development of potential use cases that address specific business challenges. Insurers can partner with startups to build pilots to test and deploy in the market.
  • Contributions to insurtech’s growth and development: As we describe below, venture capital and incubator programs can play an important role in key innovation efforts. Established insurers that clearly identify areas of need and opportunity can work with startups to develop appropriate solutions.

Most insurers are looking outside the industry for the best ways to improve their systems, processes and products.

Maintaining awareness, influencing the market and identifying the right partners

To ensure an organization’s innovation efforts are in sync with – or even driving – the latest developments in the market, an EIM needs a formalized yet agile process for identifying and incorporating best practices.

Dedicated assessment of insurtech advancements can allow insurers to identify and promote best practices and key technologies. Moreover, maintaining a close connection with the insurtech market can help a company develop its external knowledge and relationships with innovators. Through this process, insurers can identify potential partners that can help them understand evolving technologies and their applications, and even contribute to developing the capabilities they desire.

With a deeper understanding of the market, capabilities and key players, insurers can be better positioned to facilitate innovation, ideation and design. While some fintech companies already have compelling insurance applications, insurers have a great opportunity to identify and design new potential use cases.

Fast prototyping is key to quickly creating minimally viable products (MVP) and bringing ideas to life. Early-stage startups develop and deploy full-functioning prototypes in near real time and go to market with solutions that evolve with market feedback. The development cycle is shortened, which allows startups to quickly deliver solutions and tailor future releases based on usage trends and feedback and to accommodate more diverse needs. Established insurers can follow the same approach or can partner with existing startups that have a MVP to help them to move to the next stage, scaling.

The ways to accomplish all of this vary based on how the organization plans to source new opportunities and ideas, how it plans on executing innovation and how it plans to deploy new products and services. The following graphic provides examples of EIMs by primary function.

The innovation center

The innovation center (also named “lab” or “hub”) is a structure at a corporate level that bridges external innovation with business unit needs and innovation opportunities. It relies on internal subject matter experts and innovation champions to ignite and drive innovation initiatives at a business unit level. With this model, innovative new products and services go to market under the company’s brand.

The innovation hub provides an outside-in view while promoting innovation internally. With this model, the company dedicates a team to constantly monitor trends and market activity, build and maintain relationships with key insurtech players, identify potential future scenarios and determine new partnership opportunities.

The hub should be managed through business units to effectively innovate (i.e., building prototypes and scaling models). Execution is a key success factor, and we recommend insurers consider complementary innovation models to help promote positive outcomes.

Regardless of the model they use, we recommend that insurers of all sizes consider developing an innovation center and create an external connection based on potential future scenarios.

The incubator

An incubator can drive innovation from idea to end product by identifying new opportunities and developing related solutions. Although it does require a significant investment of both money and resources, it has proven especially effective in addressing complex problems and devising new approaches to them.

Although the incubator can be internal, external structures typically create unique development environments and attract necessary talent. Via an external approach, ideas come mostly from outside the company and a panel of internal or external innovation specialists provide high-level guidance and approval for the innovation the company is seeking through the incubator.

Although the incubator initially drives innovation, business units typically become involved during the development process. They have an important role, especially when planning to deploy new solutions within the organization. The incubator can wind up as a start-up that can go to the market under its own name.

One of the main strengths of the incubator model is that it facilitates execution. It holds an idea until a prototype is developed and a minimally viable product is available. The gradual involvement of business units during the process enables the model to adequately scale. Upon adoption by its future owner, the incubator and business units can address any related challenges related to operating capacity, cyber risk, regulation and other issues.

Strategic venture capital (SVC)

The SVC model offers the opportunity to participate via stake or acquisition in relevant insurtech-related players. This is a way to influence and shape the development of specific startups (e.g. pushing them to solve specific problems) and acquire key capabilities and talent, and as a way to derive value from strategic investments.

In the SVC model, the company establishes a new ventures division, which sources ideas from the outside. The company provides funding and support for equity, while a SVC from this new structure explores, identities and evaluates solutions and markets new ventures under its own brand. The funds thatSVC invests in a startup help new players augment their capabilities and scale their business model. This could lead to potential market joint ventures, acquisitions or other deals to monetize the initial investment.

Established insurers with SVC arms are usually leaders in specific market segments and therefore leverage their experience and knowledge to select key ventures. To become more active with insurtech, these structures can be linked to innovation centers, thereby allowing companies to connect ventures with business units.

Instead of choosing one model over the other, we propose one that combines key elements from each. Companies can select elements based on their need for external innovation, the availability of talent, their ability to execute and the amount of investment the organization is willing to commit.

EIM operating options

EIM operating characteristics

Bridging the cultural divide

Complicating the need to innovate is the fact that an insurer’s culture often influences an external company’s decision about partnering with it. In fact, according to our 2016 Global
FinTech Survey, more than half of fintechs see differences in management and culture as a key challenge in working with insurers. Insurers also realize this, and 45% of insurance companies agree that this is a major challenge.

See also: How to Create a Culture of Innovation  

Accordingly, insurers will need to assess the availability and compatibility of existing resources and determine how and where they can find what may not currently be available. By clearly articulating the organization’s needs, defining explicit roles and establishing a model for enterprise innovation, an insurer can address any underlying concerns it may have about partnerships.

While insurers can create internal structures to support innovation, most of them will have to enlist external resources in one way or another. In fact, we expect many talented professionals without insurance-specific skills will be the ones who wind up driving innovation.

Attracting and developing innovators

Insurers can create internal structures to support innovation, but – as EIMs stipulate – success ultimately depends on having the right talent. And, most insurers will have to enlist external resources – ones who have an entrepreneurial mindset and who are well-connected to insurtech – in one way or another.

How does a company attract and retain this kind of talent? There are four primary ways:

  • Acquire the new talent from start-ups. This works well if the acquired company keeps running its business under its own start-up rules, away from the acquirer’s bureaucracy. Otherwise, if there is too much acquirer interference, then retention will be a challenge in a market that covets innovators.
  • Attract the talent directly from the market. This option typically requires a new mindset from the hiring company in terms of business role, work environment and even location. Establishing a presence in relevant innovation hotspots will help make an offer more attractive, facilitate external connections and demonstrate the insurer’s commitment to letting innovators be free to innovate.
  • Partner with startups, technology vendors, universities, researchers and other proven innovators. This option represents a major opportunity because it enables the insurer to create the connections to and formal partnerships with new talent. However, while identifying desired capabilities is relatively easy, there will need to be strong alignment of purpose between the organization and the new partners for the relationship to work. In this case, the Innovation Hub should be the most helpful model.
  • Grow the talent. This option is probably the least disruptive because it doesn’t require external changes. Large organizations have the opportunity to discover talent within their structures. But, the organization will have to ascertain and leverage the mentality and professional background of employees in many different ways. Gamification, internal collaboration groups and other resources can help in the search for potential in-house innovators, but most companies will need a more sophisticated staffing model to develop this talent (e.g., having specific development plans and offering “external” experiences in projects and with partners).

Complementing these options is the insurance industry leadership’s advocacy of new methods to foster change in employee skill sets. According to insurance respondents to PwC’s 2017 CEO Survey,

  • 61% are exploring the benefits of humans and machines working together (considerably higher than any other FS sector), and
  • 49% are considering the impact of artificial intelligence on future skills needs (also considerably higher than any other FS sector).

Implications

In response to this rapidly changing environment, incumbent insurers are approaching insurtech in various ways, prominently through joint partnerships or startup programs. But whatever strategy an organization pursues, insurtech’s main impact will be new business models that create challenges for market players and other industry stakeholders (e.g., regulators). In this environment, insurers will need to move away from trying to control all parts of their value chain and customer experience through traditional business models, and instead move toward leveraging their trusted relationships with customers and their extensive access to client data.

For many traditional insurers, this approach will require a fundamental shift in identity and purpose. The new norm will involve turning away from a linear product push approach, to a customer-centric model in which insurers are facilitators of a service that enables clients to acquire advice and interact with all relevant actors through multiple channels. By focusing on incorporating new technologies into their own architecture, traditional insurers can prepare themselves to play a central role in the new world in which they will operate at the center of customer activity and maintain strong positions even as innovations alter the marketplace.

To effectively develop these new business models and capabilities and establish mutually beneficial insurtech relationships, established insurers will need to start with a well-thought-out innovation strategy that incorporates the following:

  • An effective enterprise innovation model (EIM) will take into account the different ways to meet an organization’s various needs and help it make innovative breakthroughs. The model or combination of models that is most suitable for an organization will depend on its innovation appetite, the type of partnerships it desires and the capabilities it needs. EIMs feature three primary approaches to support corporate strategy, partnering via innovation centers (or hubs), building capabilities via incubators and buying capabilities via a strategic ventures division. Companies can select elements from each of these models based on their need for external innovation, the availability of talent, their ability to execute and the amount of investment the organization is willing to commit.
  • Even though insurers can create the internal structures that support innovation, most of them will have to enlist external resources in one way or another. Accordingly, they will need to assess the availability and compatibility of existing talent and determine how and where they can find what may not currently be available. Much like with enterprise innovation models, there are certain ways (often in combination) that insurers can locate and obtain the resources they need, including acquiring it, trying to attract it, partnering and growing it internally.