As companies become more data-driven, so have their employee performance metrics. Yet the very metrics that are often used to gauge employee performance might actually discourage the behavior those companies want to promote. This common workplace pitfall is grounded in two basic realities. What gets measured gets managed. Employees tend to behave in a manner that is aligned with how they are evaluated and rewarded. What’s easy to measure isn’t necessarily what’s right to measure. Organizations often gravitate toward easy-to-measure performance metrics, even though the behaviors they wish to cultivate are relatively complex. Examples abound of how organizations fall victim to the “folly” of employee performance metric design:

• Service centers that measure how quickly staff handles calls then wonder why employees don’t spend ample time to completely resolve a customer’s issue.
• Companies that obsess over quarterly sales targets then are surprised when executives make short-sighted decisions which compromise the business’ long-term health.
• Organizations that focus on individual performance to assess employee success are then dismayed when they observe a lack of team work and collaboration.
• Manufacturing firms that measure workers on the volume of product they deliver then struggle with widespread quality issues on the finished goods.
• Sales divisions that measure employees purely on top-line growth are then surprised to see how unprofitable newly -acquired accounts are.
• Human resources departments that measure recruiters on candidate “yields” from job fairs then find many unqualified applicants in their interview pipeline.

See also: Risk Performance Metrics   Without careful and thoughtful design, metrics that are meant to manage employee performance can actually sabotage business success. To avoid that outcome, keep these three points in mind: 1.  Think about what employee behaviors are most valuable to your customers. What do your customers care about most? Perhaps it’s how long they have to wait in line, or be on the phone with your staff. Even more likely, it’s getting their issue resolved on the first try. Make sure your employee performance metrics are aligned with your customers’ interests. If customers value speed of service above all else, then put that at the center of your measurement methodology. If other considerations are just as critical to them (such as the quality of the product, or the efficacy of the staff), then gauge performance on those dimensions as well. For example:

• Conduct post-purchase customer surveys to assess overall satisfaction with product quality (and, indirectly, the performance of those making the product).
• Track the number of employee-submitted product enhancement suggestions, thereby encouraging staff to translate customer feedback into constructive improvement ideas.
• Or measure how frequently customer inquiries are resolved on the first contact, indicating the staff’s effectiveness at understanding and addressing customer needs.

2.  Use metric “checks and balances” to avoid over-rotating on any one measure. A singular focus on a particular performance metric can be counterproductive. The behaviors that businesses try to encourage among staff can rarely be tied to just one metric. Doing so usually ends badly. Employees become obsessed with outperforming on that single metric, regardless of the consequences. Guard against over-rotation on any single metric by creating a balanced system of measures. For example, let’s say you want to encourage a sales-oriented culture, but want to avoid misconduct. Rather than measuring staff only on sales generated, complement that metric with ones that gauges account profitability and customer satisfaction. Then, only reward salespeople for achieving revenue targets while also meeting those other performance thresholds. See also: New Way to Evaluate Captive Performance   3.  Consider unintended consequences and perverse metric-driven behavior. This is perhaps the most important element of good employee performance metric design. Look at your employee performance metrics through a critical lens. Carefully consider all of the ways by which a metric, engineered with the best intentions, might nonetheless promote undesirable (or at least customer-unfriendly) behavior. Based on how detrimental and probable those unintended consequences are, tweak your approach accordingly. That might mean abandoning some metrics in favor of new ones. For example, consider a call center that chooses to measure customer satisfaction instead of call handle time. (The latter metric often leads service representatives to rush callers off the phone.) It may also mean adding “check and balance” complements to existing metrics. For example, an organization that uses 360-degree evaluations to ensure that individual achievement does not come at the expense of collaboration and collegiality. The development of effective employee performance metrics requires a delicate touch. Success measures, and the reward systems they support, shape employee behaviors in meaningful and sometimes subtle ways. A thoughtful approach to performance metric design can help companies use metrics to their advantage. The result is a powerful “behavioral current” that steers employees in the right direction. And the value of that is…  immeasurable. This article was originally published on Monster.com.

In the wake of Hurricane Harvey and now Hurricane Irma—and with Hurricane Maria now pummeling the poor Caribbean again while Hurricane Jose looks likely to lash Long Island—it's becoming clear how much people have avoided buying flood insurance and how expensive their decision may be. The question is: Why don't people buy insurance?

The answer seems to be that people often don't think they need insurance and find it expensive. For good measure, people complain about the complexity of insurance and how unpleasant it can be to deal with insurers.  

The problem isn't just with flood insurance, either. Far from it. Life insurers, in particular, face dwindling interest, but the lack of demand for insurance is widespread. Some are now saying that flood insurance should be required, and I've heard others suggest that life insurance should be mandatory. Those ideas may or may not make sense—but shouldn't the insurance industry aspire to producing products that people want to buy, not ones that, like auto and home insurance, they only buy when forced to do so?

That's a bit of a roundabout way of saying I think insurtech can solve many of the broad problems facing insurance, slashing costs while reducing complexity and smoothing interactions with insurers. Exhibit A is chatbots.

The bots use artificial intelligence to answer routine questions, generally through some form of texting. Customers don't need to sit on hold for minutes listening to sales pitches, be chastised because they don't have all their documents in front of them, then get transferred twice because it's not clear which department they should be calling. So, customers are happier. Insurers get to save gobs of money because a call center rep can handle five to 10 times as many customers as a rep can now. Insurers are increasingly using chatbots to simplify purchasing, not just service or claims processing—attacking what Brian Duperreault, now CEO of AIG, identified in an ITL article a year and a half ago as the "massive cost of doing business...[that] puts our industry at risk."  

An article in the past week by three senior partners at McKinsey identifies the sorts of efficiencies that are possible—a British broker that automatically processes 3,000 claims a day, managed by four employees; a department of 250 employees turned into 110 bots and 11 human supervisors; 160 bots that process 500,000 transactions a month. Remember, the changes make life simpler for customers and come at a time when the insurance industry faces a talent shortage. 

At the risk of being repetitive: An article I highlighted last week provides a host of additional examples of how chatbots are ready to take on a huge role. 

In addition, Pypestream, the company that we believe is the leader in chatbots in insurance, is announcing that it has received a round of financing from W.R. Berkley and will have a Berkley executive join the board. Pypestream, which raised $15 million in Series A funding in February, isn't disclosing the amount that Berkley is investing. "We will use this additional investment to fuel growth across more industries and use cases, and to help more businesses provide 24/7/365 experiences that their customers not only love but expect," said Richard Smullen, CEO of Pypestream. 

Chatbots, alone, likely won't be enough to get people to buy flood insurance, I'm sorry to report. But they can get us started on the sort of radical reduction in expense and improvement in simplicity that will lead the charge for insurtech. Perhaps the industry can even get to the point where people look to buy insurance, rather than only doing so when a regulator or mortgage bank forces them to do so.  

Cheers,

Paul Carroll,
Editor-in-Chief

According to a new study from the Insurance Institute of Canada (IIC), the sharing economy presents both an opportunity and a threat to the insurance industry. In the U.S., the sharing economy has already created 17 companies valued at $1 billion or more, including Uber and Airbnb. Some 27% of the U.S. population participate in this type of consumption. Now, with millions of Canadians who use the sharing economy seeking unconventional coverage as a result, innovative startups are threatening Canadian insurers. See also: Opportunities in the Sharing Economy   Opportunity – Widespread Use Forty-five percent of Canadians report being interested in sharing underutilized assets to generate income. In Montreal alone, Uber provides roughly 300,000 rides per month. This means that new types of insurance policies are needed to support the emerging car-sharing and home-sharing industries. For example, because the sharing economy often includes short-term asset sharing, there is an opportunity for insurance companies to provide unconventional coverage options. Some insurers are already creating products to satisfy this demand. For instance, Aviva Canada has a policy for ride-sharing drivers, and Square One Insurance developed a product specifically for Airbnb hosts. Threat – New Competition All of this new opportunity is fueling the creation of nimble and mobile-friendly insurtech startups such as Prvni Klubova, Lemonade, and Metromile. These companies provide insurance in innovative ways using mobile and AI-driven technology. Companies like these three are potential threats to traditional insurers in Canada. In fact, Lemonade has already gained more than $59 million in funding and is quickly becoming a major player in the industry. According to a recent study, nearly half of traditional insurance companies are concerned that as much as 20% of their businesses could be lost to new insurtech players. If insurers fail to adapt to new competition, these fears could become reality. And insurance carriers are not the only companies experiencing disruption. Insurance brokers also face competition from new platforms such as Friendsurance. The Solution There are two options for traditional insurers to consider when it comes to dealing with swift insurtech startups -- compete or partner. Competition has been attempted by a number of traditional insurers, such as Economical Insurance, who launched Sonnet Insurance, an online-only insurance provider. However, due to the rapid pace of emerging technologies, head-on competition presents many challenges. Launching an insurtech solution from the ground up is resource-intensive, especially for companies who are not as familiar with a technological terrain. See also: Sharing Economy: The Concept of Trust   Partnering can be a more productive endeavor. Many traditional insurers have recognized this and have already formed key partnerships. For example, Intact and Aviva Canada have partnered with Uber. Intact is also a partner with Turo and an investor in Metromile. Additionally, Northbridge has partnered with RideCo, a Waterloo-based ride-sharing startup. Through this partnership, ride-share drivers can receive as much as $1 million in third-party liability coverage. Final thoughts Sharing economy valuation is projected to top $335 billion by 2025. Its impact on the Canadian insurance market will only continue to grow. While many Canadians will benefit from the expansion of the sharing economy, traditional insurance companies will need to adapt in order to keep up with new competition from insurtech newcomers. As a result, we are likely to see more partnerships between traditional insurers and insurtech companies in the years to come.

Once your analysts have a clear business question to answer, do they start new analysis each time, potentially reinventing the wheel? After creating or leading data and analytics teams for many years, I began to notice this pattern of behavior. What we seemed to lack was a consistent knowledge management solution or corporate memory that could easily spot what should be remembered. Funnily enough, as I became convinced of the need for holistic customer insight, I found a partial answer among researchers. Avoiding reinvention is such an important issue for analytics and insight teams that I’ll use this post to share my own experience. The lack of secondary research approach for analytics Researchers do a somewhat better job than insight teams because of their understanding of the need for secondary research. Experienced research analysts/managers will be familiar with considering the potential for desk research, or searching through past research, to answer the question posed. Perhaps because of the more obvious cost of commissioning new primary research (often via paying an agency), researchers make more effort to first consider if they already have access to information to answer this new question. But, even here, there does not appear to be any ideal or market-leading knowledge management solution. Most of the teams I have worked with use an in-house development in Excel, interactive PowerPoint slides with hyperlinks to file structures or intranet-based research libraries. Whichever end-user computing or groupware solution is used, it more or less equates to an easier to navigate/search library of all past research. Normally, a user can search by keywords or tags, as well as through a prescribed structure of research for specific products/channels/segments etc. See also: Why Customer Experience Is Key   Some research teams use this very effectively and also recall those visualizations/graphics/VoxPops that worked well at conveying key insights about customers. It is worth investing in these area as it can save a significant amount of research budget to remember and reuse what has been learned already. However, while also leading data or analytics teams (increasingly within one insight department), it became obvious that such an approach did not exist for analytics. At best, analysts used code libraries or templates to make coding quicker/standardized and to present results with a consistent professional look. Methodologies certainly existed for analysis at a high-level or for specific technical tasks like building predictive models, but there was no consistent approach to recording what had been learned from past analysis. I’ve seen similar problems at a number of my clients. Why is this? Perhaps a combination of less visible additional costs (as analysts are employed already) and the tendency of many analysts to prefer to crack on with the technical work together conspire to undermine any practice of secondary analytics. The many potential benefits of customer insight knowledge management Once you focus on this problem, it becomes obvious that there are many potential benefits to improving your practice in this area. Many analytics or BI leaders will be able to tell you their own horror stories of trying to implement self-serve analytics. These war stories are normally a combination of the classic problems/delays with data and IT projects, plus an unwillingness from business stakeholders to actually interrogate the new system themselves. All too often, after the initial enthusiasm for shiny new technology, business leaders prefer to ask an analyst than produce the report they need themselves. So, one potential advantage of a well-managed and easily navigable secondary analytics store is a chance for business users to easily find past answers to the same question or better understand the context. But the items stored in such an ideal knowledge management solution can be wider than just final outputs (often in the form of PowerPoint presentations or single dashboards). I have seen teams benefit from developing solutions to store and share across the team:

• Stakeholder maps and contact details
• Project histories and documentation
• Past code (from SQL scripts to R/Python packages or code snippets)
• Metadata (we’ve shared more about the importance of that previously; here I mean what’s been learned about data items during an analysis)
• Past data visualisations or graphics that have proved effective (sometimes converted into templates
• Past results and recommendations for additional analysis or future tracking
• Interim data, to be used to revisit or test hypotheses (suitably anonymized)
• Output presentations (both short, executive style and long full documentation versions)
• Recommendations for future action (to track acting on insights, as recommended previously)
• Key insights, summarized into a few short sentences, to accumulate key insights for a specific segment, channel or product

Given this diversity and the range of different workflows of methodologies used by analysts, it is perhaps not surprising that the technical solutions tried vary as well. Where is the technology analytics teams need for this remembering? As well as being surprised that analytics teams lack the culture of secondary analytics, compared with the established practice of secondary research, I’m also surprised by a technology gap. What I mean is the lack of any one ideal, killer-app-type technology solution to this need from insight teams. Although I have led and guided teams in implementing different workarounds, I’ve yet to see a complete solution that meets all requirements. See also: Why to Refocus on Data and Analytics   An insight, data or analytics leader looking to focus on this improvement should consider a few requirements. First off, the solution needs to cater with storing information in a wide variety of formats (from programming code to PowerPoint decks, customer videos to structured data sets, as well as the need to recognize project or "job bag" structures). Next, it has to be quick and easy to store these kinds of outputs in a way that can later be retrieved. Any solution that requires detailed indexing, accurate filing in the right sub-folder or extensive tagging just won’t get used in practice (at least not maintained). Finally, it also has to be quick and easy to access everything relevant from only partial information/memories. Imperfect solutions that I have seen perform some parts of this well are:

• Bespoke Excel or PowerPoint front-ends with hyperlinks to simple folder structures
• Evernote app, with use of tags and notebooks
• SharePoint/OneNote and other intranet-based solutions for saving Office documents
• Databases/data lakes capable of storing unstructured or structured data in a range of file formats
• Google search algorithms used to perform natural language searches on databases or folders

These can all fulfill part of the potential, but the ideal should surely be a simple as asking Alexa or Siri and having all completed work automatically tagged and stored appropriately. I’m sure it’s not behind the capabilities of some of the data and machine learning technologies available today to deliver such a solution. I encourage analytics vendors to focus more on this knowledge management space and less on just new coding and visualisations. Do you see this need? How do you avoid reinventing the wheel? I hope this petition has resonated with you. Do you see this need in your team? Please let us know if you’ve come across an ideal solution. Even if it is far from perfect, it would be great to know what you are using. Share your experience in comments boxes below, and I may design a short survey to find out how widely different approaches are used. Until then, all the best with your insight work and remembering what you know already.

Last week, we started a conversation about some of the common insurtech claims. Last week, we mentioned the statement from one particular company about all the good that they do. If you missed last week’s post, here’s a link to A Response to Some Insurtech Claims. Let’s get into statement #2. Statement #2: It’ll just take a few seconds! Swyfft wants us to believe that it only takes an address to get a solid quote on a homeowners’ policy. Going to the website, you’ll find only a few lines of text and a place to enter your address, press the button and “Get Quote.” Implication: Your insurance company is wasting your time by asking you all of those questions. We’ll give you insurance. All you have to do is give us your address; we’ll search publicly available information and give you a quote instantly. We don’t want to waste your time. Response: I don’t buy this. I tried this website out, too. It was pretty simple to get a quote. I put the address in and then they asked a few more questions. Then they asked a few more questions. Then they gave me a quote. It was a pretty good quote as far as insurance quotes go. See also: What Incumbents Can Teach Insurtechs   The problem is the lack of honesty when they say that they’ll give you a quote with just an address, or the auto insurance company that says that they’ll give you a quote without any personal information. That’s just nonsense. Their system is not making underwriting decisions based only on what their data collection algorithms can gather from the internet. Even when they say that they can give you a quote with minimal information, it’s at best a preliminary quote. It’s not a full quote. That’s when they turn around and become those they cry out against. That’s when they start asking other questions, just like I would if I was the underwriter. Here’s my next concern and its a question for the carrier. When the customer has a loss, will they have a person review the file and try to underwrite the risk at the time of the loss to avoid paying on the claim? This is a tactic that other companies have used to their detriment. Let me be clear. If a company is going to have a person underwrite the risk, it must be done prior to accepting the risk, or early in the life of the risk. This includes underwriting upon renewal. Underwriting is the end result of risk analysis and data validation and must never be done as a means of rejecting claims as part of the claims process. If a company trusted their software to make the decision to write the risk, they should stand by that trust at the time of the claim My final concern here is that the applicant doesn’t necessarily understand what they’re buying or rejecting. The company is making offers of coverage, including changing coverage A for their home, which an experienced insurance professional might look at and provide advice about. Without that advice, the customer might look at the options and reject them, leaving them open to retain certain losses that they shouldn’t. Those are the losses that they’ll try and file as claims later and the company will reject the claims. See also: 3 Misconceptions on Insurtech   I will honestly admit that some of this is my conjecture. I’m making guesses about problems that may pop up for the customer if they choose this particular sort of insurance company. I may be wrong, but I’d rather make my concerns known and be wrong than be right and keep silent. Next week, we’ll talk about statement #3: You’ll save so much money! This article first appeared at www.insurancejournal.com.

Automation and robots are not just revolutionizing work in factories and warehouses but also in offices, including insurance companies. According to a study by the McKinsey Global Institute, in around 60% of all occupations, 30% or more of all tasks could be performed by machines—and even 20% of management tasks could be performed by robot workmates. How will companies change when office work is automated? If robots and software programs replace human work, this costs on average around 13% of the wage bill paid for work in a developed country like the U.S. At a stroke, moving this work to low-wage economies becomes less attractive because offshoring on average costs almost 40% of the wage bill in developed countries. A British insurance broker today automatically processes 3,000 claims a day—all managed by a grand total of four employees. And the subsidiary of a major European energy utility has automated several important processes in administration—from billing and collection of consumption data to consumption management. What was previously handled by 250 employees is now managed by 110 robots, overseen by 11 human supervisors. One of the biggest wireless providers has automated 15 complex administrative processes, which is equivalent to 35% of its work volume: 160 robots process around 500,000 transactions a month. And it doesn’t just save costs. Since the results are more reliable than those produced by human employees, sales staff on the front line have more capacity because they don’t keep having to check back with head office to query an incorrect entry. See also: Robots and AI—It’s Just the Beginning   Machines, then, are superior both in terms of cost and quality, with robots and computers producing more accurate results. They rigidly follow their programming—errors are not a factor. And even if production is ramped up, the same quality is achieved with large volumes as with smaller volumes. Robots don’t even need breaks—they can work around the clock if necessary. And something else that’s particularly important in times of increased compliance regulations, machines record their activities in seamless logs, and any activity can be verified later. However, because it will only be possible to fully automate a handful of jobs in the foreseeable future, work content and processes will need to be redefined. For example, if banks use machines to review loan applications, employees have more time to advise customers, thus producing more applications a day. Financial advisers no longer need to analyze the financial data themselves and can therefore work more on creative investment strategies. Robots can even help develop investment strategies—meaning recommendations that were previously only given to the best customers because they tied up so much adviser capacity, can now be granted to every customer as “robo-advice”. Automation is even relevant for complex jobs The opinion still persists that automation is only suitable for the work of poorly qualified and low-paid workers. However, the study by the McKinsey Global Institute comes to a different conclusion: Even around 20% of management tasks can be handled by machines. They can analyze reports and presentations for operational decisions, check status reports for compliance with targets and even prepare HR decisions. In turn, managers have more time for thinking, for communicating and for managing—and the time needs to be used wisely. The more intensive the use of data, the more managers can benefit from automation—for example, in investment management where data volumes can be leveraged and turned into recommendations far more systematically using artificial intelligence and machine learning systems than is possible by a human. Automation is more than a technological decision Technology is, of course, a key element on the road to intelligent process automation; however, this is primarily a strategic decision that must be made by top management. The management must assess the extent to which the company is affected by the changes and decide whether to develop a specific strength in the area and to be at the forefront of change, or whether to hold back as a follower and avoid the mistakes of the pioneers. Ultimately, managers must decide how to adjust the operational business model of their company—from the organization and culture to the development of talent and skills. Experience shows that companies that selectively automated their processes and reduced costs quickly and easily in those areas with robotic process automation had to redefine all of their processes on the road to intelligent process automation—entirely in the spirit of the business process re-engineering of the 1990s. The key objective isn’t simply far-reaching automation of all processes, but to improve the overarching business system. It is still uncertain how soon automation will become widely adopted in offices. On the one hand, the timing depends on the pace of technological developments, and on the other how quickly the technological possibilities will be accepted and implemented in companies. Industries with a strong reliance on pure software solutions lead the way. They quickly achieve significant savings with manageable investment—the finance industry, where processes can be automated at relatively little cost, is a good example. The more hardware that is required, or the more security provisions and legal regulations that have to be met, the longer the switch to automation takes. See also: A Key Misconception on Digitization   Management must have a good overview of how their own industry’s parameters are developing, while at the same time developing a feeling for the economics of automation. This specific IQ of company leadership could become the difference between success and failure in the business world of tomorrow. Adapted with permission of the publisher, Wiley, from DIGITAL@SCALE: The Playbook You Need To
 Transform Your Company
 by Anand Swaminathan and Jürgen Meffert. Copyright (c) 2017 by McKinsey & Company. All rights reserved. This book is available at all bookstores and online booksellers.

Employees often are seen as the weakest link in cybersecurity. Breaches by hackers may hit the headlines, but human error (or intent) is responsible for the majority of attacks. IBM’s 2016 Cyber Security Index reported that insiders carried out 60% of all attacks. Three-quarters of these attacks were malicious, and a staggering 25% of breaches were accidental. See also: How to Determine Your Cyber Coverage   I took the opportunity to sit down with Richard Ford, chief scientist at Forcepoint Security at Black Hat 2017 in Las Vegas. The notion of understanding human behavior and its role in cybersecurity was the topic of our discussion, and you can find the key takeaways below. Look at the why, not the what. We’re great at focusing on what is happening within our network and capturing every single event. What we’re bad at doing is talking about the why. This often is much more significant. It’s time companies think about what the hacker is trying to accomplish. Why did that file get moved? Why did that data loss prevention (DLP) event occur? Mitigation depends on the why. You’d mitigate an accidental data breach very differently than an intentional one. When companies move toward the why, they can start to mitigate much more effectively. Reduce the friction caused by IT security.  A lot of security measures aren’t successful because they create friction between users. Currently, we see security’s role as protecting the business. In the future, we will see it as a way to enable business to be done safely. For example, to stop restricted files from leaving company servers, most firms would turn off universal serial bus (USB) access. But that creates friction. Instead, the file should be seamlessly and silently encrypted so that it will only decrypt if it is loaded onto another company device. It’s the same level of protection but with far less friction. The more seamless security is, the more people will buy into it. See also: Cyber Measures Starting to Pay Off   Make privacy a first-class citizen. Too often, companies send a bad message by giving the impression that they don’t trust their employees. Security and privacy should be a benefit to the employee, not a negative. One way companies can achieve this is by being open with employees. When employees understand what’s happening, they understand why it’s protecting the company. Another is by anonymizing the data in a way that protects an employee’s personal information but still continues to protect the company. When done right, employees’ privacy should be protected and so should the company’s data. You shouldn’t do one at the expense of the other.

Regulatory overhead + old technology = high prices + bad service. A German insurer shared this telling formula with us, and it’s a perfect summary of the challenges that insurers are facing. Among the 75 executives we interviewed for our book Reinventing Customer Engagement: The next level of digital transformation, many said that maintaining legacy systems consumes 90% of technology budgets. Typical digital transformation programs therefore give a lot of attention to simplifying IT environments. Outdated systems not only result in high costs but also make it difficult and costly to act quickly and effectively on new customer wishes. The systems of insurers are often older than the customers they serve. Meanwhile, digital life has become so much more intuitive (Apple), interactive (Mint), contextual (Amazon), beautiful (Spotify) and intelligent (Google). Insurers have to operate much closer to the market and foster the opportunities that new technologies offer with techniques such as the "lean methodology" to experiment with new ideas and processes, constantly tweaking these with fast feedback loops. So, in this blogpost, we included 10 insurtechs and innovative tech providers that help insurers with solving the legacy issue, taking IT off the critical path:

1. KASKO
2. Backbase
3. Vlocity
4. Keylane
5. Faktor Zehn
6. Roundcube
7. Tieto
8. OutShared
9. Guidewire
10. Ti&m

(The forthcoming DIA edition in Munich (Nov. 15 and 16) will, of course, feature the latest.) 1.  Kasko: Helping insurers to act like an insurtech startup London-based Kasko is the first digital insurance platform for on-demand insurance products to enable insurance companies and brokers to quickly bring products to market. Kasko allows digital marketplaces and booking platforms to offer their customers contextually relevant insurance products via plugin or API. The company relieves clients from the regulatory and technological burdens associated with integrating directly within insurance companies. Kasko provides insurance solutions within the spaces of car, property, freelance, travel and events. By offering an API-powered agile insurance product platform that sits in between digital customer touchpoints and their customers legacy IT, they take the internal IT off the critical path to product launch. Read more, click here. Check demo, click here. 2.  Backbase: Omni-channel experiences, ready to go Backbase has created the world’s leading lean customer experience platform, Backbase CXP. It has been designed to help financial institutions organize, create and manage deeply relevant customer experiences across all channels, on any device, to delight your customers and deliver measurable business results. Backbase has a flexible and modular architecture that puts insurance providers back in control of their digital experiences and strategy, which puts them back in touch with their customers. By putting their own business and digital marketing teams in the driver's seat, insurers will be able to create the types of interactions that boost engagement, resulting in increased retention and a larger share of wallet and, most importantly, happy customers. Backbase is a ready-to-go insurance solution. It fully supports internet, tablet and mobile experiences, including omni-channel, by facilitating cross-channel customer journeys, plus seamless handover and orchestration between channels and devices. Read more, click here. Check demo, click here. See also: 10 Insurtechs for Superb Engagement   3. Faktor Zehn: innovative agile insurance solutions Munich-based Faktor Zehn is well known as the product house for agile insurance solutions. The international IT consulting and software company, provides innovative consulting services in combination with concrete solutions based on the platform-independent programming language Java. Faktor Zehn focuses on product management, policy management and sales and service systems to help insurance companies to innovate and develop competitive advantages. All products are developed to support insurance companies to generate speed of innovation as well as competitive advantages. Therefore, all business transactions are executable through web services to ensure a high rate of fully automatic processing. The user interface is optimized to process complex issues while leaving intact all primary batch processes, such as follow-up debit and premium due date mutations. While using products of Faktor Zehn, business and IT development teams of an insurance company work hand in hand with product development to improve time to market, to make sure that the products meet the high standards and to launch products or product variants quickly and efficiently. Read more, click here. Check demo, click here. 4.  Keylane: software with smart robotic applications for insurers Keylane is the showcase of insurance 3.0. The state-of-the-art Keylane technology platform supports core processes such as policy administration, sales and distribution and underwriting, and enables companies to excel in operational performance as well as in customer service. Keylane’s software solutions enable companies to engage effectively with their customers; providing operational agility (founded on best practice), in the insurance and pension markets. New technologies such as speech recognition, social analysis and predictive analytics are already integrated with the Keylane solutions to make the insurance customer experience as easy and friendly as possible. The integration of core solutions with smart robotic applications provides front-line workers within a matter of seconds with a more holistic view of their information landscape. Improving efficiency, effectiveness and lowering of costs. The user-friendly multi-channel portals integrated with flexible administration systems enable insurers to boost customer experience as well as excel in operational efficiency, achieving cost savings of more than 50% on the IT budget. Read more, click here. Check demo, click here. 5.  Vlocity: Adding industry-specific process applications to Salesforce Developed in partnership with Salesforce, Vlocity extends the Salesforce Sales Cloud, Service Cloud, Communities Cloud and other clouds with very specific business process applications for, among others, the insurance and health insurance verticals. The Vlocity apps on Salesforce add value to the user through a much faster time to market, a lower total cost of ownership and the agility of a product that stays in sync with Salesforce all the way through. Those are huge benefits from a business perspective. ABD Insurance, a top 100 insurance broker in America, sells all different lines of insurance across multiple carriers and uses Salesforce, which ABD liked it but which couldn’t do all the things the broker wanted. Vlocity came in and deployed Vlocity Insurance in just 45 days. Read more, click here. Check demo, click here.
6.  Roundcube: Why a "fat" mid-office is healthy for insurers! To be truly agile as an insurer, you need an almost unattractive body: a slim back office, a flat layer that enables connectivity at the front end and a rich, "fat" mid office that is the engine that drives it all. It’s the mid-office where connections should be made. We cannot wish our legacy systems away, we cannot simply upgrade, we cannot continue to add channels that add cost without bringing in more business.  But what we can do is use the back office for its core and stable strength by extracting relevant data and let it run the more stable admin tasks. This system can run at a different heartbeat and cost than a mid- and front office, while still making use of your existing investment. The Roundcube Insurance Platform is an agile mid-office engine where data becomes relevant information, where you can build experiences with the customer through relevant offerings. Read more, click here. Check demo, click here. 7.  Tieto: an ecosystem for business renewal Tieto, the largest IT services company in the Nordic region and creator of the world’s first internet bank, digital health records and e-invoice solutions, has already helped a large number of worldwide businesses in banking, insurance, retail, manufacturing, healthcare and public services with the digital leap in highly competitive markets. What’s more, Tieto actively builds an ecosystem of leading innovators and startups to complement its offering on data-driven areas. Tieto has several internal startups in the company focused on Tieto’s main growth areas: Customer Experience Management (CEM), Internal Internet solutions and Security Systems. This benefits customers by allowing them an increased ability to speed up digitalization. Read more, click here. Check demo, click here. See also: What Incumbents Can Teach Insurtechs   8.  OutShared: a digital insurer in a box OutShared offers an in-house developed and built digital insurance platform in a SAAS solution to the market. OutShared's platform is an all-in-one insurance solution for policy management, quotations, claims origination and processing: from back-office database through middle-office processing to front-office web and app interfaces. Built on today's digital ethos, and offered through strategic BPO and SaaS operations, OutShared offers the smart integrated solution for insurance specialists, developed for both new market offerings and the renovation of established operations migrated to the platform. HEMA for instance, an established retail brand, converted its traditional business to OutShared’s platform. As a result, the operational cost ratio decreased by 50%, the loss ratio improved by 10 percentage points in one year. The portfolio was converted in two months, from zero to live in six months. Read more, click here. Check demo, click here. 9.  Guidewire: Personalized and hassle-free customer journeys with among others a chatbot and Facebook messenger service The California-based company builds software products that help P&C insurers replace their legacy core systems and transform their business. Providing insurers with solutions for the main drivers for a successful customer journey; digitalization, personalization and a real omni-channel strategy. Guidewire products enable insurers to deliver excellent service for all stakeholder within the insurance lifecycle, increase market share and lower operating costs. The platform is based on three elements – core processing, data and analytics and digital engagement. These work together to strengthen the insurers’ ability to engage and empower their customers, agents and employees, allowing insurers to select, deploy and upgrade best-of-breed applications individually or as a pre-integrated suite, according to their requirements and priorities. More than 260 P&C insurers off all sizes and business lines around the world have selected Guidewire. In Europe alone, Guidewire has more than 45 customers across 11 countries. Read more, click here. Check demo, click here. 10.  Ti&m: the benchmark for a personalized digitalization strategy Ti&m is a Swiss market leader for digitalization and security products. The ti&m channel suite is the simple, fast, trusted and efficient way to digitalize customer relationships. With flexible business modules, ti&m creates a personalized digitalization strategy. The ti&m security suite provides the necessary security for all channels and makes the digitalization journey safer and faster. Together they set the benchmark for business digitalization. The ti&m approach is cost efficient with an extremely low cost of entry and compatible with most of the current security providers Read more, click here. Check demo, click here.

Billing is core to your business and is a great way to help you deliver the customer experience your customers and agents expect in today’s digital world. Can you afford it to get it wrong? However small an implementation may seem, it’s critical to get it right to ensure that your customers get billed correctly and pay the amounts owed to you, so that your revenue stream is not impacted. Plus, your agents expect that their commission to be paid to them on time for their book or else they won’t sell your policies. See also: Digital Transformation in Billing   Here are the top ten things to keep in mind for a successful billing implementation:

1. Modern billing systems are a financial system with a double entry T-Accounting system under its hood. Make sure you spend time understanding how various transactions work in your billing system, so that you can understand and explain to your customers how invoicing and accounting tie together.
2. Billing relies heavily on integrations for its data. Ensure that you have a good integration infrastructure in place and develop reconciliation reports for each integration. No matter what anybody tells you, only the systems can tell you the true story. Software is only as good as the data that goes into the system. Nothing is worse than a Billing system that is not in synch with the Policy system or General ledger.
3. Avoid big bang data migration, it’s not a good idea. The delinquency and financial data migration transactions are hard to migrate due to lack of data in the legacy system. The best approach for data migration is conversion on renewal. If that doesn’t work, and you must migrate, consider open balance data migration.
4. General ledger is the hardest and the most critical integration. Develop a mapping and aggregation sheet to map the GL transactions to Billing. Reconcile daily to find discrepancies timely.
5. Plan appropriately and test invoices for all transaction types, especially reinstatements to ensure the invoice schedule was restored to original state before cancellation.
6. Commission statements are critical to your agents. Follow a rigorous cycle of commission testing with all transaction types to keep your agents happy.
7. Design your delinquency workflows so that it can handle equity based cancellation process and at the same time respect the state mandated days for the cancellation period to keep your company in compliance as well as track and collect any uncollected earned premium.
8. Don’t bring on coverage level costs into Billing. Keep the costs at the PolicyPeriod level and your bills and transactions will be manageable.
9. Manage jurisdiction variability using extension tables instead of defining large number of payment plans. A large number of payment plans can be a nightmare to manage and every change in the fees will result in a new payment plan
10. Most importantly, adopt out of the box processes to keep the configuration to minimum and don’t forget reports. This will help your upgrade path in the future and ensure you can deliver data in a useful format.

See also: Time to Mandate Flood Insurance?   Getting your billing implementation right the first time around will help you deliver the billing information your customers and agents want, when they need it. Billing interactions provide an ideal opportunity to engage your customers and agents on a regular basis. Bills can be leveraged to let customers know how much they saved and provide them with actionable information. They can also be used to offer additional, personalized services. So instead of a burden, a bill becomes something of value itself. Exceeding your customers’ and agents’ expectations will lead to higher satisfaction, loyalty, and profitability.

We tie ourselves into knots trying to understand why more of our clients, who clearly love us so much, don’t tell their friends and families about us. I’ve written, at length, about why clients don’t refer and why they do, and I believe that understanding the answers to both questions is critically important. What I haven’t specifically addressed is how they refer. And how clients refer is almost as important as if they refer. We know, from our investor research, that very few referrals are actually introductions. If you think about it, two things need to be in place for a referral to result in an actual meeting.  First, your client has to make a compelling case for the value you deliver. Then, the prospect needs to be so motivated to talk to you, he or she will track you down and set up a meeting. I’ll go with "unlikely" on that one. The answer to the problem, of course, is that we need to find a way to encourage our clients to make direct introductions.  But how? At the risk of over-simplifying the solution, I’m going to over-simplify the solution: Ask clients about how they referred, and they will likely tell you. Then use that information to encourage more clients to refer (or introduce) successfully. See also: Two Checklists for Getting Referrals   So how do you go about it? Consider this: Identify five clients who have provided referrals over the last year and invite them to lunch or ask for 10 minutes of their time at the end of a review. They referred you to someone they care about (the world’s greatest indication of trust) so there’s a good chance they like you and will say "yes." Let the client know that you’re trying to understand more about how clients refer and that you would value their input. Try this on for size: I was really honored that you referred me to <insert name of client>. It means a great deal. I wondered if I could ask you a bit about that? From there, dig in on the circumstances:

• Did <he or she> ask you for an introduction to an adviser?
• Was there something about his/her circumstances that made you think we could help?

Probe on the circumstances, how your client’s friend raised the issue and why the client thought you could help. Had they experienced the work you do in that area, read about it on your site or learned about it through stories you shared? Then dig in on the process. Try this as a starting point: It’s interesting, but we hear that clients refer all the time, but we don’t often meet those clients. Can I ask how did you make that referral? Probe on whether your client shared contact details, sent the friend to your website or perhaps passed on information or articles you had written. Dig into whether there is anything you could do to make it easier. The way the client responds to the first questions will help you understand:

• What topics are clients discussing when they think of you (e.g., was it related to investments, to life or to retirement?)
• Did your client refer you prior to being asked for a referral, or did he/she wait for a clear indication that a referral was being invited?
• How do your clients perceive the problems that you can solve?

That information will help you craft stories that will help your clients spot a need for advice. See also: Restoring the Agent-Client Relationship The way the client responds to the second question will help you understand the specific ways in which they refer, and if and how that translates into introductions. It will also help you understand if there is anything you could do to facilitate more referrals or make introductions easier or more comfortable. A Bonus And you may just find that by asking the client to help you understand referrals, it reminds them that you are open for business. Not a bad result. Thanks for stopping by, Julie