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How I Prepared my Finances Before Bootstrapping Earlier this month to work for myself. I am 35, living in Seattle with my wife and two small kids, ages 2 and 4. I’m starting this quest for an independent lifestyle with no business and household income yet, and my target is to cover my family’s expenses from my new work before I run out of savings. I left my cushy developer job at Amazon Savings Due to extraordinary luck and being in the right place at the right time, I managed to save a good amount of money in the last 5 years. My net worth was negative in 2013, but it now stands at around $1.4M, with $1M in liquid assets and the rest in home equity. That entire $1M, minus a small amount, is at stake in this venture. In fact, I’ve already mentally . written it all off On my savings balance I’ve set a surrender threshold of 6 months’ worth of expenses, and if it dips below that line I will abandon this route and go get a job again. I’m quite confident I could find a job within a couple of months that makes ends meet, but I’ve reserved six months coverage just for the extra precaution. I realize that $1M in savings is an exceptional amount of money for many people considering a similar path. However, I believe I would have still left my job and gone this route even with savings that covered just 1.5 years of expenses. One year of runway is a reasonable amount of time to give something a shot, with the other 6 months to fall back to the job market if things don’t work out. Also, remember that even if you start with one year of covered expenses, the runway will grow longer as soon as you start making money. You don’t need to break even immediately within the first year. For example, in my case, I’m starting with 5.5 years of covered expenses. If I simply manage to add $250 of linear income growth per month, I will break even with my expenses in my fifth year while still staying abundantly clear of my surrender threshold. This projection is what gave me the most confidence in taking the plunge now rather than continue to defer it. Adding $250 per month with a digital product in a global marketplace seems doable. For example, if I built a $50/month SaaS, all I’d need is 5 or 6 net new customers per month (depending on operating costs). I’m not expecting it to be easy, but I can see this happening. Expenses I admit that it would have been hard for me to regress my standard of living, especially with a family. In fact, I promised my family that our lifestyle wouldn’t have to change because of this experiment I’m doing with my career. We did seriously consider moving 30 miles out of Seattle, where houses cost $350 per sq. ft rather than $500, but my family wasn’t enthusiastic about being far away from our current community, and it wouldn’t have made a big difference to my runway anyway. Here are my current cash outflows, averaged per month: +--------------------------------------------+---------+
| Mortgage                                   |  $4,000 |
| Property tax                               |    $870 |
| HOA                                        |    $250 |
| Home insurance                             |    $165 |
| Health insurance                           |  $1,250 |
| Life insurance                             |    $115 |
| Disability insurance                       |    $165 |
| Auto insurance and registration            |    $185 |
| Utilities                                  |    $800 |
| Groceries and other essentials             |  $2,000 |
| Nanny and cleaning services                |  $1,800 |
| Preschool and kids activities              |    $800 |
| Budget for infrequent or unexpected things |  $2,600 |
+--------------------------------------------+---------+
| Total                                      | $15,000 |
+--------------------------------------------+---------+ The last item is a very conservative budget, and barring any emergencies, I don’t expect to have to spend it all. But the rest are basically my fixed costs. If the circumstances were different, I might have looked at trimming some of the expenses, but it actually doesn’t make much difference in my situation. Obviously, I still retain the option of trimming some expenses in the future, but I’m not expecting to do so right now. Health Insurance When I was with Amazon, I paid $290/month for a family health plan with a $4.5K deductible and $9K max out of pocket. gave me the option of staying with the Amazon plan for 12 more months at a cost of $1,450/month. When I first looked at alternatives in the ACA marketplace, there was only one insurer in Washington state. It was more expensive than COBRA, and it didn’t cover any of our preferred doctors. But in 2019, two other insurers showed up, and one of them offered a plan with our doctors in-network for $1,125/month, with a $14K deductible and $14K max out of pocket. I’m fine with the high deductible, as I only want health insurance so that I don’t go bankrupt if I get into an accident or get cancer. So I went with that plan. COBRA It also turned out that Washington state if you have kids and you buy health insurance through the ACA marketplace. I wouldn’t have bought it if it was optional, but since I had no option family dental coverage added another $125/month to the bill. requires the purchase of dental insurance I was able to enroll in the new plan before I left the job, and I didn’t need to provide any evidence or documentation for the special enrollment. Life Insurance I bought $5M term life insurance for 15 years with a $1,365/year premium. I did my search through the Geico website, which uses the broker behind the scenes to aggregate options from many providers in a neat table where you can play with different term lengths and different benefits. I added a feature called living benefits to my coverage, which for an extra $200 premium allows you to withdraw the benefit early in case of a terminal illness. LifeQuotes My experience with LifeQuotes was okay. The whole process from applying online to activation took nearly 3 months, which was longer than I expected. Apart from a health check, the underwriter also required tax returns and detailed asset disclosures. I don’t really know why they needed that, but I suspect the financial situation of the insured might be linked to fraud risk — even though it seems difficult to commit fraud with life insurance! I completed this process while I was still employed, but I think it wouldn’t have been a problem doing it after I left. However, I still recommend getting life insurance while employed, since it makes the financial questions much simpler to answer. Disability Insurance For disability protection I bought insurance that pays $10K/month until age 65 in case I can’t program anymore. The premium is $2K/year, and the policy is guaranteed renewable at the same cost. Unlike life insurance, I think it is very important to get disability insurance while you are still employed, because the policy is designed to pay if you are unable to continue doing the same type of job you have at the time you buy the insurance. They do employment verification and are more rigorous about health history and financial disclosures than the life insurance underwriters. I would actually have preferred to get $15K/month, but since I also had disability insurance of $25K/month from Amazon, my total benefit would have exceeded my salary, and the underwriters consider that over-insurance. Again, I suspect this has to do with fraud risk, because they really insisted on not taking my money. At least the benefits from disability insurance obtained privately are not taxable, so I would be able to keep the whole $10K/month if I ever were to claim. I searched for this insurance through an online broker called . The overall experience was better than LifeQuotes, and the process was completed in 2 months. Policygenius Umbrella Insurance I bought $1M for just $137/year with a single click from their website. I already had auto and home insurance with them, and this policy extends the liability coverage after the first insurance is exhausted. Coverage through the website is limited to $1M, and you have to call to request higher limits up to $10M. I might add more coverage eventually if the cost continues to be around $150 per $1M. umbrella insurance from Geico While I was on the Geico website, I also made sure that I was maxed out on all the liability coverage on my auto insurance. I have it at $1M injury and $500K property damage, which is the maximum allowed. To lower my premiums a bit I increased the deductible to $2,500. Just like with health insurance, I don’t need insurance for repairing a scratch. I just want it to avoid financial ruin. Retirement Savings I have only been in the US since mid 2012, and I’ve maxed my 401K contributions ever since. I’ve accumulated about $180K in my 401K account thanks to the bull market, and I consider this money, minus tax and early withdrawal penalties, to be part of my liquid savings. This might shock people who consider early withdrawals as something you would only ever do under extreme hardship, but for me this is just another form of optionality. I don’t intend to do an early withdrawal, but this is money like any other. As a small optimization, I will likely sometime this year. The conversion will require me to pay income tax on the $180K, but since this year’s tax brackets will likely be the lowest I will ever be in, this seems like a good strategy. A Roth IRA grows tax-free, and withdrawals are not taxed. convert my 401K to a Roth IRA Home Equity I bought my first home at the peak of the bubble in 2008 (outside the US), and when I sold it in 2014 I had to write a check to the bank instead of the other way around. I had better luck later when I bought my current home in Seattle just before the market spent . My home equity grew by about $400K in 3 years, and just before I left my job I refinanced my mortgage to cash out $250K of that equity. I didn’t really need the extra cash, but I figured that liquid cash in the bank adds optionality, and it would have been hard or impossible to refinance later without a high income stream from a steady paycheck. I’ve put the cashed-out money into short-term US treasury bonds at 2.5%, and after paying the bank 4% interest this $250K is only costing me $3,750 per year. 20 straight months as the hottest in the country It took me about 3 months to close the refinance, but that’s because my property is in a mixed-use zone, which spooked many lenders. A regular single-family home should be able to be refinanced in about a month. My total closing costs were about $3.5K. While I was shopping for the refinance, Key Bank also offered me a $150K line of credit at 5.5% interest at no cost and with no withdrawal obligations. They didn’t even require an in-person appraisal. I took that as well, and it closed within a couple of months. Investments I’ve put 70% of my savings in short-term US treasury bonds and about 10% in CDs, both of which pay about 2.5% right now. I picked up some CDs not for the slightly higher interest rate, but out of paranoia, just in case the US government does something unthinkable. The other 20% is in a few tech stocks that I’ve held on to for a long time. It wouldn’t be a bad idea to convert those stocks to treasuries as well, but I enjoy a bit of speculation on the side. Also out of paranoia, I’ve split my positions across two brokers. Since I’m going to depend on this money to put bread on the table, I didn’t want all my eggs in one basket. If you liked this article, you can as I continue to document how I’m pursuing my new independent lifestyle. follow me on Twitter Not my investments Originally published at danielvassallo.com on February 26, 2019.

From Employee to Bootstrapper

I wrote a Now I want to dig a bit more into that. short piece some time ago on how AI is going to affect the insurance industry. I. A bit of background The insurance sector is one of the most old-fashioned and resistant-to-change space, and this is why AI will have a greater impact on that with respect to more receptive industries. The collection of data of new types (i.e., unstructured data such as reports, images, contracts, etc.) and the use of new algorithms are disrupting the sector in several ways. Traditionally, an insurance company followed this type of process: Identifying pool of customers whom might be risk-assessed; Targeting those customers and assessing the risk for each class; Selling differently priced policies spreading the risks over the pool of customers; Try to retain those customers as long as possible offering lower price for longer contracts. This is a really simplistic representation of the insurance business in the last fifty years, and I am aware that insurance experts might disagree with me in many different ways. There are a couple of further features to be pointed out: first of all, insurance has historically been , which means that brokers and agents were essential to tracking new customers and to even retain old ones. In addition, it is an industry which is by definition rich of data because they collected anything they could, but is also one of the less advanced because either many of those data are unstructured or semi-structured, or the model used are quite old and simple. sold not bought Most of those data were easy to obtain because they were required to correctly price the coverage, while additional complimentary data were provided only by good customers who had incentives in providing as much data as possible to get a cheaper policy. Of course, this works the other way for bad customers, and this is a perspective on the phenomenon of “ ” (i.e., bad customers are going to ask an insurance because they feel they will need it). adverse selection The adverse selection issue is though only one of the intrinsic challenges of the sector: , high level of attempts, and are other features any incumbents should take care of. It is interesting to notice though that some of those are also specific barriers to entry for startups: they might attract indeed people who normally can get affordable insurance with a bigger competitor (adverse selection) and they usually have the capabilities for breaking down the risk complexity but not to support the funding need for risk coverages (so they need to work with incumbents rather than trying to replace them). strong regulation fraud complexity In spite of those problems, in the last decade, we noticed a new trend emerging. Insurances, in the effort of trying to reduce problems, they started offering . This occurred either through a questionnaire (asking the customer for further data in exchange for a lower price) or through devices (healthy devices, black boxes, etc.). The real issue though has been the engagement side of this proposal, because of the opposite nature of information, rewards, and human nature. The rewards offered were indeed either temporary or provided only once and people got lazy very quickly, while the information stream needed to be constant. moral hazard premium discounts to their final customers in order to get extra information directly indirectly The following step has been the introduction of apps to let customers monitor by themselves their own data and behavior, sometimes even given away for free the device itself. Leaving the customer with full power on his data had though an inverse effect, because people did not have the motivation in tracking down their improvements, and they got upset at the same time because they felt they were not getting the most out of that opportunity. Regardless of the specific innovative way in which insurers engaged customers, the process used in the insurance business did not change much in the past century. and dominated the sector setting the rules to be followed in internal workflows, but this is slowly changing with intelligent automation systems. We are actually migrating from rule-based decision systems to statistical learning and eventually machine learning. Expert systems knowledge engineering Image Credit: http://www.creativityatwork.com/2014/06/10/busy-innovate/ II. So how can AI help the insurance industry? AI is helping (or disrupting, depending on how you see the matter) the sector in different ways. First of all, it can help problem which has been just mentioned. The abundance of data can be used indeed to refine the customers’ segmentation and provide personalized offers based on personal features. It also helps in through smart automatization or RPA (robotic process automation). increasing the customer engagement and retention reducing the costs Second, AI is making people , and it is driving them toward better behaviors. more aware of the risks as well as habits Furthermore, the better pricing and risk assessment that AI is introducing analyzing more granular data will make some people (i.e., too risky to be fairly priced and covered) as well as to turn back some previously uninsurable people into insurable customers again. The governments or central regulatory agencies should then start thinking about a “ ” in which they intervene subsidizing the cost of relevant insurances (e.g., basic health coverage) in order to “ . uninsurable pricing/risk threshold guarantee the uninsurables” Finally, it might be useful to think in terms of what an insurable risk is in order to see how AI can help with that. According to Jin Park (Assistant Professor at IWU), an insurable risk is identifiable through the following five conditions: Large number of similar exposure units (mutuality); Accidental and unintentional loss (not predictable and independent from the insured customers); Determinable and measurable loss; Calculable chance of (not catastrophic/systemic) loss; Economically feasible premium. AI is going to affect all those features: with a better and more detailed customer profiling, we won’t need indeed to have such a large base of insured units. It will turn some frequent events into accidental (e.g., affecting drivers’ behavior it will reduce the basic accidents into rare events) and it will improve our ability to forecast and compute both the probability and magnitude potential losses even in those cases too hard to be managed before. All the previous improvements will make many more premium under budgets, and therefore the conclusion is that AI will “ ” the threshold of what we consider nowadays an insurable risk, and it will make then more risks insurable. lower Image Credit: iStock III. Who are the sector innovators? There are plenty of startups out there working at the intersection of AI and insurance, and it essential to look at least at some of them to understand the future direction of the industry, as well as the kind of improvements AI is having in the insurtech space. An interesting thing to notice is that most of the innovation is happening in the UK rather than other countries, in all the segments proposed below. skims the valid claims from the ones that deserve further validations; instead is trying to automatize experts task for insurances; has a specific focus on car claims; optimizes internal business processes, as well as does; offers instead mobile claim management solutions; and finally aims to help insurers to deliver on-premise smoothing the claiming flow. Claim processing: Shift Technology Tractable ControlExpert Cognotekt Snapsheet Motionscloud RightIndem : is an automated insurance agent who helps you buying any insurance coverage you might want; is a virtual assistant that offers customer care services; identifies which leads intend to purchase, while is a personal health assistant that analyzes symptoms and produces pieces of advice. instead uses EMR (medical records) to assist the patient as it was a virtual doctor, and gives medical advice taking care of tight budget constraints. is another personal insurance agent who works as a comparator for car insurances. Virtual Agents & Chatbots Spixii Cognicor Conversica Your.MD MedWhat Babylon Insurify What today is called simply chatbot is going to be renamed in a few years There are already few examples of companies toward that goal: is indeed an intelligent comparator which identifies gaps in coverage for the customer and looks for the best solution that fits customer’s needs and characteristics, while implements real-time video analytics to keep drivers safe(r). More generally, robo-insurers will be a quite wide class of agents who will end up providing different services, all of them with the final goal of helping the clients to undertake risk-mitigating actions and only cover the real (residual) risks. robo-insurer. Risk Genius PolicyGenius Drive Spotter : is probably the most successful insurtech company out there, with the final goal of making insurance simple and accessible to everyone through a great UX. Similar to Oscar is somehow , while is a tool that helps customers in understanding their own needs and facilitates in one place all the insurance coverages in place, in a similar fashion to . instead creates personalized offers and relevant products based on customer’s characteristics. uses machine learning to convert handwritten files into structured data, and this can be used to better understand the final customer. Finally, ranks the service of insurers to the benefit of the client. Customers engagement Oscar Stride Health Brolly Knip Adtelligence Captricity ValChoice : connected cars and telematics is a pretty big area itself (see to know more about it), but it would be worthy to point out the work that , , and are doing in capturing driving behaviors and habits as well as computing fuel efficiency. works similarly, although it uses smartphone data and mobile devices habits. is trying to revolutionizing the UI/UX within vehicles, displaying information in such a way that the driver does not get distracted. uses vision technology to provide real-time feedbacks to the driver. Telematics CBinsights article Greenroad Vnomics Telogis Cambridge Mobile Telematics Navdy Lytx : AI can be (and actually is) used to spot out hidden correlations to granularly segment customers and risks in a more efficient way. Even though it might in theory possible to identify some algos that could perform better than others (see the work for fraud detection), data always come first, at least for the next close future. Many companies operate in the space, as for instance that provides predictive algorithms and data products for property and casualty and life insurances through the analysis of public data (e.g., social media data). created a machine learning risk management platform, while uses unstructured data to optimize the underwriting and claims process. collects data from wearables and formulates health scores for a better risk assessment, while uses computer vision techniques on geospatial data to improve the level of detail on current houses conditions. creates a more accurate representation of the medical datasets to be used for underwriting purposes by insurances, similarly to that offers also apps products. provides also low-cost insurances, while uses AI to assess the risk of policy applications. A more accurate underwriting can even translate into covering events that are today quite risky (e.g., as and , and are doing for weather risk management). Underwriting Wipro did Carpe Data Atidot Tyche Big Cloud Analytics Cape Analytics Dreamquark FitSense Melody Health Insurance Uvamo MeteoProtect Praedicat Finally, on a side, it is worthy to point out to pure technological enablers as , which offers a management tool to the insurance providers to manage effectively and timely new products launched; , a cloud-based platform for insurance brokers; and finally, is instead an e-commerce provider for product insurances. Instanda Insly SimpleInsurance : , , and are peer-to-peer insurance startups focusing respectively on property and casualty insurance the first two, and car insurance the latter one. P2P insurance Lemonade Friendsurance Guevara : these are companies in the insurance sector that are driven by . offers real-time AML for bitcoin specifically, while is a permanent immutable ledger for diamond certification. is instead a stealth-mode company working on the standardization of smart contracts. provides a P2P supplementary unemployment insurance product, while provides micro-insurance policies on the blockchain. covers multiple parties with insurance cover at short notice and for varying periods, and finally, is another P2P insurance platform run on the blockchain. Insurchain & Smart Contracts blockchain technology Elliptic Everledger Luther Systems Dynamis Saldo.mx SafeShare Teambrella : this class of startups put in customers’ hand the entire insurance buying process. is probably the best example of this new class of players and it allows to ensure things by simply taking a picture of them. is quite similar but with a focus on car insurance, and on travel policies, and is another example of on-demand insurance. But this class does not include only the proper on-demand business model, but also insurance startups which provide products that vary by location, time, use, or customer. In other words, pay-per-mile business model ( ), micro-insurance policies ( ), or eventually Insurance-as-a-service models ( ). Insurance on-demand Trov Cuvva Sure Airsurety Back me up Metromile Neosurance Digital Risks IV. Concluding Thoughts which constitute the insurance profit structure: premium earned and the investment income from one hand, and underwriting cost and claim expenses from the other. AI is and will be able to improve the cost structure, increasing at the same time the competitiveness and enlarging the customer base accessible to insurers, while optimizing internal processes and enhancing the transparency and robustness of the compliance flow. Yan identifies four elements The greatest challenge I still see in insurance is the which might prevent insurance to adopt early AI solutions, although this won’t probably have a long life given the incredible pressure to innovate the insurance providers are undergoing through. cultural mindset — — Follow me on Medium Look at my other articles on AI and Machine Learning: Artificial Intelligence Classification Matrix What you are too afraid to ask about Artificial Intelligence (Part I): Machine Learning Who is best positioned to invest in Artificial Intelligence? A descriptive analysis

Artificial Intelligence Verticals (I): Insurance

AXA Strategic Ventures (ASV) invests in deep machine learning technology poised to transform the Internet of Things (IoT) AXA Strategic Ventures invests in , a company that uses machine learning to create a digital identity map of individuals Neura This investment completes the recent four investments done over the second half of 2015 in the U.S.: Bee, PriceMethod, GoldBean, CoPromote AXA Strategic Ventures (AXA SV), a global €230 million venture capital fund, announces today it is l . eading a $11 million Series A funding round for Neura Neura’s technology can be utilized to enable smarter healthcare, cars, music services, homes and much more. The service lets people get to an unprecedented level of technology personalization, by computing a constantly updated portrait of user behavior patterns. Simply put, Neura enriches apps and devices with insights about users’ past and present actions, as well as calculated predictions about the next thing they’re going to do. This Series A round, co-led by and Pitango Venture Capital and with participation from Liberty Israel Venture Fund and Lenovo Group, will enable Neura to further realize its technological and business potential. Coinciding with the first open release of Neura development framework, designed to let developers personalize and contextualize their products, the new capital will be used to expand Neura’s business reach and make the service ubiquitous. AXA Strategic Ventures ” said . “ ” “Neura is poised to deliver on the promise of IoT — improving our quality of life through smart technology. They do this with a singular and unique focus on the user. The result will allow various industries, including insurance, to better serve users at the time of need in the most convenient and transparent method possible, Manish Agarwal, General Partner at AXA Strategic Ventures in New York We believe Neura’s approach is disruptive and is going to change the way we use and interact with data and devices on a daily basis in the future. This Investment in Neura completes the recent four investments done over the second half of 2015 in the U.S.: · is building the bank of the future:a mobile-first, in-person bank for all Americans. Bee · is a predictive analytics company that provides technology to enable accommodations marketplaces and property owners to operate more efficiently through optimized, automated and now guaranteed pricing. PriceMethod · provides advice, education and low-cost trading for financial beginners. By analyzing members’ actual spending, they create customized portfolios featuring successful companies and brands that users love, know and buy. GoldBean · has built the world’s largest programmatic influencer marketing platform with over 800,000 content creators reaching more than 1.6 billion people a month. CoPromote ”, said . “ ”. “AXA is now accelerating its investment in innovative and disruptive start-ups. I believe it is critical in order for us to utilize the technology and data revolution as an opportunity to grow faster and to continue to improve the interactions with our clients Francois Robinet, Managing Partner, AXA Strategic Ventures The start-ups on which we have invested over 2015 are all relevant for us not only as investment but because of what we can develop together with them These five companies join AXA SV’s portfolio, which also includes investments in PolicyGenius, Limelight Health, VolunteerSpot in the U.S. and Climate Secure, Easy Proprietaires, Evercontact, Flyr, Fundshop, Widmee, Netheos, Particeep and Art2M in Europe.

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