What wins in fintech: sales or data? -Forbes | CarTailz

From two major fintech conferences this month (Insuretech Connect and Money 2020) it is clear that fintech is evolving – but it is not clear which evolutionary approach will dominate. Startup innovation seems to split around a choice: build on either a sales advantage or a data advantage in the insurance industry.

In 2020, I wrote about the unique attributes of a successful fintech company, or the “3 Ds”: Sales, Data, and Delivery. I’ve argued that successful startups have at least one of the three, and especially one of the first two: sales or data. The best had more than one. Some even had a trifecta of all three.

But which of the Ds is most important? What Will Lead to More Consistent Multi-Billion Dollar Startup Results?

Let’s start with a few considerations. I promise I will give an answer at the end of the article.

Is the customer difficult to reach?

Some customer bases are easy to reach through easily accessible channels like social media or online television. Over 85% of Millennials shop online, and influencers, reviews, and social endorsements are a key factor in making decisions. Others are easily accessible through pre-built existing channels – think the car or auto insurance broker channel.

Some target groups are harder to reach. Older people may not be on social media. Medium-sized companies are confronted with more esoteric risks such as climate insurance for companies. you have the idea

As a rough simplification: If the customer base is more accessible (and willing to switch), a long-term sales advantage counts less. When the customer is difficult to reach, a sales advantage is crucial.

Is the product a specialty product or a commodity?

Certain products have well-understood parameters and dimensions. They are easily comparable between companies. Car insurance and bank accounts are clear examples. Of course, these can also be distributed more easily (e.g. online or via established channels).

A sales advantage with mass products is more difficult to achieve. The playing field can be leveled in online acquisition channel (e.g. bank accounts) or brokerage channels (e.g. car insurance). So the brand is very important. No wonder, since Geico spends $2 billion on marketing every year to gain notoriety.

For more commodified products, a Data Advantage can be used to build an edge. For example, companies like Root have promised to draw based on differentiated data (driving behavior). But unless the new data creates a massive underwriting advantage in standardized categories, ultimately distribution still matters. This allows specialized players to better value the customers they are looking for and gain market share.

More specialized products will allow suppliers to exercise greater pricing power. No wonder specialty insurance has much lower loss ratios and higher profitability.

There are, of course, several nuances here. Is there a willingness to experiment with new products? What are the switching costs like (e.g. is switching bank accounts and credit cards a challenge as automatic payment leads to stickiness)? How important is brand loyalty?

Is the market changing?

In a changing world, new risks and new needs arise. Some are already emerging today, most notably cyber and climate.

In insurance, new risks lead to new questions: How do damages manifest themselves? how big will they be Who will be affected? What behaviors today will postpone losses into the future?

Unfortunately, these are massive black holes with no clear answers.

If the product were available at affordable prices, customers would often ask for it to alleviate this uncertainty. But if mispriced, they could pose major challenges for the insurer. That is why data is more important in uncertain situations.

That’s one of the reasons why parametric climate is on the rise. As Nick Cavanaugh, CEO of Sensible Weather explains, “The availability and accuracy of remote sensing data – increasingly coming from satellites – combined with high-resolution computational models and scalable data processing architectures has made many parametric products possible for the first time. Purely data-driven risk products can now provide accurate coverage while dramatically increasing costs and operational efficiencies.” Parametric simplifies and controls the risk equation (e.g. Descartes in corporate and Sensible Weather in travel). Data Advantage.

Profit margin for product

Some products have low margins. For example, average auto insurance loss rates range from 60-70% (and in some cases over 100%). 80% is mandatory for ACA health plans. Other categories like extended warranty insurance are much more lucrative, with 50-60% profit margin including loss and also administrative costs!

If the margin is lower, so is the safety margin. As a result, data is more important in underwriting to ensure profits can be made at low margins.

Conversely, when margins are high, there is room for error. There must be data, but by spreading with a large enough margin of error, the data set can be built up over time.

The role of regulation

Some products are more or less regulated. For example, in home insurance, there are limits to how much an insurer can increase prices each year. If you’re in a region with changing weather patterns (e.g. fires in California or floods in Florida) – or have mispriced your policy for some reason – it becomes much more difficult and costly to rectify the error. ACA plans have a minimum loss ratio of 80%. If you don’t hit it, you will be penalized.

Without going into the benefits and trade-offs of the regulation (in general, I am to the consumer protection), the more regulatory limits there are to pricing and price changes, the more important data is.

Embedded Financial Services

Embedded financial services – by selling a financial product as part of a broader offering – have a built-in distribution advantage. This is the core value proposition. Therefore, the sales advantage of the original product or company is naturally the most important.

Embedded fintech also has a twist. It can enhance or improve the original product. Spot insurance includes health insurance as part of a ski lift ticket. In the event of an injury, the care experience is smoother and more integrated (and free).

And if the embedded insurance offering helps improve revenue conversion, the parent company can make money in a variety of ways (regardless of the profitability of the insurance product). For lending, this is one of the key incentives for merchants to implement “buy now, pay later”.

So which ‘D’ is most important?

The unsatisfactory answer, of course, is that it matters.

In my role as a venture capitalist, I tend to look for companies with uniqueness distribution advantages, but where a Data Moat can be built up over time through experience and scale. This is one of the benefits of embedded financial services, for example, as well as emerging risk categories with great potential for relocation (and the creation of multi-billion dollar businesses). This includes new risk areas (e.g. cyber) or changing ones (e.g. climate).

However, your answer to the same question depends on your strategy and business model.

where do you land

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