Why I'm sipping on $LMND
THREAD TIME
@Lemonade_Inc A digitally-native insurance platform featuring
a) AI & machine learning to more accurately price risk & more affordably price plans
b) Philanthropy to make a shady industry friendlier
c) A quick, transparent buying process
THREAD TIME
@Lemonade_Inc A digitally-native insurance platform featuring
a) AI & machine learning to more accurately price risk & more affordably price plans
b) Philanthropy to make a shady industry friendlier
c) A quick, transparent buying process
The machine is learning:
In 2017: $LMND AI bots (Jim & Maya) handled 6% of inquiries.
Today 32%
There is every reason to believe the % will continue rising for this less than 4 y/o company.
Fosters lower customer acquisition cost that company passes on to users. (see below)
In 2017: $LMND AI bots (Jim & Maya) handled 6% of inquiries.
Today 32%
There is every reason to believe the % will continue rising for this less than 4 y/o company.
Fosters lower customer acquisition cost that company passes on to users. (see below)
AI edge:
$LMND loss ratios improve w/scale; opposite of competition.
(Loss ratio=$ paid in claims/$ collected in premiums)
$LMND: .67
Industry ave: .82 (low is 👍)
Machines > human mind @ scaling
A young company used AI to be 15% better at pricing risk than 100 y/o firms.
$LMND loss ratios improve w/scale; opposite of competition.
(Loss ratio=$ paid in claims/$ collected in premiums)
$LMND: .67
Industry ave: .82 (low is 👍)
Machines > human mind @ scaling
A young company used AI to be 15% better at pricing risk than 100 y/o firms.
How Maya & Jim enabled loss ratio lead:
They ask a fraction of the questions an agent asks yet can generate 100x the data & can digest it all.
That is the root of $LMND 's loss ratio edge
More data = more insights & more precise risk quantification... AKA more profit long term
They ask a fraction of the questions an agent asks yet can generate 100x the data & can digest it all.
That is the root of $LMND 's loss ratio edge
More data = more insights & more precise risk quantification... AKA more profit long term
@Lemonade_Inc service is about the consumer
a) Impressive savings
b) Buy plan in mins
c) Get claims immediately
d) Charitable giving
70% users below 35
$LMND aims to win users early & grow w/ramping needs
Premium per user up 17% y-over-y👀
Users up 84% to 814,160 y-over-y👀👀
a) Impressive savings
b) Buy plan in mins
c) Get claims immediately
d) Charitable giving
70% users below 35
$LMND aims to win users early & grow w/ramping needs
Premium per user up 17% y-over-y👀
Users up 84% to 814,160 y-over-y👀👀
More encouraging trends:
A homeowner plan yields 6x the premium of a renters plan. $LMND merely needed to be its user-friendly self for this to happen in just 3 yrs (see below)... no incremental investment $.
This means margin expansion. I like margin expansion 🙂.
A homeowner plan yields 6x the premium of a renters plan. $LMND merely needed to be its user-friendly self for this to happen in just 3 yrs (see below)... no incremental investment $.
This means margin expansion. I like margin expansion 🙂.
Philanthropy meets Insurance:
Insurance companies stink; all have incentive to deny claims for profit... until now
$LMND pays excess claims to a user's favorite charity
This removes conflict of interest.
YES = lower profit today.
I believe it = larger market share tomorrow.
Insurance companies stink; all have incentive to deny claims for profit... until now
$LMND pays excess claims to a user's favorite charity
This removes conflict of interest.
YES = lower profit today.
I believe it = larger market share tomorrow.
It's working:
Note: rev rec policy & usage of re-insurance means $LMND cannot recognize large chunk of premiums
To me, premium metrics are best growth barometers.
In Force Premiums (total annualized premiums): grew 115% to $155 mill
Earned premiums: grew 121% to $35.3 mill
Note: rev rec policy & usage of re-insurance means $LMND cannot recognize large chunk of premiums
To me, premium metrics are best growth barometers.
In Force Premiums (total annualized premiums): grew 115% to $155 mill
Earned premiums: grew 121% to $35.3 mill
Ideal industry for disruption:
No fortune 100 insurance company has more than 4% market share.
This is a massive, fragmented industry meaning $LMND does not need to displace deep-pocketed incumbents to win. This is important to me.
No fortune 100 insurance company has more than 4% market share.
This is a massive, fragmented industry meaning $LMND does not need to displace deep-pocketed incumbents to win. This is important to me.
Summary:
@Lemonade_Inc is ahead of incumbents in machine learning, AI & tech... & therefore pricing risk.
Built a user-centric platform
Growth speaks for itself
@daschreiber & @shai_wininger integrated philanthropy into biz model to fix inherent industry conflict of interest
@Lemonade_Inc is ahead of incumbents in machine learning, AI & tech... & therefore pricing risk.
Built a user-centric platform
Growth speaks for itself
@daschreiber & @shai_wininger integrated philanthropy into biz model to fix inherent industry conflict of interest
A final note:
I am not expecting profitability for a long time. If you are strictly a value investor look elsewhere. 🙂
This is a high risk, high volatility investment.
$LMND will be focused on growth & this story will take yrs to play out
Very long $LMND
I am not expecting profitability for a long time. If you are strictly a value investor look elsewhere. 🙂
This is a high risk, high volatility investment.
$LMND will be focused on growth & this story will take yrs to play out
Very long $LMND
Legacy insurance agents are currently trying to convince me that their industry isn’t actually naturally shady.
The argument needs work.
Long $LMND
The argument needs work.
Long $LMND
