Difference between revisions of "Funny Story About Selecting LDFs"

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My first job as an actuary in 1995 was as a summer intern at an auto insurer in Winston-Salem, NC. It used to be called ''Integon Insurance'', but it changed names a few times over the years and now I think it's called ''National General Insurance''. I started in the pricing department but at the end of the summer they hired me full-time and I transferred to reserving.  
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My first job as an actuary in 1995 was as a summer intern at an auto insurer in Winston-Salem, NC. It used to be called ''Integon Insurance'', but it changed names a few times over the years and now it's called ''National General Insurance''. I started in the pricing department but at the end of the summer they hired me full-time and I transferred to reserving.  
  
 
Anyway, one of my tasks in reserving was assisting the chief actuary in making LDF selections for the quarterly reserve review. We had data by '''accident quarter''' and '''development quarter''' so our triangles were huge. We were active in roughly 20 states at the time and our standard auto policy had I think 7 coverages. Then each of those roughly 140 combinations had its own set of triangles: ''paid loss, reported loss, paid counts, reported counts, ALAE, salvage & subrogation.'' That's a huge number of triangles of LDFs where we had to make selections.
 
Anyway, one of my tasks in reserving was assisting the chief actuary in making LDF selections for the quarterly reserve review. We had data by '''accident quarter''' and '''development quarter''' so our triangles were huge. We were active in roughly 20 states at the time and our standard auto policy had I think 7 coverages. Then each of those roughly 140 combinations had its own set of triangles: ''paid loss, reported loss, paid counts, reported counts, ALAE, salvage & subrogation.'' That's a huge number of triangles of LDFs where we had to make selections.
  
Our procedure was that I would make the first pass at selecting LDFs and this would take me a couple of weeks of early mornings and late nights. I would analyze the various triangles to try to understand what was going on. Was there a catastrophe? Tort reform? Adverse selection from a change in risk classification? Do I need to talk with product managers? It went on and on. And then how should I incorporate all of this information into make sensible LDF selections. To do this for a small number of triangles could be an interesting project, but with amount of data we had it was completely overwhelming.
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Our procedure was that I would make the first pass at selecting LDFs and this would take me a couple of weeks of early mornings and late nights. I would analyze the various triangles to try to understand what was going on. Was there a catastrophe? Tort reform? Adverse selection from a change in risk classification? Do I need to talk with product managers? It went on and on. And then how should I incorporate all of this information to make sensible LDF selections. To do this for a small number of triangles could be an interesting project, but with amount of data we had it was completely overwhelming.
  
When I'd finished, I'd pass several thick binders along to the chief actuary. In those days we still printed everything out. Then for the next week or so, I'd watch him in his office, thumbing through the pages, smoking, marking it up with a red pen. ''(Yes, smoking was still allowed in offices North Carolina back in the 1990s.)''. Then he'd dump it back on my desk so I could type the his changes into Lotus 123. ''(Lotus 123 is another throwback to the 1990s, an old spreadsheet program that doesn't exist anymore.)''
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When I'd finished, I'd pass several thick binders along to the chief actuary. In those days we still printed everything out. Then for the next week or so, I'd watch him in his office, thumbing through the pages, smoking his cigarettes, marking it up with a red pen. ''(Yes, smoking was still allowed in offices North Carolina back in the 1990s.)''. Then he'd dump it back on my desk so I could type the his changes into Lotus 123. ''(Lotus 123 is another throwback to the 1990s, an old spreadsheet program that doesn't exist anymore.)''
  
finish this story later...
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After a few quarters of this mind-numbingly boring task I couldn't take it anymore and here's what I did. I played around and created what I thought was a reasonable algorithm for the computer to select LDFs. I then went back a 2 quarters and used my algorithm to make <u>all</u> the LDFs selections, which took about an hour. All I had to do was write a macro to copy the formulas into the right place in all the different files that contained the triangles. When I summarized the results, I got a total reserve roughly equal to the official value. No real surprise as I had basically reversed engineered the algorithm. The real test was the following quarter.
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When the new arrived, I ran my macro. The computer selected all the LDFs and I got the estimate of the total reserve in about half a day. I wrote another macro to flag estimates based on criteria a changes in loss ratio, frequency, severity from last quarter in excess of certain percentage or values outside of a certain range. That let me pinpoint potential problems areas without having to look through thousands of numbers myself. I spent another day or two looking very closely at segments that were flagged or segments that had with the highest reserves Almost everything looked reasonable. The only numbers I didn't feel confident in were the LDF selections for the most recent 1 or 2 quarters, especially for

Revision as of 14:17, 15 August 2020

My first job as an actuary in 1995 was as a summer intern at an auto insurer in Winston-Salem, NC. It used to be called Integon Insurance, but it changed names a few times over the years and now it's called National General Insurance. I started in the pricing department but at the end of the summer they hired me full-time and I transferred to reserving.

Anyway, one of my tasks in reserving was assisting the chief actuary in making LDF selections for the quarterly reserve review. We had data by accident quarter and development quarter so our triangles were huge. We were active in roughly 20 states at the time and our standard auto policy had I think 7 coverages. Then each of those roughly 140 combinations had its own set of triangles: paid loss, reported loss, paid counts, reported counts, ALAE, salvage & subrogation. That's a huge number of triangles of LDFs where we had to make selections.

Our procedure was that I would make the first pass at selecting LDFs and this would take me a couple of weeks of early mornings and late nights. I would analyze the various triangles to try to understand what was going on. Was there a catastrophe? Tort reform? Adverse selection from a change in risk classification? Do I need to talk with product managers? It went on and on. And then how should I incorporate all of this information to make sensible LDF selections. To do this for a small number of triangles could be an interesting project, but with amount of data we had it was completely overwhelming.

When I'd finished, I'd pass several thick binders along to the chief actuary. In those days we still printed everything out. Then for the next week or so, I'd watch him in his office, thumbing through the pages, smoking his cigarettes, marking it up with a red pen. (Yes, smoking was still allowed in offices North Carolina back in the 1990s.). Then he'd dump it back on my desk so I could type the his changes into Lotus 123. (Lotus 123 is another throwback to the 1990s, an old spreadsheet program that doesn't exist anymore.)

After a few quarters of this mind-numbingly boring task I couldn't take it anymore and here's what I did. I played around and created what I thought was a reasonable algorithm for the computer to select LDFs. I then went back a 2 quarters and used my algorithm to make all the LDFs selections, which took about an hour. All I had to do was write a macro to copy the formulas into the right place in all the different files that contained the triangles. When I summarized the results, I got a total reserve roughly equal to the official value. No real surprise as I had basically reversed engineered the algorithm. The real test was the following quarter.

When the new arrived, I ran my macro. The computer selected all the LDFs and I got the estimate of the total reserve in about half a day. I wrote another macro to flag estimates based on criteria a changes in loss ratio, frequency, severity from last quarter in excess of certain percentage or values outside of a certain range. That let me pinpoint potential problems areas without having to look through thousands of numbers myself. I spent another day or two looking very closely at segments that were flagged or segments that had with the highest reserves Almost everything looked reasonable. The only numbers I didn't feel confident in were the LDF selections for the most recent 1 or 2 quarters, especially for