3 ms·

> I used to work for a Go shop. We dealt with financial data. People dealing with finance are THE MOST risk-averse people I know. No new tool will be used with

> I used to work for a Go shop. We dealt with financial data. People dealing with finance are THE MOST risk-averse people I know. No new tool will be used without years of vetting and it'll still be blamed if something goes wrong - even if the new tool never touched that bit of the process =) Source: Consulted for a finance company and it was Ye Olde Java and COBOL all the way down =)

Someone 2y ago
If they’re risk averse, they shouldn’t, as the OP claimed, implement basic algorithms such as rolling median, or finding a maximum instead of loading data into Pandas and doing a group by, would they?
classified 2y ago
I'm surprised they were adventurous enough to use Java.
- theshrike79 2y ago
  Someone picked Java at the start of the millennium-ish and they never dared to move away. =)
sanderjd 2y ago
Using Go for data analysis is not the risk averse choice. If the comment were "everyone was using excel and maybe R and I couldn't get them to use python", then the risk aversion comment would be spot on :)
lolinder 2y ago
It sounds like every single data operation in this shop was done with a "new tool" written on the spot in Go.
zerkten 2y ago
>> People dealing with finance are THE MOST risk-averse people I know. No new tool will be used without years of vetting and it'll still be blamed if something goes wrong - even if the new tool never touched that bit of the process =) What exactly do you mean by "finance" in your context? Even within a huge organization like Bank of America you can have an extremely conservative part and an innovative part. Obviously, most employees are likely working for the conservative part, but that doesn't mean that there aren't some people playing using modern technology. It just doesn't get evenly distributed, and you can be many layers from that usage in your department.
martinclayton 2y ago
My experience is different to that. I'd say people and businesses that best understand and balance risks against potential rewards are the most successful. I know a couple of skydiving accountants... Use of innovative tech in finance is one way for companies to gain an "edge" which can make them a lot of money. I wouldn't characterise people working in those particular areas as more risk averse. OTOH finance businesses (esp. those that manage other peoples money) are regulated and can't put new tech into Production without careful change control. But this evolves over time, and controls were looser in the past. There's a steady creep of regulation and control into tech used in finance outside and around IT: so called EUC (End-User Computing). This can be a source of "wrong tool for the job" syndrome. I've seen some hellish SQL written by non-IT people, but it got the job done. It's also an area where source code control, testing, and release processes are inevitably more human and error-prone. There is a culture clash internal to large finance between "move fast and break things!" and "nothing can change, ever - too risky!" This leads to a mixture of the very old and very new, and inevitably, more complexity. Achieving homogeneity once the heterogeneous is out of the bottle is very hard - attempts to do so often (always?) lead to a variation on the xkcd "Standards" situation https://xkcd.com/927/ https://xkcd.com/927/
murray-buttchin 2y ago
I don't think this is true of every financial institution. Nubank runs almost entirely on Clojure except for some of its Data Science tooling which is in Scala. Sure it's JVM, but it doesn't exactly scream risk-averse to me.
dagw 2y ago
Depends what you mean with "dealing with finance". If you're talking about core back office 'plumbing' the yes. Other parts are far more adventurous. Poke around any huge financial institution and you'll probably find everything from COBOL to some experimental in-house variant of Haskell.
noisy_boy 2y ago
People who are saying Finance == assembly/COBOL/Java either have never worked in the area or have decided about the elephant by touching a very small part it. Within a bank, you can have the accounting department using tested and tried approaches and/or vendor products whereas the machine learning group may be using the latest tech. But finance is not all banks - you can have non-banking financial orgs, rating firms, investment consultancies, private equity, hedge funds and on and on. A hedge fund probably uses super cutting edge stuff in one team while the other has been chugging along with stored procedures and Java. It is too big and varied to generalize.

Someone 2y ago

If they’re risk averse, they shouldn’t, as the OP claimed, implement basic algorithms such as rolling median, or finding a maximum instead of loading data into Pandas and doing a group by, would they?

classified 2y ago

I'm surprised they were adventurous enough to use Java.

theshrike79 2y ago
Someone picked Java at the start of the millennium-ish and they never dared to move away. =)

sanderjd 2y ago

Using Go for data analysis is not the risk averse choice. If the comment were "everyone was using excel and maybe R and I couldn't get them to use python", then the risk aversion comment would be spot on :)

lolinder 2y ago

It sounds like every single data operation in this shop was done with a "new tool" written on the spot in Go.

zerkten 2y ago

>> People dealing with finance are THE MOST risk-averse people I know. No new tool will be used without years of vetting and it'll still be blamed if something goes wrong - even if the new tool never touched that bit of the process =) What exactly do you mean by "finance" in your context? Even within a huge organization like Bank of America you can have an extremely conservative part and an innovative part. Obviously, most employees are likely working for the conservative part, but that doesn't mean that there aren't some people playing using modern technology. It just doesn't get evenly distributed, and you can be many layers from that usage in your department.

martinclayton 2y ago

My experience is different to that. I'd say people and businesses that best understand and balance risks against potential rewards are the most successful. I know a couple of skydiving accountants... Use of innovative tech in finance is one way for companies to gain an "edge" which can make them a lot of money. I wouldn't characterise people working in those particular areas as more risk averse. OTOH finance businesses (esp. those that manage other peoples money) are regulated and can't put new tech into Production without careful change control. But this evolves over time, and controls were looser in the past. There's a steady creep of regulation and control into tech used in finance outside and around IT: so called EUC (End-User Computing). This can be a source of "wrong tool for the job" syndrome. I've seen some hellish SQL written by non-IT people, but it got the job done. It's also an area where source code control, testing, and release processes are inevitably more human and error-prone. There is a culture clash internal to large finance between "move fast and break things!" and "nothing can change, ever - too risky!" This leads to a mixture of the very old and very new, and inevitably, more complexity. Achieving homogeneity once the heterogeneous is out of the bottle is very hard - attempts to do so often (always?) lead to a variation on the xkcd "Standards" situation https://xkcd.com/927/ https://xkcd.com/927/

murray-buttchin 2y ago

I don't think this is true of every financial institution. Nubank runs almost entirely on Clojure except for some of its Data Science tooling which is in Scala. Sure it's JVM, but it doesn't exactly scream risk-averse to me.

dagw 2y ago

Depends what you mean with "dealing with finance". If you're talking about core back office 'plumbing' the yes. Other parts are far more adventurous. Poke around any huge financial institution and you'll probably find everything from COBOL to some experimental in-house variant of Haskell.

noisy_boy 2y ago

People who are saying Finance == assembly/COBOL/Java either have never worked in the area or have decided about the elephant by touching a very small part it. Within a bank, you can have the accounting department using tested and tried approaches and/or vendor products whereas the machine learning group may be using the latest tech. But finance is not all banks - you can have non-banking financial orgs, rating firms, investment consultancies, private equity, hedge funds and on and on. A hedge fund probably uses super cutting edge stuff in one team while the other has been chugging along with stored procedures and Java. It is too big and varied to generalize.