[Havoc]

For those in the finance space, are you actually seeing any real AI tools being used? Like for actual operational tasks?

I've really only seen it used for research / exploration thus far. Either for economic research slide deck or for exploring trading hypothesis

[OkayPhysicist]

On the spend management side of things, I've found pretty remarkable success in letting LLMs check "does this receipt match this reimbursement request and based on all the information about the user, the request, and our policy, is it appropriately allocated to appropriate GL, Location, Department, and Project codes?" If the verification step fails, it kicks it back and the user can either override it (which gets it flagged for AP review), or fix it. It does substantially better than the naive Bayes classifier I was using before.

[ofjcihen]

I’m not saying your implementation is bad or anything but my visceral reaction to this was “I’m glad I’m not on the other side of that”

[JamesSwift]

Why? It sounds exactly like the design I would hope for. It automates what I'm going to do already without needing to wait. And it allows you to bypass it entirely and just revert to the manual process (along with waiting).

[sholladay]

That all sounds reasonable until you realize that the same logic is how we ended up with customer support systems that try to walk you through a phone tree and if you are lucky, you will be able to press 0 to speak to a human without answering a bunch of questions first and being referred to the online help articles.

Do you enjoy using any of those systems? Do you want the world to be that way?

[JamesSwift]

Maybe we are interpreting the GP differently. In this scenario, the phone tree is doing the same questions that the human agent is going to do but does it immediately when I call rather than "waiting for an operator" to ask me those questions. And as long as I can "press 0 to eject" (just like I can in the accounting scenario, then its completely kosher to me.

[stubish]

No, we end up with crappy systems because people are optimizing to save money over providing a good service. OP has simply replaced the traditional room full of clerks applying policy rigorously with a baysian algorithm and now AI. The management and oversight is still in place, and that is what makes a system that doesn't suck. To make it suck and save money, you remove access to that oversight or just remove it all together. And falling down that slippery slope is not inevitable, even if it sometimes seems like it is.

[KellyCriterion]

Regarding customer support on phone: I usually have lock with just waiting and not responding to the tel bot, very often you are routed to a human at the end :-D

[mikeyouse]

In many businesses, the employee is responsible for inputting most of that. If a LLM can get to 95% accuracy and flag exceptions, the employees (and AP team) would actually have less work and bureaucracy.

Though we’ve had a few incidents where employees have submitted AI-generated receipts for reimbursement which is another issue..

[notahacker]

It's already pretty common for some sort of tool involving some sort of AI to collect receipt data and attempt to categorise them and hook up to your accounts. They also make mistakes, though the advantage of more tractable, less configurable and more limited models is they're unlikely to interpret a prompt as "invent receipts that have never been submitted" or "delete records", as well as trained much more on receipt OCR and less on poetry....

As a business, you've also got to remember that employees are much more likely to complain if the 'agent' or any other form of automation errs by denying their claim or underpaying than the reverse. Depending on the scale of expenses and how likely you are to be audited, the cost of the odd mistake might be more or less than the cost of doing it manually.

[Zopieux]

Please tell me those are former employees. How can anyone feel confident committing such blatant fraud.

[mikeyouse]

Yeah the ones that were just fraud we termed almost immediately.. there were a few in the middle ground of where they’d lost their receipts (or decided that fabricating a receipt was easier) but we could verify that the expense actually took place from a cc statement. We added an extra approval step for those employees going forward which is annoying for everyone involved so hopefully they’ve learned their lesson there.

[infecto]

What is your point? This is pretty normal expense management in any company setting. I don’t know what is so bad about being on the other side of that. Hope I am not too inflammatory by asking what is the point but genuinely you pointed it out like it’s some archaic process flow but it’s part of almost every expense system.

[ofjcihen]

I guess my current company’s processes may be easier to deal with than others. That or my position affords me some extra catering to.

The system is currently using a simple app to submit expenses and any issues gets a simple human chat request and a call if requested.

They try to avoid kicking anything back and if they do they make sure it’s reviewed first to make sure that it’s needed and to make sure the reason is understood.

Our company is also very large so I’m not sure how they manage but they do. People rave about the process instead of hating it.

[infecto]

Thanks for the thoughtful reply. To add some color… most expense systems are setup so that the user has to input a couple fields like the category or GL code. Some of the fields might be auto populated. Some companies might not care about the classification but usually the intent is to capture things like travel or software etc. What was described earlier is really not painful for users most of the time but a LLM helps automate so much of it these days.

[infecto]

Yes. On the accounting side agents can handle a lot of the low value work like recons and other ledger activity pretty well. On the investment side I think like you pointed out it’s going to be a lot of research, industry, company, macro etc. Value in letting run on top of the data you have and put together ideas at a quicker pace than a human can. There is still a human in the loop but it can do a nice job of lining up thought you might have otherwise missed.

[Havoc]

What does the integration look like on accounting? Is this a tool provided by the accounting software provider?

I'm in that space so naturally interested in what people are up to :)

[j_w]

Likely "dump all your data into our system then we provide you AI tools." Typically how it goes with most fintech startups.

[TacticalCoder]

> For those in the finance space, are you actually seeing any real AI tools being used? Like for actual operational tasks?

> I've really only seen it used for research / exploration thus far

Summaries and translation for sure.

Speaking with devs in the field I know that AI tools are used to summarize and extract data from... PDFs. Now, thankfully, LLMs got better at answering "How many 'r' in 'strawberry" and it looks like they're good enough for summarizing PDFs and extracting key numbers but I'd still be cautious.

And I've got a friend who's a translator specifically for financial documents: she's a contractor and getting about 1/10th of the work (and 1/10th of the pay) she used to have for now she's only tasked to verify that the translations are correct. Of course she already had lots of tools, way before he LLM era, automating some of her work but she was still billing he use of those tools. Now LLMs are doing nearly all the work and not "for her": it's happening upstream and she only gets the output of the LLMs and has to verify them. And there aren't that many errors.

[torben-friis]

Pretty good as a dev with finance stakeholders. We have skills in place acting over our automated month closing and it was able to provide manual checks and flag issues, for example.

Nowhere near self sufficient tools though, just great to answer questions over the data that would usually take a few hours of custom scripting/excel. I wouldn't trust our stakeholders using AI directly either, being frank.

[timbaboon]

Seen it used in some of the fraud models (I work in insurance). So that's both from the perspective of people trying to claim fraudulently and from suppliers over charging. I can't say how much of a lift we actually get vs existing ML models

[bvan]

Yes, in very specific cases where I fully understand the methodology(ies) that is (are) applicable, and am able to verify correct implementation. Also, as an enhanced ‘Google search’ to supplement what I have found. I am the skeptical type… yet, so far have been impressed. But, I wouldn’t trust using AI to blindly give me solutions to a problem I couldn’t solve myself, albeit much more slowly.

[iewjj]

Nope If anything firms are pulling back (I know someone closely who works at blackrock).

[semiquaver]

I don’t just know someone who works in finance, I am someone who works in finance and I say you’re wrong.

[kx_x]

In what context?

For research and theses evaluations, we're observing that firms - of names we all know - are bullish and even eager to try AI products.

Regarding automated asset management and the likes, indeed there's much more apprehension.

[biophysboy]

pulling back as in setting more realistic token budgets, or something more drastic? I'm curious

[iewjj]

Stopped using them altogether in the context of productivity - in essence they’re useless.

[roughly]

I can believe that. Gambler’s Ruin gets costly when you’ve actually got money on the line.

[apaprocki]

We’re integrating AI tooling into the Bloomberg Terminal for everyone to use.

https://www.bloomberg.com/professional/insights/press-announ...