I asked ChatGPT to write a Clarus blog. Here is what happened….

I am travelling in APAC this week so I could do with a helping hand on the blog-writing front.

SACCR is our most popular topic on the blog, so as the title says, I asked ChatGPT to help out. If you are not familiar with ChatGPT (where have you been?) you can check out this introduction.

The results are … possibly too good?

Be Specific

I was fortunate to get some advice. Similar to “knowing what to search for” via Google, it turns out that some specificity is required to be truly impressed by ChatGPT.

For example, I started with the following:

Whilst it recognised that this was a “blog” it clearly did not know who Clarus was (how very dare you, ChatGPT!), and the prose was a little generic.

However, when you turn up the precision, you get a pretty good imitation of Chris Barnes:

Hello, fellow finance enthusiasts! Today, we’re going to delve into the world of standardized approach for counterparty credit risk (SACCR). Now, if you’re not familiar with this term, don’t worry, because we’re going to break it down and simplify it for you.

SACCR is a method used by financial institutions to calculate the amount of capital they need to hold against potential losses resulting from counterparty credit risk. In simpler terms, it’s a way for banks to determine how much money they need to have in reserve in case one of their customers defaults on a loan or other financial obligation.

So, why is SACCR so important? Well, for starters, it’s a regulatory requirement under the Basel III framework. Banks are required to hold a minimum amount of capital based on their exposure to counterparty credit risk, and SACCR provides a standardized approach to calculating this exposure.

Now, let’s dive into the nitty-gritty details of how SACCR works. It starts by calculating the potential future exposure (PFE) of a transaction, which is the estimated maximum loss that could occur over a specified time period. This is done by considering factors such as the notional amount of the transaction, the remaining maturity, and the volatility of the underlying assets.

Next, SACCR calculates the credit valuation adjustment (CVA) risk capital charge, which takes into account the counterparty’s creditworthiness and the potential loss due to a change in the counterparty’s credit spread.

Finally, SACCR calculates the capital charge for potential future credit exposure (PFCE), which is the amount of capital that the bank needs to hold against the estimated potential future losses resulting from counterparty credit risk.

Now, as you can imagine, SACCR calculations can get quite complex and involve a lot of variables. That’s why there are specialized software and solutions available to help financial institutions with these calculations.

At ClarusFT, we provide one such solution – our SACCR Navigator. It’s a web-based application that allows users to calculate SACCR exposure quickly and easily, using real-time market data and customizable inputs.

In conclusion, SACCR is an important part of risk management for financial institutions, and understanding how it works is crucial for anyone in the finance industry. At ClarusFT, we’re dedicated to providing innovative solutions to help our clients navigate complex financial calculations, and our SACCR Navigator is just one example of that commitment. Thanks for reading, and stay tuned for more insights from ClarusFT!

https://chat.openai.com/chat

Initial comments are:

• It is still very high level. No new “content” for our readers here.
• I had to “regenerate response” as Version One did not resonate with me at all.
• It recognises that it is a “blog” but does not include any links or references. Take it from me, if a “bot” could automatically add links to our blog posts, it would cut down our production time by about 25%!
• It does a decent job of introducing a (somewhat repetitive) chatty style of prose.
• ChatGPT somehow thinks our product is called “SACCR Navigator”. Maybe we should rebrand. But it does a good job of describing our actual product. If ChatGPT can understand what it does, then we are clearly selling the right thing!

What About Maths?

I wondered if it could do more detail….

It has a good go, but really it just regurgitates the BIS documentation.

https://chat.openai.com/chat

Examples

Our most useful blogs are those that include examples. Let’s see chatGPT try it:

https://chat.openai.com/chat

That is the spookiest impression of an expert saying “I don’t know” that I think I have ever read…..!

I think it is clear where this is going. What we really need is ChatGPT to get access to our API. Then this user experience would be pretty difficult to beat:

One day…..

What do you think?

Please feel free to let us know what other Clarus-related topics you have tried over at ChatGPT. The results are pretty interesting!