We already talked about how companies are exposed to different types of vulnerabilities, and they can change according to the department you are considering.
Let’s talk about the finance department of a company, and that’s only the tip of the iceberg, being one of the easiest to fix mostly because has structured databases and often spreadsheets, so structured data in a sense.
Being organized and structured leads to the ability to simulate scenarios quite nicely because it’s fundamental to have a clear idea of what happens today and in the next 30 days.
These scenarios also help you to calculate the risk, measuring and forecasting is another way where AI and machine learning really shine.
If you’re able to quantify what risk is because you do have all this data and it’s all very structured, it allows your business to get to a place where having seen risky things come to fruition in the past, you can model them into the future.
Additionally, to empower all of that beyond spreadsheets and databases, all of the software that is typically used in operations, you’re going to have just a lot of contracts, a lot of documents, a lot of agreements and invoices. There is a huge portion of business operations, especially in finance, that requires you to read those documents.
Most organizations just tend not to actually enter all of the information back into their systems from the agreements and invoices so you get into weird situations at times where you have a contract that isn’t performing and the company isn’t doing the thing it’s supposed to, or not performing to that company and the interaction is still going.
Let’s cut through the jargon, myths and nebulous world of data, machine learning and AI. Each week we’ll be unpacking topics related to the world of data and AI with the awarding winning founders of 1000ML. Whether you’re in the data world already or looking to learn more about it, this podcast is for you.