Environment – a view from Deloitte

Problems and challenges with the with big data or having large volumes of data actually really interesting because, five years ago having too much data was an issue because we didn’t have the computing power to actually cope with that. But more and more now the, actually volume of data is critical because the better picture you have of a situation, the more history for example, the more understanding wider a wider data set about your particular problem. The the more accurate your decisions are going to be.

Giving an example if you know which clients you want to target, but you’re only looking at your internal data, you’re not considering all the external data about that client, the industry, they’re in, the market they’re in. That gives you a whole much better understanding about that particular customer or prospect. So having that big data is is is crucial, but it’s not just about volume. A lot of people make that mistake with big data. It’s not just about volume. It’s also about frequency. It’s also about, you know, how many different V’s Do you get velocity, veracity of data, it’s, it’s important to have the full breadth of understanding of that big data.

Data ethics is a really hot topic at the moment as it’s vital that organisations think long and hard about how to be ethical, not only with data, but then also the decisions that hang off the back of it. And one of the most effective ways is to have a clear view of what controls you can put in place around the data. So not only the collection of it, but the storage of it, how long you can keep it, the quality of that data.

You know, the the GDPR is actually it’s a very important and good compliance regime and the six principles of GDPR are really important for us to consider when you look at ethics, and being able to have a risk and control framework around anything to do with data, it’s important you know.

To bring that to life, you know, if you if you’re making a decision on whether to lend somebody some money or to give them a mortgage, you want to make sure that you’ve got highly accurate data, that you can trace the data at every point in the journey, and that any decision is not only traceable, but it’s it’s it’s easy to follow and to see there’s no sort of black box, or hidden aspect to that data. And, and also that anything that you you, you’re capturing isn’t going to hold some sort of bias, because that bias is what ultimately leads to poor decisions, you know, affecting certain parts of the population.

And that’s, that’s really, that having that data ethics and now it’s becoming AI ethics as well, very related point. You know, it’s critical. So we’re working with a client, a European Bank, and they’re implementing AI and of course data is a key part of that, that journey. But the risk and control framework that wraps around that is is absolutely critical.