So you will say that there's lots of ESG scores out there that can be a blackbox, the company will be given a score, but you don't necessarily know that the Inklings behind it.

What we're bringing with our green score is effectively that transparency, bringing in SME climate experts for a single institution and try to build that score around what their views are and how they view it and align it to their pathway to net zero or ESG, or climate risk within within their institution.

And then the other piece of the training that I do is I work with senior analysts as they begin to step into their first leadership roles. Because the other thing that is hugely bought by I found very relevant to my world was that when you start leading, it's as if someone goes here, the keys to the car, if you go, you mean you want driving lessons to beat after school drive.

And a lot of us analysts types are super introverted and really fact oriented. And we like our processes. And we don't necessarily do the soft skills particularly well. Yet we all respond really well to those being done well, but they don't necessarily come naturally to us. And I include myself in that. But it's something that we need to learn and be aware of how do we communicate with people up the chain? How do we take analytics and when someone says, but I don't understand. As an analyst, our tendency is to double down on the detail. And when you know what you're looking for, you can literally see people lose the will to live because they don't understand and that isn't helping, and they're not number oriented. So just make it stop.

"I don't understand why I have to take credit out to get credit. Why don't you just look at my bank statement, you can see how I'm behaving?"

Well, that's great. That's exactly what we do. At Direct ID we focus on categorising transactions that have particular interest risk decision makers.

So what we were able to do is to bridge the gap from unsupervised learning, where we don't have any labels, to supervised learning, where we do have a label.

Most decisioning systems rely on an opaque patchwork of siloed teams and data streams with insufficient oversight and control.

Many decisions, therefore, back to the tech line that you just mentioned, rely on guesswork and instinct. And this leads to bad decisions, and costly mistakes and disappointed customers.

This is why we founded Taktile in 2020 to change that.

Taktile has offices in New York City, London, and Berlin and serves as the backbone for risk, for pricing, and fraud teams across financial services. It enables decision authors to enrich internal signals with data from our rapidly growing data marketplace and flexibly express their desired decision logic - and all of that without actually requiring engineering support.

A broader philosophy could be formulated as working together in order to achieve better decisions. And as Jonathan mentioned earlier, these decisions should lead to fairer and more inclusive financial services and the world in general.

I think the topics of the past conferences and the forthcoming talks really reflect this focus on the final objective.

Yeah, of course they are are many purely technical talks about the new machine learning methods and new sources of data. And of course, you can't build credit scoring models without technology and without data. But there will be also papers focusing on fairness, my direction of research, financial vulnerability, affordability, over-indebtedness... climate risk is becoming a huge topic recently.

If you have to remember what we talked machine learning AI today is not something that's come around today, right? What has changed today is our ability to store enormous amount of data economically. Number two is the processing speeds we have today. You know, you want a search bar before you type, your third word is already telling you what it should be. So think about it. And there are millions of people doing it at the same time, any second. And the third thing is the speed of transmission of information.

I think those three in combination literally are the most fertile ground to bring AI to life.

And that's what we've essentially done. But be mindful that when you're doing things at that speed, there are things that could happen which go out of your control.

We use the same standard of care across the credit spectrum, and we actively seek new ways to innovate the scoring process. It's the architecture of our model that allows us to score approximately 37 million more individuals than conventional models. And interestingly, to note about that 37 million, approximately 10.7 million are members of the Black and Latino communities who have historically often been underserved. And approximately 3 million of those have scores that are above 620, which is generally considered those that will be eligible for traditional lending products.

So inclusion and broadening access to credit and being predictive have been guiding principles for VantageScore since its inception.

Convenience being such a huge motivator means that we don't need in my view to educate people on what open banking is, we just need to provide the reasons the benefits, especially around convenience, that get people to connect their bank account. And as you said, it is safer sharing that data through a secure channel as a regulated business like like us than, you know, photocopying or printing out your bank statements and then sending them into the post to some unknown place.

And these are all topics that have been talked about for a long time. But it is great to see the use cases start to develop the market start to mature, our understanding of these topics really starts to develop the fact that we don't need to educate consumers on what open banking is we just need to provide them a reason to call to action that makes sense. And if we do that, they get where they need. The business gets what they need. The regulators are happy because there's more richer data to personalise and, and really provide that responsible approach to to those lending situations and, and we just get on with their life. It's exciting.

I think you're absolutely right that credit scores in the US are better understood. We're told that Americans ask lenders 'my score is 750, what can you offer me?' and they discussed it openly with friends over dinner - it hasn't quite penetrated the consumer psyche in the same way here, but what's been really positive to see recently, though, is there's definitely a growing awareness of the importance of regularly monitoring your credit information.

And that's been particularly evident through the pandemic TransUnion has been conducting a consumer pulse study to track the impacts of the pandemic on consumer finances, and we found at the end of 2021 that almost half of UK consumers are now monitoring their credit score at least monthly. And that's up from a third at the start of May 2020. Downside is our data has also shown that a quarter of people have never checked it, which is worrying given the important role that this information plays in helping people get access to finance and protecting their identity.

So we had to tweak it and move it to image-based selection. And one thing led to the other and ConfirmU evolved from something which is good for the English language but is not scalable for 207 dialects in India, to an actual gamification, which would be much more engaging for people at the bottom of the pyramid. So what better way, you know, of engaging people in that kind of a segment. And our initial pilot was with Experian the nd Grameen Foundation in India, which is really exciting, because in my vision, Grameen Foundation is financial inclusion.

Now, as you said, ConfirmU started out as prop tech before expanding into financial services. What does the product look like today?

What we take pride in is the fact that we collateralize and localise the game to any market that we go to - credit at the end of the day is a matter of cultures, and we need to embed that within our game. So we will do a pilot and we will build a bespoke model for those lenders based on, you know, our understanding from the lender of the practicalities and the characteristics of that audience. And then we would send the link.

So we've created a first-world infrastructure, but it's been an uphill battle to get lenders to embrace the use of bureau data and credit scores and bureau scores to make mass decisions. In Nigeria, it's a legal requirement that you perform two credit inquiries, but that's not to say that you must make good use of the data you're given, as long as you know, you've met your legal obligations. So there hasn't really been an appreciation of how that data can help you improve your decision making. So that's the journey that I've been trying to help my clients to realise - it's been as an educational upskilling, a sort of training project as much as much as a hands-on rebuild the bureau score project.

I think one of the cultural changes that's required is the willingness to invest money in order to save money, that thinking hasn't really been that prevalent in Nigeria, in the past at least. Curiously, that's the first time I've ever encountered a situation where lenders have questioned, well, why are we paying for a credit inquiry if we ended up rejecting that customer? Why would we want to pay for that? Which kind of misses the point of the protection that screening for risk gives you.

The other thing that we noticed was consumer behaviour changed, which was really interesting. Some of it was taking the subsidies and doing this, some it was taking the payment holiday and doing this, and some of it was just people doing it on their own: but we've seen the largest stockpile of cash going into bank accounts that we've ever seen, of just new deposits that came in over COVID. And so there's this big pot of cash that consumers are holding onto right now.

And I think the provision for credit losses that most of the banks had forecasts through COVID were relatively high and nothing came to fruition, right. They didn't see the link. And in fact, delinquency rates have been dropping, even when deferrals ran off as the freezes expired. We thought, well, you know, the people taking deferrals are probably the people that need it. Once they don't have that option anymore. We're gonna see delinquency rates amongst that population increase... and it didn't. So it did, it's increased slightly, but not to the levels that we had thought. And so I think lenders looked at that brand. And they just said, No, we're ready, we're ready to jump back in and you know, ourselves from a supply perspective, we tighten the reins, you know, it was prudent from a risk perspective what we did, but we're ready to start to get back out and you know, reengage with consumers and lend.

There's a whole bunch of people out there where the traditional model doesn't work, there simply isn't enough information on these people to make a reasonable credit call...

This is a space where lots of people are working, but very few people can claim results. Because this is also the sort of space where lots of AI propellerheads think they can crack the problem. To some extent, that's true. This is also the classic case where progress is both hindered and aided with experience. It's actually good that some youngster on a beanbag, with long hair, thinks about this stuff completely unhindered by any previous industry knowledge, because that's anyone with too much experience probably thinks too much inside the box. At the same time, with something like credit, you do need to have some other people in there who can say, 'well, yeah, that's cool but you need to take these following five things in'.

That doesn't mean that the thinking needs to be restrained, but someone needs to make it practical in the end. To simply let the same space cadets go mad on this is likely to land you in a heap of problems, if you don't actually understand the lending industry.

I think the unprecedented level of government support and the way that lenders and consumers alike have been able to help keep the ship afloat, mean that it definitely could have been a lot worse than what we've seen up to date. But to your point, there are still plenty of consumers, hurting out there, and hopefully are getting that assistance as they need it.

So we actually as home prices started coming back up, we saw that consumer started reprioritizing their mortgage ahead of credit card. And what we saw, you know, actually starting back in like the first quarter of 2017, we first see that mortgage overtakes auto as the primary payment. So the phenomenon of mortgage becoming the highest ranked actually started well before this pandemic. And then what we saw in the pandemic, was the separation between auto and mortgage delinquency got even bigger. It's likely due to a number of factors, as we talked about the accommodations, for sure, you know, suppressing that delinquency, but also, you had so many people now working from home that they had to protect their home, they might be willing to maybe let one of their autos go, because they weren't going anywhere, you know, and people weren't taking road trips, and they weren't worried about their car, they had to make sure that they had a place to work that coupled with the home price index in the US.

So that was my focus point is, if you've got nothing, that's where we start… for existing clients, you can just go with the Chief Operating Officer to a branch, have your scoring, talk to the loan officers about the clients, they know them, right, you'd be surprised by how many they have but they know them by name, and test the scoring.

The common feature here was that, like banks were slow to be on the take up of the scoring methodologies, FICO was slow to see the value of bureau information. And for that matter, the credit bureau saw FICO as a competitor, they didn't see FICO as somebody that they could collaborate with. And yet nowadays, a FICO score is synonymous with a bureau score.