Loraine Lawson
Hi everyone, I’m Deputy Editor Loraine Lawson and welcome to The Buzz from Bank Automation News, where we explore how automation and emerging technology is transforming the banking industry. This is our Weekly Wrap for what’s happening in the industry this week. And before beginning I’d like to give a big thanks to BAN sponsor and advertiser Volante — thank you so much for your support.I’m pleased to be joined by Associate Editors Aaron Marsh and Alijah Poindexter. It is Dec. 17, 2021, and here are the biggest news items from our editorial team this past week. Distributed ledger technology has been in banking news in a big way, with the latest being new news that IBM and HSBC completed wholesale CBDC transactions on distributed ledger. The Canadian prepaid market is expected to reach $6.7 billion in loads by the end of this year, and that’s a nearly 100% increase, according to a recent study. And ML, machine learning, and automation drive efficiencies in anti-financial crime efforts. We’ll look at that.

First on the distributed ledger technology, Aaron and Alijah, it was like Oprah gave out distributed ledger technology this week. IBM first came out with a report recently that they had done a successful test at the behest of a central bank, France’s central bank, and that included successfully conducting an end-to-end transaction lifecycle which covered central bank digital currencies, minting and allocation. They also successfully tested e-balance delivery versus payment settlements across primary issuance and secondary trading and coupon payments. And finally, foreign exchange pricing and payments versus payments settlements. They weren’t the only ones to do a foreign exchange settlement this week.

Again, HSBC along with Wells Fargo completed a payment versus payment settlement. That’s basically where one bank says, “Okay, we have all these euros, and we need to get dollars,” and another bank says, “We have all these dollars, we need to get euros,” and they do these big money transfers, to sort of settle the difference between them. And traditionally those happen in two systems, and they would have to get on the phone and work out any kind of issues that came up. In this case, thanks to distributed ledger technology, they can kind of agree to the rules by which things will be settled. And that’s done through a contract, a smart contract, or in the case of the Wells Fargo, HSBC, something very like one called a baton rule book. And then they settle it automatically without having to get on the phone and open all the spreadsheets. So that was another big announcement. And this, of course, came on the heels of State Street last week and their digital ledger announcement, where they had settled another foreign exchange deal related to foreign exchange, I think that had to do with micro payments. They tested live trades. Go ahead.

Aaron Marsh
I was gonna mention though, I’m more talking about CBDCs — central bank digital currencies. I have heard, and probably Alijah and you have heard also, that every government — like literally, every government around the globe, is looking at how to make this work. And you know, we’re talking about who’s it going to be, like the who and the how needs to be defined. How is this going to be handled? And how are you going to automate the whole process and make it happen in real time? So I think what you’re starting to see, is the answer some of that question. It doesn’t surprise me to see some of these key players involved.

Loraine Lawson
Well, there are central bank digital currencies already in existence. And there are lots of experiments with them. This is part of the experiment about how they would work in banking. So it’s not so much an experiment to see, can we create these can we work internally, but to see, can we use CBDCs and interchange them with each other across multiple distributed ledgers? That’s what the IBM play was. They involve more than one distributed ledger and exchanging central bank digital currency across those ledgers. So what we’re getting at is sort of like, okay, we know we can do digital currency. Can we use it the same way we use currency currently, can we do some of the same trades?So it’s been an interesting week. I think we’ll continue to see it automated in a very specific way it automates out an entire function really, of trying to settle these discrepancies in currency. So you know, people no longer have to get on the phone and dicker over who’s paying who, how much. It’s just done through the contract. It’s to me fascinating. But this week, we also saw in Canada news prepaid cards use. Alijah, can you tell us what that means to Canada? What’s the significance of that news?

Alijah Poindexter
So the first thing I’ll preface this with is by stating that when people see prepaid, you know, it’s kind of inverse. So Canada, they have this big prepaid boom. But as I mentioned in the article, as we’ll talk about, right now, their innovations rail for payments lag behind the rest of North America, specifically, specifically the United States. But how it works on the inverse is that, well, America hasn’t really had this big prepaid boom, yet. They’ve had the innovation rail come from the innovators themselves, it hasn’t been delivered on any type of rail or any type of pipeline. So it kind of works in the inverse, but we do have a higher level of innovation. What does matter? You know, the reason why this matters so much for Canada is because again, as I just said, this is the main innovations, rail COVID-19, the pandemic really accelerated the growth of prepaid.

And when I say prepaid, I don’t just mean gift cards. That’s something that when I spoke to the people at CPPO, and I Tina Baraka, they were quick, too quick to quick to delineate for me, prepaid is everything from payroll, insurance payouts, to business to business business to government, prepaid access to wages, prepaid access to health care, prepaid access to and to, you know, corporate expense accounts, and B to G, as well as government to government to citizen. It’s huge. And the pandemic really accelerated this, it saw a one, the prepaid market saw a 100% increase nearly very, very close to 100%, between 2019 and the end of 2021. And this is, I mean, this is such a stark and exciting, honestly, opportunity for Canadian consumers because everything we have in America, you know, by now pay later gig economy solutions for getting food delivered or getting a ride somewhere, you know, instant access to your wages getting paid a day to a week before, if not getting your wages paid on a daily basis. They didn’t have that in Canada yet.

But the growth of this prepaid market, the boom, so to speak, has really accelerated the innovations there. And it’s kind of putting them on a level playing field with both their actual neighbors and their global peers in terms of GDP and economy and, you know, economic makeup and stuff like that. So this is super exciting, because I feel like and I think the research reflects this is that soon you’ll see Canadian, a lot of Canadian FinTech start to arise a lot of Canadian, you know, providers start to arise, it’s not going to be so centric on the UK and Europe and America. And prepaid is really the market for this. And I think it also provides opportunities for Americans to learn as well, for the United States to learn because we are missing a lot of these pre paid opportunities. A lot of people are still receiving their checks every two weeks, you know, bi weekly, or your you know, how weekly however they receive it.

But COVID-19 in the pandemic has accelerated and maybe you know, part time or retail or food service, the growth of getting paid daily. And part of that is prepaid. But we still haven’t seen that in these other industries. But maybe the United States can learn from Canada and vice versa. So this is just an incredible, incredible change and incredible growth in the market in Canada. And I think it bodes well for their FinTech and financial services, innovation moving forward. And I think everybody can learn a lesson from it, as well.

Loraine Lawson
Aaron, you’ve done some coverage with the idea of prepaying or paying ahead of two weeks schedule income, right, like, or salary rather. I think that’s a fascinating trend to look at how we can pay people faster. I know, I’m gonna sound really old here. But when I started in freelancing, you know, it could be it could be one month, or it could be three months before I got paid. So I know that’s huge for the great gig economy to look at being able to get paid sooner, and maybe on their basis.

Aaron Marsh
That was definitely something that came up you know, we did a recent look at these micro businesses, freelancers, gig workers. The example that comes up all the time is Uber drivers. And really what you’re talking about in so many of these cases is just access to money access to getting you know, paid and that may be like if I’m an Uber driver that I can very seamlessly you know, in one app you know once I’m once I have all my information in there that I need, I can you know, I can take customers I can drive them and navigate to where I need to go and at the end of that, I can boom accept payment and be paid instantly and be able to use those funds instantly not have to wait for that to clear or anything like that. So you’re looking at just a major innovation in people like sort of being able to be paid in the moment. And sometimes that’s really critical access for somebody.

Loraine Lawson
So Aaron, you also did some reporting this week on an interesting topic, which is how machine learning and automation are helping to fight financial crimes like fraud and money laundering. And you found there’s still room for improvement and have some recommendations. Can you talk a little bit about those?

Aaron Marsh
Well, absolutely. And let me just sort of preface the discussion. You know, this is this is an area that I have loved to cover, because it was — and this actually shows up in this article — it was in September, at the Association of Certified Anti Money Laundering Specialists conference in Las Vegas. And I’m going to call him out here, because I was listening, and I hope he’s listening, is Andrew Davies of Fiserv. He was basically talking about anti money laundering efforts. And all you need to know is that there are less than 1% effective, the net that’s out there at stopping these crimes from happening is actually probably much less than 1%. But he called it absolutely appalling that that is the success rate. Okay, so you have that. So anti money laundering efforts aren’t particularly effective at all. And online, transacting. And digital banking has been increasing, you know, by a lot. And along with that has come online fraud.

So we’ve seen, you know, hearing from these companies involved in this, that they’ve seen an uptick in online fraud, and that this is going on. So again, you’ve got this area, where the good guys are not particularly effective. And there’s a lot that stands to be improved. And so I you know, so I spoke with linear financial technologies and Kaufman Rossin about this and Kaufman’s a consultancy, they actually deal with banks, financial institutions, they get in there and improve their anti fraud, anti money laundering systems, so improving efficiencies, and Linear has actually just launched a, like, an all inclusive anti fraud platform platform called Linear Defense. So, you know, we’re looking at how to improve this. And the problem, right, you know, apparently with this is that many of these systems are, they’re called, like, rules based systems. And the issue there is that you’re, you’re constantly reactive, and following. So you’ve got like instances of money laundering, you’ve got instances of fraud, and it’s like, you have to program the system to look for those kinds of instances, you’re looking at what has already happened. And, you know, so it’s, the criminals are changing what they’re doing. So they’re like constantly several steps ahead.

And the systems, they tend to also need like a critical mass of fraud, they actually spot it and start reporting it. And they tend to also produce this like wide net of red flags and alerts that then banks and financial institutions have to weed through. And it’s an extremely tedious process to actually then you’ve got to do things, like, look at the, you know, the parties involved in a transaction that’s, you know, potentially red flag, right. So you’ve got the, you know, the payer and the recipient. So you might have to do like additional research, looking for information on the on these parties involved. And you got to do that for each and every one of these situations, they got red flag, it’s extremely onerous is extremely tedious. And it’s absorbing of all those resources. So, you know, it’s Kaufmann, Ross, and, you know, I heard it’s like, well, we can automate some of that, we can automate some of these tasks that are like redundant and handle that. So that your bank personnel, your anti fraud personnel, anti money laundering personnel, don’t have to get bogged down with it.

But most importantly, to where we’re talking about machine learning. We’re talking about automation that learns. Now, instead of looking broadly, at like a category of businesses, say, like businesses up to, you know, a certain size of revenue or something like that, like a broad categorization of businesses, what they’re doing is really slicing out much more narrowly. For example, something like pizza parlors with say, five to 10 locations. Okay, so now you can take like a much more minute, narrow view, and they’re in the systems are looking for behaviors, abnormal behaviors, that are just sort of outside the norm, anything that’s an aberrant behavior. And now we’re going to, we’re going to fine tune those red flags quite a bit more. So it’s like, here you’ve got a situation where there’s an awful lot that stands to be gained. There’s a big room for improvement, and machine learning and automation seems to be key here.

Loraine Lawson
Yeah, one of the things that machine learning technology does really well is pattern recognition. And that’s been known for some time. I remember it’s probably been, it’s probably been 10 years ago, that I was able to have a demo of a system that was so to law enforcement, but it can recognize from cellphone patterns, who you called, who called you whether or not you were involved in a directory with high accuracy. So I think it’s more it’s not so much that the technology isn’t there, it’s more that the maybe the cost is prohibitive, maybe the data sets aren’t there. I don’t really know what’s holding it back, I will say that I have talked to bankers who have done machine learning and implemented systems like you’re talking about, they do reduce false positives, which is a huge savings over manual efforts that reduces manual efforts to dig in, like you said, but he also, they are also cautious about still using the rules based and a lot of people think that the best solution might be to have both the rules based system still there, but the machine learning to sort of rule out, hey, you know, it’s over. It’s giving you false positive, and these are the false positives. So it’s definitely an interesting technology trend to watch and see as it gets adopted by banks. Okay, guys, I think that’s enough for today, we’ve covered it pretty well. Let’s talk about what’s ahead for next week. Aaron, you want to go first?

Aaron Marsh
Toward the end of the year, it’s kind of been, what can we fit in? There’s been a lot that sort of come down the pipelines. I just had a discussion, I’m not going to tell you with who were looking at bank behaviors, like a massive study that instead of looking at the client side of things, the customers and what and what businesses are doing with banking, this is a huge look at how banks are have been approaching digital transformation, and specifically, what they’re doing well, and what they’re not doing well. And, you know, where they see their biggest challenges that they’ve had so far. And it’s a pretty interesting take. So I think that’s something I’m looking forward to.

Loraine Lawson
That’s interesting. Alijah, what are you working on for next week, you’ve got several things in the hopper.

Alijah Poindexter
So next week, the biggest thing, in my opinion that I’m working on, so Temenos, the banking platform or banking software provider, they extended their partnership with Microsoft as your they already had a partnership or collaboration. But they’re extending it. A good example of that would be in their banking, cloud, the Temenos, banking cloud, that kind of provides, you know, collaborating financial institutions with what they call an innovation sandbox, allowing them to sort of customize both their back end and front end experience helping improve the helping improve customer experience as well. Well, Microsoft is your they’ve extended their collaboration.

So it’s just going to be that much deeper in terms of being cloud native and being customizable for their clients. But there are some other insights that I was able to glean from this, I spoke to Andrew Reeves, who was the head of cloud over there. And we spoke about how automation has impacted their ESG strategy. And they’re looking to cut their emissions by over 46% by 2030. And of course, they’ll be using in house and external automation to accomplish that. And we also spoke about open banking, which is kind of seen as a buzzword in some circles. But Reeves and Mr. Mr. Reeves was quick to point out that in Europe, it is most definitely not a buzzword. It is something that pretty much every sort of hip, bank and cloud provider and what have you ascribes to because it helps break down barriers. And it helps provide, you know, for customers, clients, vendors and financial institutions alike, that bigger pool of data to access to enhance the experience for everybody. So that was super exciting. And I think it’s awesome that we can glean so much insight from a simple, you know, collaborative announcement like that.

Loraine Lawson
Yeah, and yesterday tested pay. This is what I’m digging into announced that it has provided a blockchain based digital payment for banks, B2B clients, and it’s a network that went live yesterday with 200 With more than 100 Beat sorry. So I’ll be looking more at that and what that how that works and who’s involved in that. Thank you so much for joining us for the weekly wrap on the buzz don’t forget to attend our fake automation summit March 1 through second in Charlotte, North Carolina. You can learn more about that at BankAutomationSummit.com. For more podcast content, check out bank automation news.com and search the buzz for big automation news on iTunes and Spotify. Thank you.

Loraine Lawson
Hi everyone, I’m Deputy Editor Loraine Lawson and welcome to The Buzz from Bank Automation News, where we explore how automation and emerging technology is transforming the banking industry. This is our Weekly Wrap for what’s happening in the industry this week. And before beginning I’d like to give a big thanks to BAN sponsor and advertiser Volante — thank you so much for your support.I’m pleased to be joined by Associate Editors Aaron Marsh and Alijah Poindexter. It is Dec. 17, 2021, and here are the biggest news items from our editorial team this past week. Distributed ledger technology has been in banking news in a big way, with the latest being new news that IBM and HSBC completed wholesale CBDC transactions on distributed ledger. The Canadian prepaid market is expected to reach $6.7 billion in loads by the end of this year, and that’s a nearly 100% increase, according to a recent study. And ML, machine learning, and automation drive efficiencies in anti-financial crime efforts. We’ll look at that.

First on the distributed ledger technology, Aaron and Alijah, it was like Oprah gave out distributed ledger technology this week. IBM first came out with a report recently that they had done a successful test at the behest of a central bank, France’s central bank, and that included successfully conducting an end-to-end transaction lifecycle which covered central bank digital currencies, minting and allocation. They also successfully tested e-balance delivery versus payment settlements across primary issuance and secondary trading and coupon payments. And finally, foreign exchange pricing and payments versus payments settlements. They weren’t the only ones to do a foreign exchange settlement this week.

Again, HSBC along with Wells Fargo completed a payment versus payment settlement. That’s basically where one bank says, “Okay, we have all these euros, and we need to get dollars,” and another bank says, “We have all these dollars, we need to get euros,” and they do these big money transfers, to sort of settle the difference between them. And traditionally those happen in two systems, and they would have to get on the phone and work out any kind of issues that came up. In this case, thanks to distributed ledger technology, they can kind of agree to the rules by which things will be settled. And that’s done through a contract, a smart contract, or in the case of the Wells Fargo, HSBC, something very like one called a baton rule book. And then they settle it automatically without having to get on the phone and open all the spreadsheets. So that was another big announcement. And this, of course, came on the heels of State Street last week and their digital ledger announcement, where they had settled another foreign exchange deal related to foreign exchange, I think that had to do with micro payments. They tested live trades. Go ahead.

Aaron Marsh
I was gonna mention though, I’m more talking about CBDCs — central bank digital currencies. I have heard, and probably Alijah and you have heard also, that every government — like literally, every government around the globe, is looking at how to make this work. And you know, we’re talking about who’s it going to be, like the who and the how needs to be defined. How is this going to be handled? And how are you going to automate the whole process and make it happen in real time? So I think what you’re starting to see, is the answer some of that question. It doesn’t surprise me to see some of these key players involved.

Loraine Lawson
Well, there are central bank digital currencies already in existence. And there are lots of experiments with them. This is part of the experiment about how they would work in banking. So it’s not so much an experiment to see, can we create these can we work internally, but to see, can we use CBDCs and interchange them with each other across multiple distributed ledgers? That’s what the IBM play was. They involve more than one distributed ledger and exchanging central bank digital currency across those ledgers. So what we’re getting at is sort of like, okay, we know we can do digital currency. Can we use it the same way we use currency currently, can we do some of the same trades?So it’s been an interesting week. I think we’ll continue to see it automated in a very specific way it automates out an entire function really, of trying to settle these discrepancies in currency. So you know, people no longer have to get on the phone and dicker over who’s paying who, how much. It’s just done through the contract. It’s to me fascinating. But this week, we also saw in Canada news prepaid cards use. Alijah, can you tell us what that means to Canada? What’s the significance of that news?

Alijah Poindexter
So the first thing I’ll preface this with is by stating that when people see prepaid, you know, it’s kind of inverse. So Canada, they have this big prepaid boom. But as I mentioned in the article, as we’ll talk about, right now, their innovations rail for payments lag behind the rest of North America, specifically, specifically the United States. But how it works on the inverse is that, well, America hasn’t really had this big prepaid boom, yet. They’ve had the innovation rail come from the innovators themselves, it hasn’t been delivered on any type of rail or any type of pipeline. So it kind of works in the inverse, but we do have a higher level of innovation. What does matter? You know, the reason why this matters so much for Canada is because again, as I just said, this is the main innovations, rail COVID-19, the pandemic really accelerated the growth of prepaid.

And when I say prepaid, I don’t just mean gift cards. That’s something that when I spoke to the people at CPPO, and I Tina Baraka, they were quick, too quick to quick to delineate for me, prepaid is everything from payroll, insurance payouts, to business to business business to government, prepaid access to wages, prepaid access to health care, prepaid access to and to, you know, corporate expense accounts, and B to G, as well as government to government to citizen. It’s huge. And the pandemic really accelerated this, it saw a one, the prepaid market saw a 100% increase nearly very, very close to 100%, between 2019 and the end of 2021. And this is, I mean, this is such a stark and exciting, honestly, opportunity for Canadian consumers because everything we have in America, you know, by now pay later gig economy solutions for getting food delivered or getting a ride somewhere, you know, instant access to your wages getting paid a day to a week before, if not getting your wages paid on a daily basis. They didn’t have that in Canada yet.

But the growth of this prepaid market, the boom, so to speak, has really accelerated the innovations there. And it’s kind of putting them on a level playing field with both their actual neighbors and their global peers in terms of GDP and economy and, you know, economic makeup and stuff like that. So this is super exciting, because I feel like and I think the research reflects this is that soon you’ll see Canadian, a lot of Canadian FinTech start to arise a lot of Canadian, you know, providers start to arise, it’s not going to be so centric on the UK and Europe and America. And prepaid is really the market for this. And I think it also provides opportunities for Americans to learn as well, for the United States to learn because we are missing a lot of these pre paid opportunities. A lot of people are still receiving their checks every two weeks, you know, bi weekly, or your you know, how weekly however they receive it.

But COVID-19 in the pandemic has accelerated and maybe you know, part time or retail or food service, the growth of getting paid daily. And part of that is prepaid. But we still haven’t seen that in these other industries. But maybe the United States can learn from Canada and vice versa. So this is just an incredible, incredible change and incredible growth in the market in Canada. And I think it bodes well for their FinTech and financial services, innovation moving forward. And I think everybody can learn a lesson from it, as well.

Loraine Lawson
Aaron, you’ve done some coverage with the idea of prepaying or paying ahead of two weeks schedule income, right, like, or salary rather. I think that’s a fascinating trend to look at how we can pay people faster. I know, I’m gonna sound really old here. But when I started in freelancing, you know, it could be it could be one month, or it could be three months before I got paid. So I know that’s huge for the great gig economy to look at being able to get paid sooner, and maybe on their basis.

Aaron Marsh
That was definitely something that came up you know, we did a recent look at these micro businesses, freelancers, gig workers. The example that comes up all the time is Uber drivers. And really what you’re talking about in so many of these cases is just access to money access to getting you know, paid and that may be like if I’m an Uber driver that I can very seamlessly you know, in one app you know once I’m once I have all my information in there that I need, I can you know, I can take customers I can drive them and navigate to where I need to go and at the end of that, I can boom accept payment and be paid instantly and be able to use those funds instantly not have to wait for that to clear or anything like that. So you’re looking at just a major innovation in people like sort of being able to be paid in the moment. And sometimes that’s really critical access for somebody.

Loraine Lawson
So Aaron, you also did some reporting this week on an interesting topic, which is how machine learning and automation are helping to fight financial crimes like fraud and money laundering. And you found there’s still room for improvement and have some recommendations. Can you talk a little bit about those?

Aaron Marsh
Well, absolutely. And let me just sort of preface the discussion. You know, this is this is an area that I have loved to cover, because it was — and this actually shows up in this article — it was in September, at the Association of Certified Anti Money Laundering Specialists conference in Las Vegas. And I’m going to call him out here, because I was listening, and I hope he’s listening, is Andrew Davies of Fiserv. He was basically talking about anti money laundering efforts. And all you need to know is that there are less than 1% effective, the net that’s out there at stopping these crimes from happening is actually probably much less than 1%. But he called it absolutely appalling that that is the success rate. Okay, so you have that. So anti money laundering efforts aren’t particularly effective at all. And online, transacting. And digital banking has been increasing, you know, by a lot. And along with that has come online fraud.

So we’ve seen, you know, hearing from these companies involved in this, that they’ve seen an uptick in online fraud, and that this is going on. So again, you’ve got this area, where the good guys are not particularly effective. And there’s a lot that stands to be improved. And so I you know, so I spoke with linear financial technologies and Kaufman Rossin about this and Kaufman’s a consultancy, they actually deal with banks, financial institutions, they get in there and improve their anti fraud, anti money laundering systems, so improving efficiencies, and Linear has actually just launched a, like, an all inclusive anti fraud platform platform called Linear Defense. So, you know, we’re looking at how to improve this. And the problem, right, you know, apparently with this is that many of these systems are, they’re called, like, rules based systems. And the issue there is that you’re, you’re constantly reactive, and following. So you’ve got like instances of money laundering, you’ve got instances of fraud, and it’s like, you have to program the system to look for those kinds of instances, you’re looking at what has already happened. And, you know, so it’s, the criminals are changing what they’re doing. So they’re like constantly several steps ahead.

And the systems, they tend to also need like a critical mass of fraud, they actually spot it and start reporting it. And they tend to also produce this like wide net of red flags and alerts that then banks and financial institutions have to weed through. And it’s an extremely tedious process to actually then you’ve got to do things, like, look at the, you know, the parties involved in a transaction that’s, you know, potentially red flag, right. So you’ve got the, you know, the payer and the recipient. So you might have to do like additional research, looking for information on the on these parties involved. And you got to do that for each and every one of these situations, they got red flag, it’s extremely onerous is extremely tedious. And it’s absorbing of all those resources. So, you know, it’s Kaufmann, Ross, and, you know, I heard it’s like, well, we can automate some of that, we can automate some of these tasks that are like redundant and handle that. So that your bank personnel, your anti fraud personnel, anti money laundering personnel, don’t have to get bogged down with it.

But most importantly, to where we’re talking about machine learning. We’re talking about automation that learns. Now, instead of looking broadly, at like a category of businesses, say, like businesses up to, you know, a certain size of revenue or something like that, like a broad categorization of businesses, what they’re doing is really slicing out much more narrowly. For example, something like pizza parlors with say, five to 10 locations. Okay, so now you can take like a much more minute, narrow view, and they’re in the systems are looking for behaviors, abnormal behaviors, that are just sort of outside the norm, anything that’s an aberrant behavior. And now we’re going to, we’re going to fine tune those red flags quite a bit more. So it’s like, here you’ve got a situation where there’s an awful lot that stands to be gained. There’s a big room for improvement, and machine learning and automation seems to be key here.

Loraine Lawson
Yeah, one of the things that machine learning technology does really well is pattern recognition. And that’s been known for some time. I remember it’s probably been, it’s probably been 10 years ago, that I was able to have a demo of a system that was so to law enforcement, but it can recognize from cellphone patterns, who you called, who called you whether or not you were involved in a directory with high accuracy. So I think it’s more it’s not so much that the technology isn’t there, it’s more that the maybe the cost is prohibitive, maybe the data sets aren’t there. I don’t really know what’s holding it back, I will say that I have talked to bankers who have done machine learning and implemented systems like you’re talking about, they do reduce false positives, which is a huge savings over manual efforts that reduces manual efforts to dig in, like you said, but he also, they are also cautious about still using the rules based and a lot of people think that the best solution might be to have both the rules based system still there, but the machine learning to sort of rule out, hey, you know, it’s over. It’s giving you false positive, and these are the false positives. So it’s definitely an interesting technology trend to watch and see as it gets adopted by banks. Okay, guys, I think that’s enough for today, we’ve covered it pretty well. Let’s talk about what’s ahead for next week. Aaron, you want to go first?

Aaron Marsh
Toward the end of the year, it’s kind of been, what can we fit in? There’s been a lot that sort of come down the pipelines. I just had a discussion, I’m not going to tell you with who were looking at bank behaviors, like a massive study that instead of looking at the client side of things, the customers and what and what businesses are doing with banking, this is a huge look at how banks are have been approaching digital transformation, and specifically, what they’re doing well, and what they’re not doing well. And, you know, where they see their biggest challenges that they’ve had so far. And it’s a pretty interesting take. So I think that’s something I’m looking forward to.

Loraine Lawson
That’s interesting. Alijah, what are you working on for next week, you’ve got several things in the hopper.

Alijah Poindexter
So next week, the biggest thing, in my opinion that I’m working on, so Temenos, the banking platform or banking software provider, they extended their partnership with Microsoft as your they already had a partnership or collaboration. But they’re extending it. A good example of that would be in their banking, cloud, the Temenos, banking cloud, that kind of provides, you know, collaborating financial institutions with what they call an innovation sandbox, allowing them to sort of customize both their back end and front end experience helping improve the helping improve customer experience as well. Well, Microsoft is your they’ve extended their collaboration.

So it’s just going to be that much deeper in terms of being cloud native and being customizable for their clients. But there are some other insights that I was able to glean from this, I spoke to Andrew Reeves, who was the head of cloud over there. And we spoke about how automation has impacted their ESG strategy. And they’re looking to cut their emissions by over 46% by 2030. And of course, they’ll be using in house and external automation to accomplish that. And we also spoke about open banking, which is kind of seen as a buzzword in some circles. But Reeves and Mr. Mr. Reeves was quick to point out that in Europe, it is most definitely not a buzzword. It is something that pretty much every sort of hip, bank and cloud provider and what have you ascribes to because it helps break down barriers. And it helps provide, you know, for customers, clients, vendors and financial institutions alike, that bigger pool of data to access to enhance the experience for everybody. So that was super exciting. And I think it’s awesome that we can glean so much insight from a simple, you know, collaborative announcement like that.

Loraine Lawson
Yeah, and yesterday tested pay. This is what I’m digging into announced that it has provided a blockchain based digital payment for banks, B2B clients, and it’s a network that went live yesterday with 200 With more than 100 Beat sorry. So I’ll be looking more at that and what that how that works and who’s involved in that. Thank you so much for joining us for the weekly wrap on the buzz don’t forget to attend our fake automation summit March 1 through second in Charlotte, North Carolina. You can learn more about that at BankAutomationSummit.com. For more podcast content, check out bank automation news.com and search the buzz for big automation news on iTunes and Spotify. Thank you.