The new business, which will be known as Gresham, will be based in London with former Gresham Technologies chief executive Ian Manocha continuing the role at the company and Mark Hepsworth, who headed Alveo, taking the chair’s position.

The combined companies marry Gresham Technologies’’ transaction control and reconciliations, data aggregation, connectivity solutions and regulatory reporting capabilities with Alveo’s enterprise data management for market, reference and ESG data.

The range of data automation and process solutions it can offer will reduce the total cost of ownership of clients’ data, Gresham said.

“The combination of the two firms accelerates our journey to bring digital integrity, agility, operational efficiency and data confidence to financial markets globally,” said Manocha. “It creates a comprehensive set of solutions for data automation, operational efficiency, data management, analytics and risk mitigation for financial and corporate clients globally.”

The terms of the deal were not disclosed but Alveo’s majority owner, technology-focused private equity firm STG, backed the merger.

London-based Alveo was founded in 1991 as Asset Control, one of the first third-party enterprise data management service providers. It changed its name in 2020 after becoming a cloud-native, managed-service provider.

Gresham Technologies began life as Gresham Computing offering real-time transaction control and enterprise data integrity solutions.

Hepsworth said the newly enlarged company will be able to meet the increasing data demands of clients.

“We can now offer clients greater scale and a wider range of solutions that will simplify their operations and enable them to manage data more effectively,” he said.

The post Alveo and Gresham Merge to Offer Data Services at ‘Significant’ Scale appeared first on A-Team.

Last month the California-based company deepened its association with Databricks, providing the full range of its AI-powered Intelligent Data Management Cloud capabilities within Databricks’ Data Intelligence Platform. The expanded partnership will enable joint customers to deploy enterprise-grade GenAI applications at scale, based on a foundation of high-quality, trusted data and metadata. That followed the unveiling of a similar association with Snowflake. It was also selected by Microsoft as the Independent Software Design (ISV) design partner for the software behemoth’s new data fabric product.

The frequency of the rollouts in recent months has been dictated by the rapidity with which Informatica’s financial institution clients are seizing on the potential of AI. Many are struggling to bring the technology into their legacy systems, while others have a vision of what they want to do with it but not the capability to implement it.

With the market also heavily weighted towards capitalising on the growing generative AI space, Informatica group vice president and head of EMEA North sales Greg Hanson said new developments and enhancements are on the cards for the near future.

“The critical foundational layer for companies is to get their data management right and if you look at the current state of most large organisations, their integration and their data management looks a bit like spaghetti,” Hanson tells Data Management Insight.

“They realise, though, that they have to pay attention to this strategic data management capability because it’s almost as fundamental as the machinery that manufacturers use to make cars.”

Rapid Change

Hanson says that the pace of innovation at Informatica is the fastest he’s seen in his two decades at the company because its clients understand the operational benefits to be gained from implementing AI-based data management processes. This “unstoppable trend towards AI” is being driven by board-level demand, especially within financial services, a sector he describes as being at the “bleeding edge” of technological adoption.

Many have had their appetites whetted by AI’s ability to streamline and improve the low-hanging fruit challenges they face, such as creating unique customer experiences and engagements. To embed and extend those AI-powered capabilities across their entire organisation, however, will take more effort, says Hanson.

“Their ability to harness data and exploit AI’s potential is going to be the difference between the winners and losers in the market,” he says. But the drive to get results quickly may lure firms towards rash decisions that could create more problems later.

“They need to think strategically about data management, but they can start small and focus on a small use case and an outcome that they can deliver quickly, then grow from there.”

Make it Simple

Among Informatica’s clients across 100 countries are banks such as Santander and Banco ABC Brasil, US mortgage underwriting giant Freddie Mac, insurer AXA XL and online payments provider PayPal. Among the services it’s providing such institutions are broad cost reduction by the optimisation of reference data operations and the simplification of their broader data processes.

This latter point is key to helping clients better use their data, says Hanson. Arguing that without good data inputs, AI’s outputs will be “garbage out at an accelerated pace”, he says that many companies have overcomplicated data setups that are hampering their adoption of the technology. By having separate tools to manage each element of their data management setup – including data access, quality, governance and mastering capabilities – large firms are strangling their ability to make AI work for them.

“But now complexity is out and simplicity is in,” Hanson says. “As companies modernise to take advantage of AI, they need to simplify their stacks.”

Enter GenAI

Informatica is helping that simplification through a variety of solutions including its own GenAI-powered technology for data management, CLAIRE GPT – the name being a contraction of “cloud AI for real-time execution”. The technology began life simply as CLAIRE seven years ago. Last year, however, it was boosted with the inclusion of GenAI technology, enabling clients to better control their data management processes through conversational prompts and deep-data interrogation.

Comparing the new iteration to Microsoft’s Copilot, Hanson says CLAIRE GPT now offers clients greater capabilities to simplify and accelerate how they consume, process, manage and analyse data.  Adding fuel to its firepower is CLAIRE GPT’s ability to enable individual clients to call on the combined metadata of Informatica’s 5,000-plus clients to provide them with smarter outputs.

While almost all of Informatica’s offerings are embedded with its new GenAI technology, the next step will be to ensure the company’s entire range of products benefits from it.

“Data management is complex and costly for many companies and it massively impacts the ability of the company to release new products, deliver new services and create more pleasing customer experiences,” he says.

“Our job with GenAI as the fundamental platform foundation is to offer more comprehensive services around that foundational layer of data management, and more automation and productivity around the end-to-end data management journey.”

The post Informatica Sees a Future of AI-Focused Innovation Releases appeared first on A-Team.

A survey by data security provider Dasera found that 73% of institutions questioned said they had high levels of confidence in their ability to fend off ransomware attacks, data breaches and other unauthorised uses of data. Nevertheless, records of attacks showed that those firms were among the worst affected in 2023.

“The significant number of breaches contradicts high confidence in their security strategy, suggesting overconfidence in their security posture,” the report, entitled The State of Data Risk Management 2024, stated. “The sector remains a prime target for cyberattacks due to valuable data, indicating a gap between perceived effectiveness and actual vulnerability.”

The report compared the perceptions of companies in a range of high-profile data-focused sectors, including healthcare and government, with statistics on data breaches compiled by a variety of organisations and studies. These include the Verizon Data Breach Security Report, Kroll’s Data Breach Outlook Report and the Identity Theft Resource Centre.

Record Year

The Dasera survey said the combined conclusions of those studies showed that 2023 was a “record-breaking year” for breaches.

According to Verizon, the financial services industry suffered 477 data security incidents in 2023, compared with 380 for IT firms and 433 in the healthcare sector. Only government bodies suffered more, at 582. Kroll found that financial firms accounted for the largest proportion of attacks, at 27%.

Two-thirds of breaches originated externally. With the balance coming from internal “threat actors”, the financial services firms were among the least protected against attacks from within their own systems.

The report found that 77% of breaches within the sector came from basic web application attacks, miscellaneous errors and system intrusions.

“The survey underscores the importance of adopting integrated and automated data security strategies to address these challenges,” the Dasera report stated. “Reliance on outdated, manual processes and slow adoption of automated systems contribute to current vulnerabilities. Organisations must prioritise modern, proactive approaches, including regular audits, strategic use of technology, and external consulting, to effectively navigate the evolving landscape of data risk.”

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**The latest results of the surprising snap French election are a timely reminder for asset managers to always expect the unexpected. The knock-on effects on their investments can create a metaphorical line at the door from anxious investors with a million questions on how their portfolios have been impacted.

Going into the run-off, the RN was widely expected to have a reasonable chance at gaining a majority. Instead, the leftist Nouveau Front Populaire bloc won the most seats in this most strange of elections, with Le Pen’s RN coming in third place. While the reaction from markets wasn’t as significant as it could have been, it still had impact on the French sovereign long-term borrowing rate against the German equivalent – a barometer of market sentiment towards French fiscal fortunes.

A major market event is often when an investment manager’s reporting and client servicing capabilities are tested to the limit. In the wake of election results, investors are desperate to get clarity on their portfolios, and how they are impacted. They are often on the phone, calling up their asset managers, requesting information on risk exposures, price impacts, and a plethora of other bespoke inquiries.

Outdate Data Systems

This is not just something that happens in isolation when market-affecting events occur though, it is part of a general trend for investors to become more demanding of the people managing their money. Perhaps this is reflective of the relatively easier access that they have to news in 2024 than they did 20 years ago.

As the news cycle intensifies, asset managers are struggling with outdated systems. Reliance on legacy infrastructure, combined with the piecemeal addition of new products, has made managing the growing volume and variety of data increasingly difficult. This information often isn’t centralised, and with thousands of different clients with varying servicing requirements, there is always a tendency to focus on repeatable client reports. There is also a reliance that requests are coming into the same place, but this often isn’t the case. If there is no central repository, the data that is being provided to clients will often be different – depending on what information that particular team has access to. When bespoke inquiries come in, they are incredibly difficult to deal with effectively. This is felt even more starkly if the incumbent data architectures are not interacting with a modern reporting solution.

Modern Architectures

While the fall-out from the French election does not seem to have been too severe on markets, it is a timely reminder, nonetheless. Client engagement is a key differentiator in an age where performance is squeezed increasingly by passive investing through exchange traded funds (ETFs)– it is important that clients remember who was able to put their minds at ease rapidly in the aftermath of surprise elections or other market-shaking events.

When you consider that those accounts that generally require the most bespoke treatment are the largest accounts, the ones that drive the majority of a firm’s revenue, it becomes clear why asset managers need to expect the unexpected, and prepare themselves with modern, interactive data architectures and reporting solutions.

The post French Election Reminds Asset Managers to Expect the Unexpected appeared first on A-Team.

Identifiers and standards ensure those attributes can be met. The challenge facing institutions, however, is that such rules often conflict or don’t exist. At the most fundamental level, for instance, company names may not be identically represented across datasets, meaning any analytics or other process that incudes that data could be skewed.

Industry Leaders

The webinar will see leading figures from the sector delve into the importance of identifiers and standards as well as provide context about their uses and benefits. On the panel will be: Alexandre Kech, chief executive of the Global Legal Entity Identifier Foundation (GLEIF); Robert Muller, director and senior group manager, technology product owner, at BNY; Emma Kalliomaki, managing director at Derivatives Service Bureau (DSB); and, Laura Stanley, director of entity data and symbology at LSEG.

“Identifiers and standards play a critical role in data management,” GLEIF’s Kech tells DMI. “They facilitate clear identification and categorisation of data, enabling efficient data integration, sharing, and analysis.

Without them financial institutions, corporates and other legal entities, would struggle with several challenges, he said.

Among those pain points are data inconsistency resulting from different systems using different naming conventions, which would lead to difficulties in data reconciliation and integration, and operational inefficiencies, with manual processes being used to verify and match data increasing the risk of errors and operational costs.

Additionally, Kech said, compliance risks that stem from fragmented and inconsistent data would prevent regulatory requirements to be met effectively; and, limited transparency would make tracing transactions and entities accurately difficult, potentially hindering risk management and auditing processes.

In essence, this would erode trust and reliability in the data, said DSB’s Kalliomaki.

“That is fundamental for firms to fulfil a lot of functions, but regulatory reporting is one that comes with great consequences if not undertaken properly,” she tells DMI.

“When it comes to having data standards, everyone is very aware that to better manage your data, to better assure the quality of your data, to ensure consistency alignment harmonisation with your counterparties and to mitigate the number of omissions and errors you may have, having standards is much more effective from a data management standpoint.”

Growing Need

“The amount of data that financial services firms are engaging with in their financial instrument processes is growing exponentially. Therefore, the need for data standards and identifiers is growing alongside this,” said Stanley at LSEG, which supports a number of identifiers, enabling delivery of a firm’s existing and evolving use cases.

LSEG issues proprietary identifiers such as SEDOL and RIC and acts as an National Numbering Agency for UK ISIN codes, is a globally accredited Local Operating Unit for LEI codes and recognises the importance of standards across the ecosystem and beyond regulation.

“At LSEG we acknowledge the potential of data when shared, the PermID is fully open and acts as the connective tissue that enables us to identify different objects of information and stitch data sets together.”

More Than Compliance

With robust identifiers and standards in place, the full value of data can be extracted. Among the benefits expected to be discussed in the webinar are:

• Improved decision-making and analysis
• Lower costs from reducing the need for manual data processing and reconciliation and from accelerating transaction processing
• Innovation driven by seamless data exchange between different systems and organisations
• Enhanced business agility and competitiveness that comes from providing reliable data for strategic planning and risk management.

“I see financial institutions using data standards and identifiers – beyond compliance – to a great extent,” says BNY’s Muller. “There are a number of best practices firms can employ, for instance strategy, design and education, to ensure standards and identifiers deliver value through associated business cases.”

With regulatory demands likely to increase over time the need for common identifiers and standards is expected to grow in importance and lead to harmonisation across borders.

“As a broader community, we all have to be willing to look at the greater good rather than commercialisation or IP-related aspects,” says Kalliomaki. “That harmonisation of us working together collaboratively is key.”

• A-Team Group’s How to Maximise the use of Data Standards and Identifiers Beyond Compliance and in the Interests of the Business webinar will be held on July 18 at 10am ET / 3pm BST / 4pm CET. Click here to join the discussion.

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The Adaptive Intelligent Document Processing product will enable financial institutions to automate the extraction of unstructured data for ingestion into their systems. The London-based company said this will let market participants automate a choke-point that is often solved through error-prone manual processes.

Duco’s AI can be trained on clients’ specific documents, learning how to interpret layout and text in order to replicate data gathering procedures with ever-greater accuracy. It will work within Duco’s SaaS-based, no-code platform.

The company won the award for Best Transaction Reporting Solution in A-Team Group’s RegTech Insight Awards Europe 2024 in May.

Managing unstructured data has become a key goal of capital markets participants as they take on new use cases, such as private market access and sustainability reporting. These domains are largely built on datasets that lack the order of reference, pricing and other data formats with which it must be amalgamated in their systems.

“Our integrated platform strategy will unlock significant value for our clients,” said Duco chief executive Michael Chin. “We’re solving a huge problem for the industry, one that clients have repeatedly told us lacks a robust and efficient solution on the market. They can now ingest, transform, normalise, enrich and reconcile structured and unstructured data in Duco, automating data processing throughout its lifecycle.”

The post Duco Unveils AI-Powered Reconciliation Product for Unstructured Data appeared first on A-Team.

SIX, a global data aggregator and operator of exchanges in its native Switzerland, as well as in Spain, has released a flurry of new data products since January, including a suite of ESG tools and two global equities index families that herald a plan to become a one-stop-shop for ETFs.

According to Leslie, the frenetic pace of partnerships, product releases and enhancements this year is just the tip of the iceberg. The Zurich-based, bank-owned organisation has more to come, all built around a trove of data and data capabilities it has built up over more than 90 years of operations.

At heart, it remains a global pricing reference data provider – that’s the “base data” that SIX “is built on”, says Leslie. But the company is putting in place ambitious plans to leverage that core data competency to meet the increasingly complex demands and use cases of financial institutions.

“I believe that the fundamental data set – having really good-quality reference data and pricing data – allows us to create new value-added services and insights to our clients, and that remains the same whether we’re talking about GenAI or good old fashioned master reference,” Leslie tells Data Management Insight from SIX’s offices in London. “Unless you’ve got those basics you can’t really make sensible decisions, let alone produce reliable analytics.”

Expansion Plans

Leslie says SIX sees its USP as the ability to leverage that core data product to create applications for a multiplicity of use cases. Already it is using its fundamental datasets as the backbone of regulatory, corporate actions, tax, sanctions and ESG products for its banking clients.

A slew of recent acquisitions, investments and partnerships have been similarly guided by SIX’s programme of creating services that can tap into its core offering. The purchase of ULTUMUS in 2021 and the deepening of a long-standing association with BITA earlier this year were part of a plan to forge the company’s ETF-servicing business, each deal enhancing SIX’s indexing capabilities.

In ESG too, it has been aggressively striking deals to help burnish a slate of new sustainability offerings. Products unveiled in the past year by ESG product strategy and management head Martina MacPherson all benefit from supply deals struck with vendors including Sustainalytics, MSCI, Inrate and the CDP, as well as new partnerships with companies including Greenomy. Among the ESG products launched recently is an SME assessment tool, which MacPherson said will bring thousands of smaller companies into the ESG data ecosystem, into which banks and investors might otherwise have had no visibility.

Working Data

SIX’s ESG provisions illustrate what Leslie describes as the company’s dedication to making data work for companies.

“Organisations need to figure out how they’re going to incorporate data and how they’re going to make it relevant,” she says. “Well, the only way you can make it relevant is if it’s got something to hook on to, and that’s where you get back to those fundamental data sets.”

Leslie explains that one of the driving forces behind the company’s vigorous expansion plans is the changing demands for data among banks. No longer can any part of the industry rely on end-of-day pricing data, or monthly and quarterly reports. Ditto for risk managers and compliance teams.

The consequence has been a shift in the workloads of the front-, middle- and back-offices. No longer is research the premise of middle-office teams, Leslie offers as an example; the front office needs those insights quicker and so it has made sense for banks to embed data access and functionality within asset managers own analytical workflows.

“Asset managers see that the speed of data is increasing all the time and so the buy side, which was perhaps in the past much more built around end-of-day or less immediate requirements, is moving much more into real-time and intraday needs,” she says. “That requires, therefore, real-time market data, and that is expected by regulators, it’s expected by customers, and its therefore expected by market participants.”

AI Challenge

Jokingly, Leslie likens data operations to raising a child: it needs constant attention and feeding to grow and thrive. The simile is just as true for banks’ data management needs too; they are constantly changing and growing, influenced by internal needs and external innovations. That’s exemplified by the race to integrate artificial intelligence (AI) into processes and workflows.

Recent SIX research found that more than nine out of 10 asset managers expect to be using AI within the next three years and that half already do. Driven by its own clients’ need to understand what AI will mean to them, SIX has begun looking at how it can enhance its products with the various forms of AI available.

It has taken a structured approach to the programme and is looking at where AI can help clients improve efficiency and productivity; examining how it can improve customer experience and support; and, testing how it can be incorporated into products. For the latter, SIX is experimenting with off-the-shelf GenAI technology to identify aberrations in trading patterns within a market abuse solution.

On this subject, too, Leslie stresses that SIX can only think about such an evolution because it is confident that it has a solid foundational data offering.

“Our role is to make sure that we’re providing data that is fit for purpose and enables our clients to do business in a competitive way,” she says. “So that will include, as it always has, providing trusted, reliable data that the client knows is fit for purpose and on which they can make decisions. And that’s as true if it’s going to an AI model as if it’s going into a client digital wealth platform or portfolio reporting or risk solution.”

Values Align

Leslie took up her latest role at SIX in 2020 and also is a member of the board for the SIX-owned Grupo BME, Spain’s stock exchange, previously holding roles at LSEG and Thomson Reuters.

She is proud to be part of an organisation whose stakeholders are banks – about 120 of them – and not shareholders “trying to race to hit a quarter result”. She feels a very strong alignment with its values, too.

“It’s an organisation whose purpose is to enable the smooth functioning of the economy and has consistency and trust at the very core,” she says. “When half the world is voting this year, this stuff’s important, and when we’re talking about AI, or we’re talking about market failures then the thing that brings trust and progress is the data that sits behind it. To be a trusted provider in this day-and-age is a critical service.”

The post Building Future Growth Around a Foundational Data Core: SIX’s Marion Leslie appeared first on A-Team.

The cash injection, which will be used to further develop BlueFlame’s AI platform, raises the company’s value to $50m, the New York- and London-based company said.

BlueFlame’s platform enables private market clients to use generative AI and natural language processing to source deals and streamline communications. It can also accelerate the review and surfacing of insights from PDFs and other unstructured data sources, such as confidential information memoranda, when negotiating deals.

The company is among a number of data services providers to launch products designed to help limited and general partners better use data in the running of funds that draw about a third of all institutional investment capital.

“AI is now a ‘must-have’ tool that alternative investment managers recognise is critical to streamline their operations, improve efficiencies and help them deliver cutting-edge strategies,” said BlueFlame chief executive Raj Bakhru, who helped form the company last year. “The value AI can deliver is clear and our investors understand the challenges of bringing structured and unstructured data together through AI tools while meeting compliance, security, and regulatory requirements.”

According to a statement, BlueFlame was founded by former cybersecurity, financial technology and governance, risk and compliance specialists. It has a 20-strong workforce and serves clients that have “hundreds of billions” of dollars-worth of assets under management, including private equity, hedge fund and wealth managers.

The post AI Startup BlueFlame Raises $5m for Alternative Markets Data Platform appeared first on A-Team.

As part of the arrangement, ratings provider Moody’s will gain access to MSCI’s data and models, which will eventually replace its own content in services offered to banking, insurance and corporate clients. That will include MSCI’s ESG ratings and scores. In return, MSCI will be able to use Moody’s Orbis database, which contains information on more than half a billion private companies.

The move has been described by the companies as groundbreaking and credit ratings specialist at Aston University, in the UK, Daniel Cash said it was inevitable that such “convergence” would happen among big players in the ESG rating and credit rating sectors.

“This is the first really important move in the related sectors together. It is an important move for the ESG rating sector specifically,” Cash told Data Management Insight, noting that Moody’s indication that it would step away from ESG ratings would increase the “duopoly in the ESG rating sector between MSCI and S&P”.

More Developments

The companies said they would also explore ways for MSCI to benefit from Moody’s credit rating scoring models for private companies: “Stay tuned for more updates,” said MSCI chairman and chief executive Henry Fernandez.

Both companies said the strategic partnership would “bring greater transparency on ESG and sustainability to markets and power better decisions”.

Moody’s is bolstering its ESG data capabilities at a time when regulators are requiring risk assessment providers to tighten the quality of their offerings and potentially to open their methodologies to public scrutiny. This comes amid accusations that opacity within ESG ratings is fuelling greenwashing.

The company already provides two ESG scores products but said the deal would not have an impact on Moody’s Ratings, its credit ratings business.

For MSCI, the deal will offer clients a portal into the increasingly important private equities and credits markets. ESG data on these companies has become a key target of financial institutions as they have diversified their holdings into alternative assets amid fluctuations in global capital markets. According to recent estimates, about a third of all institutional money is now tied into private markets.

The implementation of the EU’s Corporate Sustainability Reporting Directive (CSRD) is expected to raise the profile of smaller companies further, providing greater transparency into their ESG performances.

Earlier this year MSCI unveiled its MSCI Private Company Data Connect platform that brings together sustainability data from unlisted companies for use by private market funds and investors.

Market Implications

Cash, who predicted coalescence within the ESG ratings market in his 2021 book “Sustainability Rating Agencies vs Credit Rating Agencies: The Battle to Serve the Mainstream Investor”, said the timing of the Moody’s and MSCI announcement was significant.

“It is not coincidental that this move takes place as the EU are becoming the first major market for the agencies to actively regulate the ESG rating space,” said Cash, who is also ESG ratings and regulations lead at global law firm Ben McQhuae.

“Regulators – particularly in the EU – will need to be watching these developments very carefully because the impact and effect of duopoly on this nascent field is a significant ‘unknown’, which could have a dramatic effect down the line. As both S&P and MSCI are major providers of investment indices, this duopolistic move could have far-reaching effects.”

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Considering the use of GenAI, an early audience poll question asked to what extent organisations are committed to GenAI applications. Some 46% said they are testing GenAI apps, 24% are using one or two apps, and 20% are using a number of apps. Nine percent are researching GenAI and 2% say there is nothing in the technology for them.

Value of GenAI applications

A second poll questioned which GenAI applications would be of most value to a delegate’s organisation. In this case, 53% of respondents cited predictive analytics, 39% risk assessment, 39% KYC automation, 28% fraud detection and 19% portfolio management.

The panel shared their own use cases, with one member experimenting with GenAI to produce programming code and creating an internal chat box for data migration, as well as scanning data to surface information that can be categorised, sorted, filtered and summarised to create ‘kind of conversational extracts that can be used.’

All agreed that GenAI produces some low hanging fruit, particularly in operational activities such as KYC automation, but that the technology is too young for many applications, leading firms to build capability internally before unleashing GenAI apps for customers as there is still work to do around issues such as risk integration and ensuring copyright and data protection are not compromised. One speaker said: “There is a lot of experimentation and some research to do before we’re confident that we can use this at scale.” Another added: “There are just not enough skilled people to allow us to push hard, even if we wanted to. There’s a real pinch point in terms of skills here.”

Risks of adopting GenAI

Turning to risk, a third audience poll asked the audience what it considered to be the biggest risk around adopting GenAI. Here data quality was a clear leader, followed by lack of explainability, hallucinations, data privacy and potential misuse. Considering these results, a speaker commented: “We’ve already got existing policies and governance frameworks to manage traditional AI. We should be using those to better effect, perhaps in response to people identifying data quality as one of the key risks.”

The benefits of AI and GenAI include personalisation that can deliver better products to consumers and improve the way in which they interact with technology. From a regulatory perspective, the technologies are focused on reducing financial crime and money laundering, and resulting enforcements against fraudulent activity.

On the downside, the challenges that come with AI technologies are many and include ethical risk and bias, which needs to be addressed and mitigated. One speaker explained: “We have a data science lifecycle. At the beginning of this we have a piece around the ethical risk of problem conception. Throughout the lifecycle stages our data scientists, machine learning engineers and future engineers have access to python libraries so that when they test models, things like bias and fairness are surfaced. We can then see and remediate any issues during the development phase so that by the time models come to validation and risk management we can demonstrate all the good stuff we’ve done.” Which leads us to the need, at least in the short term, for a human element for verification and quality assurance of GenAI models in their infancy.

Getting skills right

Skills were also discussed, with one panel member saying: “We are living in a constantly more complex world, no organisation can claim that all its workforce has the skill set necessary for AI and GenAI, but ultimately I am hopeful that we are going to create more jobs than we are going to destroy, although the shift is not going to be easy.” Another said: “In compliance, we will be able to move people away from being data and document gatherers and assessors of data in a manual way to understand risk models, have a better capability and play a more interesting part.”

Taking a step back and a final look at the potential of GenAI, a speaker concluded: “Figuring out how to make safe products that we can offer to our customers is the only way we have a chance of reaching any sort of utopian conclusion. We must chart the right course for society and for people at work, because we’re all going to be affected by generative AI.”

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