Intertrust, a global leader in providing expert administrative services to clients operating and investing in the international business environment, surveyed over 500 capital markets executives to identify the impact that disruptive technology is having on jobs and skills. Of these, one in six (14%) believe that AI has already surpassed human-based systems.

In recent years, the data sources used in credit decision-making have become increasingly broad and non-traditional, now including social media activity, retail spending habits and even political inclinations.

The research revealed a division in the industry about the impact of using such data on the quality of decision-making. While a third (30%) of respondents believe that using a broader range of data reduces subjectivity, a fifth (18%) think AI exacerbates existing prejudices in the credit decision-making process.

Intertrust’s study also highlighted privacy concerns regarding expanded data sets. Although almost a third (31%) of respondents think that the use of non-traditional data such as and personalised algorithms leads to better credit decisions than just relying on detached data, 36% believe tighter legislation is required to protect borrowers’ rights when they apply for funding and to restrict the information included in the assessment. A fifth (20%) suggested that the use of non-traditional data has already overstepped the ethical line and needs to be better controlled.

Cliff Pearce, Global Head of Capital Markets at Intertrust said: “The use of AI in credit decision-making has become increasingly commonplace, with the potential to make quicker more accurate credit decisions based on an expanded set of available data.

“A challenge in this area is that AI systems are only as good as the information programmed into them. For example, while a prospect may look like a poor risk at first sight, there may be extenuating circumstances overlooked by the system that a human would have noted. Put simply, AI underlines the contrast between the prime and more specialised non-conforming lending markets.”

(Source: Intertrust)

In contrast to other gambling conferences, ICE London seeks to forge a connection between the offline sector and the online ‘iGaming’ sphere. The attendee list and event's floor reflect this amalgamation, with major brands from both land-based and online casinos showcasing their products alongside one another.

Organisers describe ICE as ‘the entire gambling ecosystem in one place’, referring to how not only casinos, but affiliates, payment solution providers, software developers and marketers are also represented. The jam-packed three-day event gives a good overview of the trends and topics shaping the multi-billion dollar industry. Here are a few themes at this year’s ICE which give us strong indications of what to expect for the future of gambling.

Blockchain Solutions
The relationship between cryptocurrencies and online gambling is a natural one; both crypto-technology and iGaming stem from digital innovation, and both concern varying degrees of risky investment. As more online players wish to preserve their privacy, cryptocurrencies present themselves as a practical alternative to traditional payment methods. FinTech companies offering integration of crypto-payment solutions to online casino platforms will be making their rounds at ICE, networking with those interested in the prospect of committing to the still burgeoning world of blockchain technology.

Facial Recognition Software
There are a number of focus points specifically for the land-based casino sector, as evidenced by this year’s exhibitions at ICE. One such technology which is peaking the interest of many attendees is that of AI facial recognition for land-based gambling establishment. The technology is developed to heighten security, strengthen statistics, and improve player experience. One provider of facial recognition is Fincore, a company which is demonstrating the benefits of monitoring player behaviour through assigning IDs to faces.

The suggestion is that this technology will allow casinos to more efficiently identify valuable players, problem gamblers, and trouble makers. “The Facial Recognition system uses the latest developments in Data Science (AI) to create a more easily managed and personalised offering,” says the B2B Commercial Director Jamie Maskey. Monitoring individual players with facial recognition will help casinos personalise VIP offerings and share information on cheaters and problem gamblers with other casinos.

Customer Verification Solutions
The importance of complying to KYC (Know Your Customer) particularly in the gambling industry can not be understated, and at this year’s ICE there will be a few FinTech companies showcasing their KYC solutions. One such company is Safened, a FCA-licensed payment institution that claims to make customer verification process faster, simpler, and more thorough. With so many regulated brands looking for cost-effective means of complying to KYC in light of the 4th EU Anti Money Laundering Directive and GDPR, it’s clear to see why these solutions are proving a hot topic at ICE. “We believe that the cascading of checks is an effective way to form a holistic view on a client and in the process to filter out fraudsters. There is a lot of activity in the digital KYC space, but what sets us apart is the fact that we are a regulated financial institution that can offer an end-to-end solution”, says Kirk Gunning, CCO of Safened.

Content Marketing
For online casinos, the increasing trend of outsourcing marketing and content services is evident by the growing number of creative agencies present at ICE. “Many online casinos that have traditionally relied entirely on affiliates are realising the value of increasing the degree to which they invest in their own marketing”, explains Lucy Jacobs from PlayFrank UK. “Stricter marketing regulation means online casinos want to retain control over their own advertising for 100% compliance, but it’s also a matter of realising how important a brand’s own content marketing is for a sustainable online presence and long-term brand awareness.” Offered by the many agencies at ICE are branding services, content writing, translation and localization and SEO. A number of discussion panels will also be held with regards to the topic of marketing gambling products.

Game Providers
Major casino game providers will, as usual, be present at ICE - including the biggest names in the industry such as NetEnt, Play’N’Go and QuickSpin. However, this year also marks the debut of some smaller but fast emerging providers. Red Tiger Gaming Limited is a relatively young name but is making waves at ICE where the developers are showcasing their unique Daily Jackpot games. Online casinos are continuously looking to strengthen their game portfolio and will be keeping a close eye on the next big providers in the industry.

Esports
Although esports betting has not yet exploded quite as exponentially as some have predicted, many existing sportsbooks believe there simply been a failure to seize the market. As such, a lot of networking is focused on bringing esports expertise together in developing a successful esports betting product. An ICE workshop held on the 6th of February will look at the potential of esports in relation to the gambling industry, focusing on an esports market overview, forecast and valuation. With the global esports market currently valued at $493 million, it seems that there are plenty of opportunities in this sphere. What sportsbooks have realised is that there are unique challenges of establishing a brand within the esports community - a community rather unlike the fanbase of traditional sports. It is these perceived challenges that the workshop intends to tackle.

Affiliate Programs
A record number of gambling affiliates have led to a need for more - and better - platform management tools than ever before. From casino operator's perspective, affiliate management tools have become increasingly important in keeping track of various partnerships and their costs. The London Affiliate Conference (LAC) will be held right after ICE so that those offering and seeking affiliate deals can attend both conferences. A panel talk will initiate discussion on how to organise affiliate programs and find appropriate partners, as well as how to offer better deals as an affiliate name in an increasingly competitive field.

There are 8,500 operators and 150 countries in attendance at this year’s ICE - most likely beating the record of last year's 3,000 attendees. Though the full scope of ICE’s impact on the gambling industry is better understood in the context of an annual overview, there’s no doubt that this year’s conference will be pivotal in helping shape and reflect the discussions central to the gambling industry and its future.

This is why Dean McGlore from V1 believes that in 2019, we’ll see CFOs switch their focus from AI to automation.

In 2019, automation – also known as Robotic Process Automation (RPA) – will move from the shadow of Artificial Intelligence. And rightly so. Like AI, it can relieve teams from mundane and repetitive work to focus on higher-value and strategic activities. But, unlike AI, automation is easier to access, expand. It’s a forecast echoed by experts around the world. Forrester, for example, predicts that the RPA market will reach $1.7bn in 2019 while Advanced has found that 65% of people would be happy to work alongside robotic technology if it meant less manual processes.

Over the next year, we will especially see RPA climb in popularity within the finance function. Teams will use it to automate the data capture and processing of supplier invoices, sales orders and other accounting documents. By automating these manual and usually administrative heavy processes, finance teams can drive unprecedented productivity and efficiency levels as well as benefit from increased visibility into the entire organisation and better data for reporting to the board.

RPA will help with a host of other external factors too. With the General Data Protection Regulation (GDPR) now in place, it will help the finance department (and indeed other areas of the business) get their data in order. RPA is a good starting point for GDPR compliance, as businesses can store, manage and track electronic documents and electronic images of paper-based information in one place and in real-time. This ensures compliance requirements by providing traceability on all documents.

Automation technologies will only be effective if the people using them understand how they work, appreciate their true potential and recognise the value they bring.

And then there is Brexit. Because RPA helps free up time for the finance team, more resources can be devoted to planning for when Britain leaves the EU in March. RPA provides an opportunity for businesses to scale up or down volume to meet demand from outside of the EU, for instance, as well as to assist the development of new products and services for new markets – all of which is essential for business growth. Moreover, with the threat of other countries hiking up tariffs after Brexit, RPA has the potential to replace the need to hire more employees and it can also help keep production costs to a minimum.

Regardless of the reason behind RPA adoption, CFOs will need to make sure that there will be a change in culture among the workforce. Automation technologies will only be effective if the people using them understand how they work, appreciate their true potential and recognise the value they bring. Arguably, investing thousands on pounds on technologies such as RPA won’t be effective if users don’t believe in them. A robust upskilling and training programme is necessary to ensure future digital success.

However, saying that businesses will turn their backs on AI in 2019 was never my intention – Artificial Intelligence will still play a key part of many organisations’ digital transformation plans. What RPA does is allowing businesses to test the water. Planning and testing automation software to see the impact it has on your operations and staff is a great indicator of the benefits that large-scale AI deployment could bring in the future – minus the fear of large-scale failure.

Planning and testing automation software to see the impact it has on your operations and staff is a great indicator of the benefits that large-scale AI deployment could bring in the future – minus the fear of large-scale failure.

In the future, we will see RPA and AI working together to transform the finance function like never before. With a combination of the right technology with AI handling decisions and chatbots managing customer queries, completely unmanned Accounts Payable (AP) for example is perfectly achievable by 2020 as a result of invoice automation.

RPA will be the first step for many and businesses looking to realise the power of automation over the next 12 months should take the following steps:

• Audit your processes and identify which involve low-skills, manual and repetitive tasks, such as many of the core, yet daily finance functions of invoice processes;
• Determine the key technologies that your business needs to become more agile, competitive and productive. RPA and AI have different capabilities, so decisions must be made based on need, rather than hype;
• Understand which new technologies are best placed to modernise or integrate with your organisation’s existing legacy systems;
• Ask yourself what the potential benefits of RPA and AI are to your finance team. Understand employees’ pain points before deciding which digital tools will help;
• Appoint a digital pioneer – someone that will drive positive technology change and that has the backing of your CEO and the rest of the C-Suite;
• Engage with your younger workforce. Typically, they are more digitally savvy and open to change. Find out what technologies they think will make a real difference.

RPA has the potential to change the face of finance for good. And, eventually, it will become ubiquitous among all key processes.

We’ve all heard of the so-called ‘war-for-talent’ within the US’s Investment Banking and Financial services field. In fact, it’s no secret that there’s an ever-increasing demand for specific and niche skills, but short supply of the requisite talent.

According to EY, over the next two to three years, machines will be capable of performing approximately 30% of the work currently done at banks: yet the ability to attract technology experts into investment banking is arguably presenting the greatest challenge for many employers.

Regulatory changes, coupled with digital advancements, mean that business models are adapting at a rapid rate. Today, automated electronic trading powered by AI and machine learning mean that the skills of the top traders of yesteryear are quickly becoming obsolete. However, the data scientists and programmers needed to drive today’s systems are in short supply. And with increasing reports of tech firms such as DeepMind, the Google artificial intelligence division, stealing top tech talent from the world of investment banking, this is only going to get more difficult in the coming months and years.

Today, automated electronic trading powered by AI and machine learning mean that the skills of the top traders of yesteryear are quickly becoming obsolete.

Furthermore, recent research from Accenture has found that just 7% of US graduates see banking and capital markets as a top industry to work for. However, by predicting both the behaviors of internal employees and market demand fluctuations, investment banks can map out a coherent plan to overcome forecasted skills gaps and bring in expertise to guarantee future growth and profitability.

Despite the clear benefits of implementing an effective strategic workforce plan, a 2014 Workday/Human Capital Institute survey of 400 HR professionals revealed that 69% consider the function either an “essential” or “high” priority, but that only 44% actively engage in it. This is not because there are not tools available – there are. Both internal data and industry trends are usually an excellent source of knowledge of individual jobs’ attrition rates, which can lead to a surprisingly detailed forecast of skills needed for the future. Technological tools can also be used to predict the likelihood of employees jumping ship, including through social media monitoring applications. So why is this disparity in numbers?

Although increasing percentages of businesses are recognising strategic workforce planning’s place within their growth plans, it can still be difficult to implement and sustain effectively. As well as needing the support of a CEO – or at least, a board member – to drive the initiative and free up resources, HR departments must also be star players in its success. This is because they can provide reliable data regarding which employees are eligible for up-skilling/re-skilling, helping to predict gaps within the workforce – although these may open and close as market demand fluctuates. In this way, the data can also be used to implement a policy of growing your own internal talent, which can subsequently help to close projected managerial gaps in the future. You can see that it is important to remember that technology is just a support tool and should not overshadow the input of your stakeholders – they also have real insight in the business’ needs.

The traditional trading desks of Wall Street in the early 80s are now well and truly a thing of the past.

One common misconception about a successful workforce plan is that it is rigid and set in stone when in fact, almost exactly the opposite is the case; what might be needed for a financial institution now may be totally different in five years’ time. Naturally, it is important to address the organisation’s most critical needs first, and not rush to implement an overarching strategy. This allows for progression and, critically, facilitates the avoidance of paying premium rates whilst trying to fill immediate skills gaps.

The traditional trading desks of Wall Street in the early 80s are now well and truly a thing of the past. But just as open outcry and hand signals have been replaced by predictive analytics and machine learning, no one knows what the future will hold for the profession. With this in mind, an effective plan must be adaptable and almost constantly fine-tuned in order to stay in line with market demand, new platforms, emerging markets and regulatory change – especially when reacting to or predicting competitors’ moves.

In fact, it is intrinsically important to keep your competition at the very front of your mind when constructing a workforce strategy. It is highly likely that you will be fishing from the same talent pool down the line, and predicting skills gaps means that your business will be able to create pipelines and contacts within these areas long before anyone is needed on board. This provides the best chance of winning the top talent – and these acquisitions can be the difference in staying a head and shoulders above the rest.

About Nicola Hancock:

Nicola Hancock has over 15 years’ experience in resourcing for financial services organisations. During her time with Alexander Mann Solutions, she has led a number of key clients globally, including RBS, Deutsche Bank, HSBC and BAML and has built extensive experience and understanding of financial services and the challenges and opportunities this brings to talent acquisition and management. 

Below Russell Bennett, Chief Technology Officer at Fraedom, discusses the future prospects for AI in the banking sector, and what 2019 may hold.

AI is incredibly complex and doesn’t represent a single technology. Rather, it’s a multidimensional field encompassing a range of different technologies and methods, each supporting and supported by the others[1]. The technology’s pace of evolution has grown exponentially in recent years and if AI’s benefits and limitations are understood, it’s believed this technology will have a tremendous impact on the banking industry in 2019.

With so much potential ready to be unleashed, where exactly will we see AI’s influence in the banking sector in 2019?

Chatbots and Virtual Assistants

While chatbots have been used by financial institutions for several years, thanks to advances in AI their capabilities have continued to grow. Whereas they were once only used to answer generic FAQs, for example, most chatbots are now capable of initiating and performing tasks on their own. Thanks to these developments, Juniper estimates that the introduction of chatbots and virtual assistants will save companies $8 billion per year by 2022[2]. This is set to be only one of the benefits to banks with Gartner suggesting that by 2020 consumers will manage 85% of their total business interactions with banks through fintech chatbots[3].

Juniper estimates that the introduction of chatbots and virtual assistants will save companies $8 billion per year by 2022

While this could be a source of worry for the banking workforce, in reality, there should be little concern. Rather than acting as a replacement for employees, banks instead seem to be looking at AI as a tool to help release pressure points and empower the workforce with Accenture even predicting that banks that deploy AI wisely will see a 14% increase in jobs[4].

In 2016, Santander became the first UK bank to launch voice banking technology[5]. Of course, since then a large variety of global banks have adopted this technology in one way or another, suggesting that banks are looking at utilising AI beyond chatbots. In fact, with Mariano Belinsky, managing partner of Santander InnoVenture, discussing natural language processing[6], it seems to only be a matter of time before virtual assistants come into use.

Driving Customer Insights

Last year, we saw a clear disconnect between banks and their smaller customers. In these situations, intelligent automation could well be the answer to support businesses and provide a better service as well as working seamlessly with third parties and fintechs, rather than against them.

In our recent study of SMEs in the UK and US, we found that less than 20% of SME owners thought that banks they had dealt with over the past year fully understood their needs as a business, demonstrating a clear lack of engagement. In 2019, using automated data collection on an ongoing basis, behind the scenes, can ultimately ensure bank relationship managers are better equipped with in-depth knowledge about their customers; hence best positioned to support their business and provide a better service.

Less than 20% of SME owners thought that banks they had dealt with over the past year fully understood their needs as a business.

Security and Compliance

One of the key differences between AI applications and other, more traditional technological solutions, lies in AI’s ability to continuously learn from the data it is supplied with, hence refining its decision-making processes over time.

Cybersecurity is a current hot topic for the financial services sector and regulatory compliance is another. AI can add real value in both of these areas. Machine Learning platforms can be coded to identify user patterns and detect anomalous network behaviour, something that’s increasingly essential as cyber-attacks are often disguised with inconspicuous data or code.

In recent years, technology has been a disruptor and an innovator. Technology is increasingly helping shape customers’ wants, needs and expectations. With a raft of new regulation encouraging the use of technology in banking, there’s nowhere left for anyone to hide. The technology revolution is in full swing and for banks, it’s very much adapt or die.

In the very near future, it is likely that AI will completely revolutionise banking. It will redefine how banks operate, what innovative products and services they create and how they evolve the customer relationship. Banks must, therefore, embrace this new technology or risk of falling behind in an extremely competitive environment.

[1] https://www.accenture.com/t00010101T000000Z__w__/gb-en/_acnmedia/Accenture/Conversion-Assets/DotCom/Documents/Local/en-gb/PDF_3/Accenture-Redefining-Capital-Markets-with-Artificial-Intelligence-UKI.pdf

[2] https://www.juniperresearch.com/press/press-releases/chatbots-a-game-changer-for-banking-healthcare

[3] https://www.gartner.com/imagesrv/summits/docs/na/customer-360/C360_2011_brochure_FINAL.pdf

[4] https://www.accenture.com/gb-en/insights/banking/future-workforce-banking-survey

[5] https://www.santander.co.uk/uk/infodetail?p_p_id=W000_hidden_WAR_W000_hiddenportlet&p_p_lifecycle=1&p_p_state=normal&p_p_mode=view&p_p_col_id=column-2&p_p_col_pos=1&p_p_col_count=3&_W000_hidden_WAR_W000_hiddenportlet_javax.portlet.action=hiddenAction&_W000_hidden_WAR_W000_hiddenportlet_base.portlet.view=ILBDInitialView&_W000_hidden_WAR_W000_hiddenportlet_cid=1324582275873&_W000_hidden_WAR_W000_hiddenportlet_tipo=SANContent

[6] https://www.americanbanker.com/news/what-santanders-latest-bets-say-about-the-future-of-fintech

Most of Nitin’s career has been involved with business model changes around disruptive technologies and M&A work in the TMT sector for companies around Silicon Valley. He has developed M&A strategies, conducted commercial/operational/technical due diligence and has assisted with M&A integrations and separations for his clients. He specialises in creating value from emerging technologies and helping his clients prepare and adapt to the next big thing. A veteran with over 1,000 transactions, he specialises in revenue synergies and has also led dozens of cost-focused consolidation M&A deals. His recent work includes helping CEOs, boards, investors and business leaders transform their business models by leveraging disruptive trends and M&A to pivot into new business models, utilising technologies such as SaaS, SDN, blockchain, open source, AI, IoT, AR/VR, drones and voice-enabled devices.

“As a Silicon Valley insider for two decades, it is a fascinating challenge to utilise my business knowledge, network of experts, consulting skills and experience in M&A deals to solve problems at the cutting edge of new technologies”, says Nitin. “I have built an expansive network in Silicon Valley with TMT sector clients who look to me to help them through difficult business changes, serving as both a trusted adviser and personal advocate.”

 What are the current key business and technology trends within the TMT sector?

I believe that today we are experiencing the equivalent of tectonic shifts in business that are primarily technology-driven and are impacting the fundamental ways we do business – and these trends extend far beyond the technology sector. These shifts can conflict with each other, making business strategy more difficult to conceptualise and execute today than it was in the past. Some of these shifts are as follows:

• Product to cloud vs. cloud to edge;
• Centralise (SDN/NFV) vs. decentralise (e.g., blockchain);
• Players who monetised voice are now monetising data (e.g., telcos), while those who monetised data are now monetising voice (e.g., Google, Amazon);
• Brick-and-mortar stores to an omni-channel retail economy, or ‘bricks-and clicks’;
• Closed-source to open-source (Android);
• Human to machine (AI);
• Real to virtual (AR/VR); and
• Building traditional enterprises vs. monetising ecosystems.

Each of these shifts is a transformation that presents an opportunity to get ahead of the game.

There are few absolute rules in this new frontier – companies need a data-driven approach to navigate the complexity, uncertainty and ambiguity, which has become profound over the last few years and is not likely to abate.

Traditionally, technology has served to enable or enhance existing business models or to create entirely new ones. More recently, we find ourselves in a place where there is a developed technology, but the ecosystems and business models around it are taking longer to evolve. Take, for instance, blockchain – here we have a viable technology, but it will take a few years to build scalable business models around it and monetise it. CEOs and corporate think tanks must devise new ways of adapting in such a landscape.

I have built an expansive network in Silicon Valley with TMT sector clients who look to me to help them through difficult business changes, serving as both a trusted adviser and personal advocate.

How is FTI positioned to take advantage of these so-called shifts and disruptions in the market?

FTI is configured differently than traditional consulting firms because we have an expert-centric approach to creating value for our clients. Most of our practitioners have deep industry experience, having operated businesses as executives and in consulting for several years, which has created a lot of credibility with clients and other executives. We are also an industry- and sector-oriented firm and taking a profitability view of the business is a highly valued and impactful perspective for our clients. We not only understand the sector, trends and structural shifts, but can also translate those into meaningful operational and tactical outcomes. Our clients tend to hire us for our expertise and experience rather than to simply add leverage to their internal teams. Given the highly sector-focused approach, we tend to formulate points of view on what is coming next, to ensure our clients are well prepared to adapt.

You have quite an amazing M&A background as well. What are key current M&A trends and drivers in the sector?

There is a lot going on in the M&A world. The last two years have been record-breaking, with unprecedented deal activity across industries, geographies, private equity and corporates. While there is some rumbling that M&A is slowing, I think that the big drivers are intact. For one, the US dollar has appreciated significantly against some developing market currencies, and that creates an interesting value discount. The 2017 tax cuts will continue to put more money in the hands of corporates, which will likely fuel M&A activity. The wave around digital business models is not cresting, and companies will acquire or strengthen their capabilities in this space. Incumbents will continue to consolidate to survive and create scale.

All these trends have put pressure on internal M&A teams and external advisers to create more value and to do it quickly. M&A integration has gone through a lot of change, and many professionals have still not adapted to the structural integration aspects and approach it ‘function-by-function’, limiting their ability to create value. There are several industries and sectors where the M&A wave is just starting – the scaling of technologies such as blockchain and AR/VR will attract preemptive strikes from bigger players. Private equity firms continue to be aggressive and are developing some unique strategies for deploying capital and creating value. When you consider all of these trends, I don’t think that M&A activity in the sector will slow down appreciably anytime soon.

The last two years have been record-breaking, with unprecedented deal activity across industries, geographies, private equity and corporates.

How do you go about keeping up with all the trends in the market while continuing to build skills and reinvent yourself?

This is an important aspect that has become critical if you want to stay current, relevant and excel. Learning patterns, adapting and creating value for the entire ecosystem around you is vital when working within this field. Gone are the days when one could read a few books or attend a couple of training sessions to grasp a new subject. Our clients are very smart people and they have access to a vast collection of materials and resources.

The way I have adapted is by learning from my network. For example, I learned about autonomous driving by speaking with approximately 50 companies across the value chain. By the time I spoke with a couple of dozen players, I started seeing patterns and trends that they were not able to see individually, such as partnership opportunities, M&A opportunities, market needs and disruptive trends.

After you’ve networked, it’s about building insights and getting into more details through targeted discussions around specific areas of autonomous driving. Clients value market insights and trends from external sources as validating. I did something similar with blockchain and IoT previously. One can always dress up their credibility with technical credentials, but this is usually less effective than learning from the field and building insights and skills from it. People are also curious about what others are thinking and doing, hence forming a cohesive, defensible, fact-based point of view often goes a long way.

Gone are the days when one could read a few books or attend a couple of training sessions to grasp a new subject.

It is widely believed that you are one of the most connected C-Level Executives in the TMT sector. How have you built such an impressive network?

Great networks are always built over time. It is easy to make connections, but it’s a lot harder to maintain them. I like connecting with people in general and I like exchanging ideas and facilitating with them – be it making introductions, sharing insights, learning from them, advising them or being helpful otherwise. Not all meetings have to be about getting something out of them – be genuine, take interest, help if you can and I guarantee that will deepen your relationships with them. I always tell people that if your relationships are strictly an outcome of your business, then something is not right, but if your business comes to you as a byproduct of your relationships, then you are doing it right. Remember, it is about the quality and strength of your network – not the numbers. It takes a lot of commitment to genuinely foster and maintain a network as it gets bigger. Your network is like a living organism and it needs to be nurtured in order to strengthen and grow. There is not one magical formula for this; everyone has different styles, but it is important to know what works best for you. The crucial element is to put yourself out there in the field.

You have received multiple awards for pioneering new approaches in M&A – please tell us about them.

The most important outcome is to innovate and adapt – awards are only a byproduct of that but, of course, serve as a validation and recognition of your contributions. Some of my work that has been externally recognised is creating a new framework for delivering revenue synergies in M&A, a new approach to managing M&A from strategy through integration by utilising Wargames - a new and unique way to assess blockchain and understand how to unlock its business model value. Additionally, I am currently working on building a new approach to assess and integrate platforms, which requires a different approach from integrating products or processes. When it comes to platforms, the bulk of value created is outside the company and delivered through network effects. Stay tuned for more on this topic.

How does one go about generating new business in today’s world? Has the approach to sales changed?

I think the best way to sell nowadays is to be visible in the right places, share insights and experiences to create a ‘pull effect’. You can no longer just show up and talk about the services your firm offers and wait for the client to bite on something relevant. More specifically, today’s clients judge your expertise by how well you understand their business, trends and context apart from your technical or functional area.

Today’s clients judge your expertise by how well you understand their business, trends and context apart from your technical or functional area.

My field is highly relationship-driven – the deeper you know your topic, the more amplification you will get from the network or relationships in order to get referrals. We don’t live in an age of long attention spans. If you meet the CEO of a company in the elevator, speak about business issues relevant to him. If what you’re saying resonates, you’ll have plenty of opportunities later to talk about how great your firm is.

You also sit on boards of multiple companies – can you tell us about them? How do you choose the companies that you join?  

Foremost, I need to genuinely believe in what the company does and that I can really add value. I am always happy to help talented people with my ideas, skills or network. A great idea is unlikely to succeed without great management teams, and resonating with these people is a key consideration for investing time.

I’m also attracted to disruptive technologies that could have a big impact on the business world. Some of the companies that I am a board member of include Pronto, a partner orchestration and automation platform; SmartBeings, an AI based smart speaker focused on enterprises; and Crosby, a blockchain-based asset tracking technology which is unique and differentiated.

What is your advice to CEOs and how do you adapt to changes in today’s world?

• Get comfortable making frequent or sudden pivots. Never get into a comfort zone or be complacent, even when you are ahead of your competition.
• Find builders and give them responsibility, authority and accountability.
• Develop foresight and skillsets to navigate business complexity and strategic ambiguities.
• Move away from intuition to data-driven decision making wherever possible.
• Build ecosystems and develop skills to monetise them. There is no need to own the value chain, but you should learn to have a specific and influential role in it.
• Continuing with traditional approaches will not change much.
• Invest in continuous and fast-paced learning.
• When it comes to the organisation, be agile and respond quickly.

What is your advice to the Management Consulting community on how they should adapt to the changing landscape?

• Understand the changing business landscape and identify your niche, skills required and ways to play.
• Look at ways to adapt your skill set and see how you can create value as the next big thing surfaces.
• It is about constant learning, reinvention and reorientation of your skills.
• Bring data, facts and insights into everything that you do and put yourself out there.
• Your network is a vehicle to engage, learn and amplify your personal brand – reach out to people and create avenues to exchange value.
• Client relationships are for life. Stay engaged and avoid tendencies to move on after your successful project.
• Adapt your thinking from pure enterprise or client to the ecosystem itself – you will discover more ways to add value for your clients.

The emergence of AI has had a positive impact on the financial industry and has enhanced productivity, in particular in the accounting and banking areas. Therefore I anticipate that machine learning will definitely be a significant area of investment in the near future for this sector.   However, as with any change of this magnitude, the benefits offered by the implementation of AI in the financial sector are met with a number of challenges – most notably businesses ensuring they are equipped with the right technology, staff and skills to embrace AI and automation.

Automation is now used to perform or enhance many administrative tasks, and Artificial Intelligence is already more a part of daily life than you might realise. Robotics, while commonplace in manufacturing, are beginning to show impact in other sectors. One of the key drivers behind the adoption of AI software in the financial sector is the time-saving benefits it offers users. Gone will be the days of long hours spent working on spreadsheets, processing data, or handling customer enquiries. Those tasks will be streamlined by machines, allowing workers to focus more time on complex tasks which require human touch. As well as working with advancing technologies, junior employees will be involved in more planning, reporting and analytical jobs, and as such their required skill set will change.

Gone will be the days of long hours spent working on spreadsheets, processing data, or handling customer enquiries.

Through machine learning, artificial intelligence can painlessly consume and process large amounts of data at an accelerated level. Its vast speed brings efficiency and productivity to the financial sector, and as it continues to develop and become even more efficient, it can identify more patterns than ever before, providing scope for customised offerings to customers. However, this being said, adoption of AI in the financial sector imposes many challenges to the industry. The use of AI’s ability to consume large amounts of consumer data raises questions about how this information is stored and processed and to what end. Organisations that encourage, and even mandate the uptake of these types of technologies must tread carefully. Individuals are already highly attuned to the sensitivity of their personal information and will require robust guarantees about the security of any further information they are willing to give up.

One limitation of machine learning in this context is that it primarily relies on the basis of historical data sets and as a result, can fall into the trap of becoming repetitive, as well as potentially giving way to conscious or unconscious bias. For instance, how fair can a financial system really be without human involvement? In a world where new technologies are quickly improving or even replacing existing processes, there is one area that cannot be automated, and that’s building strong relationships with clients. The human element is needed in these instances to perform certain job functions that AI is incapable of replicating. Individuals have the ability to be aware of their own emotions and those of others, but also their capability of showing empathy in the way they handle interpersonal relationships, which is known as emotional intelligence.

It’s crucial for businesses, in the fast pace of today’s world, to continue to develop and think about where their use of data can get them tomorrow, as well as where it’s got them today. Organisations must not become complacent, and instead continue to reflect on their processes, challenge routine and be future-facing in their approach to machine learning.

One limitation of machine learning in this context is that it primarily relies on the basis of historical data sets and as a result, can fall into the trap of becoming repetitive, as well as potentially giving way to conscious or unconscious bias.

Over the last two decades, technology has advanced at such a speed that many roles in the financial sector have either disappeared or wholly changed due to the implementation of AI technology. One of the many challenges facing the finance industry is the impact that AI is having on the job roles within sector. Artificial intelligence and automation can take on many of the tasks a transaction led accountant or data administrator would typically undertake, with little or no human involvement. The process is almost seamless, error-free and time efficient.

The challenge of economic survival of the financial sector is to not only accept these changes, but to capitalise on them. With any significant change in the market, there’s always a fear that it will eliminate jobs from the workforce. AI tools may well remove a number of job tasks carried out by accountants and data administrators, but rather than eradicating jobs and losing talented members of staff, employers will need to ensure that their HR directors are equipped to spot the right skilled professionals who are well versed with the latest AI technology. The HR function will also need to quell fears of job losses amongst employees and instead empower their staff to adapt and develop new skills to work alongside new technologies.

At this juncture, skilled employees are key – and we anticipate a change in the skills that businesses across the financial sector will be demanding from their employees and prospective hires. For years, Michael Page clients in this sector have been seeking candidates with financing and analysis skills; those that have a strong understanding of financial planning and reporting; people who are adept at using Excel and other such software. Our recently launched Skills Checker tool has taken the most in-demand skills for roles across the financial industry to highlight what employers are looking for today. But as we continue to see AI and automation adoption increase in the sector, we expect to see a rise in employers expanding the skill sets they require from new employees with coding and AI experience becoming ever more valuable.

One of the many challenges facing the finance industry is the impact that AI is having on the job roles within sector.

To the same end, the advent of these new technologies presents the opportunity for businesses to enhance their current workforce by equipping employees with the skills to work alongside AI and automation. A challenge in itself, such training should not be brushed off as a ‘nice to have’; it is vital for the growth, and even the survival, of a business. Employees are the lifeblood of any business, as the landscape of the financial sector changes, businesses must ensure that their workforce is keeping pace with the industry.

Before incorporating AI software into their businesses, organisations will need to think strategically about what their key objectives are and what they hope to achieve from using the technology. This is the only way they can truly expect to see any long-term benefits, through a strategic and considered approach – not simply thinking of AI as a ‘nice add-on’. It’s also important for organisations to have realistic expectations.

Businesses should start by looking at key areas where they can make an impact by using this technology on more routine tasks and go from there. This will help to build their confidence and understanding of the software over time, rather than trying to implement it all at once. Strategic thinking and patience are key here.

Although robots and AI will inevitably take a lot of the more data-driven job functions, there will be a change in how humans and machines interoperate for the highest level of efficiency and playing to each other’s strengths. The increased use of AI in the financial sector is going to spur on new innovation, and an entirely new landscape of jobs are going to emerge. Although there is always a lag between the adoption of new jobs and loss of current jobs, up-skilling and re-skilling are going to be the key to success in the future of the financial job market.

Website: https://www.michaelpage.co.uk/

With increasing high-street competition, AI is redefining the banking sector with each and every customer interaction. With banks, like NatWest, deploying AI-based virtual assistants to offer customer-facing communication around the clock, the consumer banking experience is now heavily digitised, with 86% of banks stating they now use AI technologies in some way. 

Martin Linstrom, Managing Director for UK and Ireland at IPsoft, looks at the next stage in technological evolution of the banking industry and how artificial intelligence (AI) will redefine banking as we know it.

The banking industry has made huge strides to drive innovation by investing in new technologies over the last few decades. Commercial banks first adopted telephone banking, then came internet banking and now, for most customers, all your financial services needs can be met via an app. Now, as we enter the conversational era enabled by cognitive AI, customer expectations have evolved once again.

Banks have long been ahead of the curve in terms of elevating the user experience for their customers and so, it’s perhaps unsurprising that many are already looking to AI-powered digital assistants and are investing in cognitive solutions to upgrade and scale customer-facing financial management processes. Many banks are also looking at how they can provide the same simple, frictionless service to their own employees.

Banks have long been ahead of the curve in terms of elevating the user experience for their customers and so, it’s perhaps unsurprising that many are already looking to AI-powered digital assistants

As AI-powered customer interfaces gain mainstream acceptance, we will once again see a revolution in technological change within the banking industry. So, what functions within banks will cognitive assistants transform?

Building a hybrid workforce

Virtual assistants have a twofold capability which is driving innovation in the banking industry. Firstly, they can be implemented in back office functions such as finance or HR and secondly, they can supplement customer service centres. Creating a hybrid workforce of human employees and AI-powered virtual assistants can help drive enormous cost efficiencies and increase staff productivity. Employees in administrative roles can pass their repetitive tasks over to their digital colleague, freeing up their time to focus on more creative or interesting work that requires soft skills whilst customer service agents can pass standard requests through an AI system leaving them with only the most complex of customer queries to deal with.

Ubiquitous customer services

One of the most attractive things about AI-powered customer services for banks is its ubiquity. With virtual customer service agents available 24/7 and through a variety of channels such as live message, telephone or email, it’s a win-win situation for both bank staff and customers. From a customer’s perspective, simple requests such as password resets or international transactions can be performed in an instant and there’s no need to visit the bank or spend an hour in a telephone queue to speak to a human agent.

One of the most attractive things about AI-powered customer services for banks is its ubiquity.

Banks adopting customer-facing AI solutions are in fact seeing increased customer satisfaction rates despite removing the human-to-human contact element. For example, since implementing IPsoft’s AI solution, Amelia, SEB, a leading Nordic bank has been able to avoid 544 hours of escalations to customer support with an average handle time of six minutes. What’s more, Amelia has reached an 85% accuracy in immediate intent recognition which has meant a faster service delivery to customers and soaring customer satisfaction.

24/7 banking support

Unlike human agents, digital assistants can work around the clock, seven days a week with no breaks and without tiring. For modern consumers, particularly young digital natives who expect to be able to manage their finances at any time of the day, integrating AI into a bank’s customer service centre will soon become the norm. Chatbots are already an industry standard, therefore at the very least, banks that don’t continue scaling this technology throughout their business will find themselves at a severe competitive disadvantage, trailing behind the market by delivering an inferior customer service experience.

Go beyond simple chatbots

Digital assistants with cognitive intelligence capabilities represent the next leap in automation for financial institutions. Digital colleagues like Amelia are now able to perform tasks above and beyond mere transactional ones, digitising more complex financial management processes such as wealth management onboarding and mortgage applications. Unlike simple chatbots, digital colleagues are also able to develop their cognitive abilities through an advanced Natural Language Interface (NLI) which can process customer queries asked in hundreds of different ways, including slang. More importantly for the banking industry, they can handle context switching so that when a customer moves quickly from one request to another, the interface is able to process both requests without starting over.

Many banks have already integrated voice capabilities into their finance management solutions. Customers communicate via text or voice to gain quick answers to banking questions, tailored financial advice and can even carry out transactions all from the same channel. Voice-enabled digital assistants can handle payments and transfers, credit card activation, charge disputes and travel alerts for customers at any time, freeing up customer services teams to focus on more complex customer enquiries and giving customers full control and access to their finances. Conversational AI will become more and more widely accepted as banks start to harness the technology to help drive customer engagement and operational efficiencies.

Sophisticated systems can recognise patterns from the sheer amount of data that they are processing. Thanks to these capabilities, businesses can easily find out the most common types of transactions by customers of a certain demographic and can then retarget this group for specific marketing or sales campaigns, helping to drive revenue.

Delivering better insights and improved security

Unlocking key business insights is another key driver motivating banks to invest in AI. Sophisticated systems can recognise patterns from the sheer amount of data that they are processing. Thanks to these capabilities, businesses can easily find out the most common types of transactions by customers of a certain demographic and can then retarget this group for specific marketing or sales campaigns, helping to drive revenue. These real time insights can help business leaders make better, more strategic decisions that are informed through concrete data.

Real-time data mining can also be applied to improve customer security as many AI tools have built-in privacy and security by design. An AI-powered virtual assistant can pick up on irregular payments immediately, flagging potential “phishers” to a human agent for additional authentication. What’s more, advanced machine learning solutions can improve over time so that banks can continue to scale up their services. Virtual assistants like Amelia can go one step further by ‘learning on the job.’ Essentially, when Amelia does not understand a request or query she can pass it on to a human colleague but remains in the conversation to learn how to resolve the issue next time.

The future of retail banking

The financial services industry has long been at the forefront of technological innovation. Whilst many businesses are still debating whether to invest in AI, major banks are very much leading the way to invest in the technology and are thriving as a result. As virtual assistants become increasingly more intelligent and their cognitive abilities develop, the expectations for banks and the services they offer will be elevated. Banks that rest on their laurels and refuse to acknowledge this risk falling behind permanently, particularly with the slew of challenger fintech companies that are appearing on the market, offering dynamic and tailored financial services at a lower price.

Using Google and O*NET data from the past 10 years for typical finance roles, Reed Finance developed the interactive online tool on stateofskills.reedglobal.com. It found that written and verbal communication is prized by employers of finance professionals, with ‘oral comprehension’ (an understanding of what people are trying to say) and ‘written comprehension’ (understanding written ideas and information) ranked as the most valued skills. This is in comparison to traditionally assumed skills such as ‘economics and accounting’ and ‘deductive reasoning’ which are ranked as the fourth and 10^th most important.

Reed Finance suggests that this is due to the future strategies of companies wishing to see finance executives take on leadership roles which entail not only technical soundness, but also an ability to inspire and work as a leader of teams – with ‘active listening’ and ‘oral comprehension’ some of the most important skills for a CFO to have.

Firms value ‘human skills’ such as communication over technical accounting skillset.

As such, ‘human’ skills are prominent in successful candidates for roles such as management accounting and FP&A management. This may suggest that these workers have the skillset to take upon more senior roles.

Securing the right talent

Reed Finance found that the level of interest from candidates for the majority of roles in accountancy and finance had been consistent over the past decade, but there are some notable exceptions.

Interest in CFOs peaked in April 2013, higher by 111% in comparison to January 2012. The trend is even starker for finance business partners. From only modest interest in October 2009 popularity has continued to increase rapidly over the decade hitting a peak in July 2018 that is almost 2500% higher. The stark rise reflects a change in the industry towards finance professionals with strong communication skills informing and guiding the business.

Interest in finance business partners has increased from near non-existence in October 2009 by 2333% to a peak in July 2018.

Rob Russell, director at Reed Finance, says: “Businesses are in direct competition for employees that can bring ‘human’ skills to the table, not just technical accounting and number crunching. The influx of AI in the workplace is helping to enhance the numerical skillsets within these teams, so there will be greater time for high-level creativity. Companies want candidates that can communicate, secure business wins and manage teams so that they perform to the best of their ability. These changes to a more fluid, creative workplace are creating great opportunities for those within the finance sector.”

Software use is essential to success but becomes less important with greater seniority

The research conducted also investigated the tools that must be mastered for success in these roles, encouraging businesses to upgrade their software where necessary.

Rob Russell continues: “Every day working with businesses we find that tech is there to enhance the performance of individuals. While candidates should endeavour to keep up with the latest accounting tools on the market, businesses are increasingly looking for those that can win new business and demonstrate a return on investment.

“For candidates, developing the ability to take complex finance information they deal with on a daily basis and using it to answer the question, ‘what does this mean for the business?’ will set them aside from colleagues. This, coupled with commercial nous, has always been an advantage, but now it seems it is even more sought after as business leaders search for the candidates that can secure the future of their business.”

(Source: www.reedglobal.com/finance)

Headlines have raised fears in recent months that robots threaten many of our livelihoods. However, Jan Hoffmeister from Drooms says that those in the private equity (PE) industry should instead be encouraged by how Artificial Intelligence (AI) technology can give them an edge in a competitive marketplace.

AI technology cannot replace human thinking in relation to strategy and business planning, which are fundamental to PE. But it is an impressive tool when it is correctly incorporated into the more process-driven functions of PE firms, increasing the power to collect, process and distribute information to the right parties with much greater speed and accuracy.

The need to stand out is imperative in the highly competitive PE market. Analysis by EY¹ shows that while the industry has made a strong recovery after the crash of 2008, there is also a lot of ‘dry powder’ sitting in the wings because of intense competition for deals.

Total PE commitments globally stood at US$530.7 billion in 2016, which was close to the US$616.7 billion pledged in 2007. However, in 2017, only US$440 billion of transactions took place versus US$748.4 billion in 2007. In terms of dry powder, there was US$525 billion sitting without investments in 2016.

The key issue is that the right investment targets with appropriate valuations are hard to find. Offering a solution to managing the deal-making process helps a PE firm stand out amid intense competition. Using a virtual data room (VDR), which leverages AI technology, makes a firm best in class, whether it is used for a one-off transaction or to create value in assets over their entire life cycles.

Successful PE firms are thorough in their due diligence, nimble and open-minded to pinpoint the right opportunities and disciplined about formulating the right investment philosophies.

There are two key areas in which a VDR is useful for PE firms, particularly if it is used during the ‘hold’ phase of an asset. The first is consistency, in that documents can be updated regularly, giving the vendor full control over data, sourcing investment targets and achieving correct valuations. The second is responsiveness – documents are always ready, so assets can be bought or sold whenever required.

Given that the intention of PE firms is always to sell an asset, it is especially relevant for them to establish a ‘life cycle’ VDR that can be used to manage a company throughout the period of ownership, from purchase, through management and on to divestment.

A VDR connects authorised users, including those inside a company and their external stakeholders, digitally and in a secure environment with real-time access to all relevant documentation.

A VDR always makes documents relevant to a transaction available to authorised parties and helps ensure that they are up-to-date. All data is stored securely online on a server platform and is always accessible to both internal and external parties, depending on their individual permission levels.

Creating a database in which documents can be updated consistently gives asset owners full control and the ability to react to the latest market conditions, bringing assets to market quickly when the conditions are right, sometimes at short notice.

One of the strengths of the Drooms NXG VDR is its Findings Manager function. This improves the vendor due diligence both prior and during the sales process. It allows for the automatic pre-selection of documents and helps in the assessment of potential risks and opportunities within a transaction. This yields greater control, instills confidence in potential buyers and cuts disruption to existing business.

Those PE firms involved in cross-border deals will find the Drooms transactional room particularly useful. It includes a tool that translates documents in real-time, ensuring risk assessments are maintained in a timely fashion throughout the process.

Essential elements

The integrity of documentation is paramount for PE firms. When deals are going through, unclear, incomplete or erroneous documents can cause all manner of problems, including sales falling through. Documentation must provide an accurate assessment of the value of an asset.

For clarity and transparency, a VDR must also have a stringent and standardised index structure for all assets within a portfolio. All an asset’s documentation should be organised in the same manner, allowing quick access to relevant content for the purposes of comparison. Long-term value can be created in assets if they are encapsulated by standardised and sustainable data – and life cycle data rooms are the optimum tool for this purpose.

The practicalities

In practice, careful planning is essential to manage a life cycle VDR successfully. This starts with getting an accurate snapshot of a project’s current progress using key metrics such as available (and missing) documents.

The time frames, processes and the responsibilities of all relevant parties should be defined, and their commitment secured to the proposed solutions, including any changes to management processes.

All the relevant documents must then be collated and, if necessary, digitised before being uploaded to the VDR. Finally, the VDR must be regularly monitored and maintained, updating and adding documents as required.

Most powerful tool in the box

PE firms that wish to manage a market currently characterised by dry powder, high valuation and enhanced competition need to adopt beneficial technologies. A VDR adds value at all the stages of an asset’s lifecycle, including buying, holding and selling, making the whole process much smoother. The value added in terms of making better deals, improving operational efficiency and enhancing the transparency increasingly demanded by stakeholders makes a VDR one of the most powerful tools at a PE firm’s disposal.

¹Source: EY, Global PE Watch, 2017

The Bank of England (BoE) has released its latest data on mortgage lending this morning which reveals that new lending commitments are at their highest level since 2008 Q1.

BoE also reports that first time buyers increased their share of the market to 21.4% in Q2 2018 - a rise of 1.8% against the previous quarter. Despite the surge in lending, the mortgage market continues to be challenged by a combination of fierce competition from traditional and non-traditional players.

With the rise in the lending market, there is an ever-growing need for traditional lenders to offer innovative solutions that provide faster and more efficient end-to-end mortgage resolutions.

In the FCA’s Mortgages Market Interim Report 2018, the need for more customer-facing innovation in the mortgage market is being encouraged for traditional lenders. On average the loan procedure can take approximately 45 days and this can be exasperated if the loan requires additional underwriting.

Most of the time the lenders will underwrite applications manually, which risks inaccurate pre-approval. Traditional lenders are seeking out next generation technology solutions to compete with non-traditional players to better manage the entire mortgage lifecycle.

Across the assessment, valuation, offer and contract completion process, manual data-entry errors can be reduced using Optical Character Recognition technology (OCR) by attaining customer data from key documents automatically. These bots extract applicant’s personal details from know your customer (KYC) documents and automatically review the applicant’s credit history which will speed up the mortgage application lifecycle, thus reducing the probability of manual error.

Puneet Taneja, Head of Operation at Intelenet Global Services, comments: “Buying a property is an important chapter in anyone’s life - dragging out the process creates a great deal of stress, preventing customers from getting their dream home as quickly as possible. Rather than having to wait for days to find out whether an applicant is eligible for a mortgage, automating the checks required across the assessment, valuation, offer and contract completion process takes away the headache away from mortgage brokers so they are able to communicate to customers and give them offers in 30 minutes.

Puneet continues: “Using this AI & Automation based initiative which uses bot technology to gain business intelligence alleviates the pain of mortgage brokers getting applicants data to find out if they are eligible. Digitizing the home-buying process by intelligent reporting & dashboards reduce processing times by 40% and costs by 50%.”

(Source: Intelenet Global Services)

Salvatore LaScala is a Managing Director at Navigant Consulting, where he is Co-Lead of the Global Investigation and Compliance and Anti-money Laundering (AML) Practices. Mr. LaScala has over 20 years experience conducing AML and Sanctions compliance programme reviews, Risk Assessments, Monitorships and Remediations and regularly assists his financial services clients with Navigating regulatory or law enforcement actions. Mr. LaScala also applies his expertise by assisting clients with AML & Sanctions optimisation services that increases the breadth and scope of risk coverage while making the programme more efficient. He oversees Navigant’s AML Technology Team and has helped develop STAR, Navigant’s proprietary Case Management System and Rules engine regularly utilised for AML Look-Backs, Sanctions Look-Backs, CDD Remediations and other compliance and investigative projects. Additionally, Mr. LaScala provides his clients with outsourced Financial Investigation Unit (FIU) teams to both augment existing FIUs on a permanent basis or by providing FIU Surge protection services whereby the Navigant team is deployed to handle an increase in investigative or compliance activity pursuant to a compliance technology transformation or acquisition of another institution or large scale customer on-boarding.

Mr. LaScala began his career as an accountant, attorney and Special Agent with the IRS Criminal Investigations Division of the Treasury Department and thereafter spent over 20 years providing AML compliance and investigative services. He has been with Navigant since 2010.

This month, Finance Monthly had the pleasure to connect with Mr. LaScala and discuss AML in the US and the impact that AI, Machine Learning and Robotics Process Automation have had on the sector.

What drew to the AML field? What excites you about the sector you work within?

My background initially drew me in. As an accountant, attorney and former law enforcement officer, it all came together initially with a consulting job in 1997 with a Big 4 firm specialising in AML and Forensic Accounting. I enjoyed both but spent far more time in AML. I loved developing and dispositioning AML and Sanctions alerts and constantly found ways to make the process more comprehensive and efficient. Eventually I developed ways to make large scale AML remediations, including Look-Backs more efficient by building rules engines, false positive review platforms and custom case management systems. My perspectives as an accountant, attorney and former law enforcement officer helped make these technologies, auditable, regulatorily responsive and feature rich for investigators, respectively. These days I am still excited to be involved because I like working with clients, and because the regulations, financial institutions, and money launderers constantly change. It’s constant learning, which works for me - otherwise I’d be bored.

What is the current state of AML in the US?

This is a very important time for AML compliance - regulators, examiners and law enforcement now know more about AML programmes, compliance technology and payment platforms than ever before, and as such, the stakes for financial institutions regarding compliance become increasingly higher. Financial institutions are quickly adapting and upgrading their technology and overall programmes to maintain compliance and prevent and detect money laundering, terrorist financing and fraud. The ‘bad guys’ however, seem to have far more payment methods and venues at their disposal to commit crimes than ever before in history.

What are some of the key challenges you face on a daily basis and how do you overcome them?

The key challenges include finding innovative and cost effective ways to serve our clients, who are often faced with fines and expensive remediations. Providing the right breadth and depth of services to them in a cost effective way is critical. We also work for financial institutions of all different shapes and sizes, some have been through enforcement actions two or more times and are in a position to better plan their way through those actions with a great appreciation of the effort it takes. Others have either not been through too many regulatory or law enforcement actions, or are unable to communicate to a home office in a foreign country the gravity of a US regulator or law enforcement action, and don’t get the financial support they need to get through it. The challenge in both instances still becomes handling ongoing work or “business as usual work” (BAU) along with regulatory action or some compliance technology transformation. Without consultants helping, there are just not enough hours in the day. Regardless of a financial institution’s capacity to respond to a regulatory action, it’s often best if we get in there early and get them off to a timely start so they don’t also fall behind on BAU, or react to regulators too slowly, which can lead to additional issues.

What are the current AML issues and solutions affecting American businesses?

AML is constantly undergoing transformations. Some of these are based on new and emerging AML and Fraud schemes that the industry has to respond to, other transformations are due to new regulations, such as NYSDFS Part 504 regulations, which add additional layers of accountability on AML programme owners. Still, other transformations are the result of enhancing the regulations and the technology behind it because every time we close a door on money launderers and fraudsters, they both seek out institutions without robust compliance and find new venues through which to launder money. The US and several other markets are attractive to money launderers, fraudsters and terrorists because the financial services industry is vast and because these markets are segmented. This means that some players in capital markets or money service business spaces are very technologically savvy with respect to compliance, while other smaller players in the same segment are not. In fact, we often see challenges where the larger and more sophisticated financial institutions de-market or close customer/client accounts which later pop up at smaller or less sophisticated financial institutions.

How has the introduction of Artificial Intelligence, Machine Learning and Robotics Process Automation impacted compliance and investigative solutions?

Navigant is highly focused on applying Artificial Intelligence (AI), a form of Machine Learning (ML) and Robotics Process Automation (RPA) to our clients in many different areas, including AML and Sanctions. For AML example, we believe that AI/ ML can help existing AML Transaction Monitoring Systems deliver enhanced detection scenario parameters by grouping behavioural patterning to cover more risk and produce fewer false positives. Concurrently, we are applying RPA to the expedite portions of the dispositions of such alerts by removing mundane rote tasks from the analysts purview so that he/she is spending more time on considering the facts, CDD, news and current transactions to determine whether the transaction should be filed on, and less time hunting for data and writing the disposition. Specifically, AI/ML, which helps increase coverage and reduce false positives, and RPA which provides the Investigator more time to analyse the actionable items, are remarkably powerful together.That said, there is a fair amount of work to do, and in the beginning, we need to focus AI/ML only on matters for which the data feed is clean and comprehensive and apply it in a way that is transparent and can readily be described to regulators, examiners and internal audit. The AI/ML revolution won’t survive if the providers that developed it and the financial institutions that use it are not completely transparent. Moreover, even RPA will be better received if it is introduced in stages and when implementations are accompanied by statistically valid data showing that it is more accurate, and saves time such that the ultimate work product contains more thoughtful analyses and is generating comprehensive filings useful to law enforcement.