In the middle and back offices, the depth and breadth of industry expertise will be a bigger driver of AI innovation than data science
By Tom McMackin, SVP, Marc Zimmerman, SVP, and Scott Kurland, MD, of SS&C
Although AI technology is increasingly being embraced by most industries to drive enhanced operational efficiencies, customer experience and financial performance, the financial services industry was actually one of its earliest pioneers. The ability to predict stock market movements has been the holy grail for institutional investors since the inception of securities exchanges. It is little wonder that this industry segment first began research with predictive analytics as early as the 1950’s and 60’s. A decade later, capital markets began to see the development of the first algorithmic models that were used to accelerate trading decisions. Today, these tools have evolved into the High Frequency Trading (HTF) systems that execute millions of transactions daily.
In very real terms, AI offers the ability to make faster and smarter decisions, translating into billions of dollars a year for financial services institutions. It should come as no surprise then that investment banks and hedge funds have been pouring significant funds into related software technology and research for years.
Investment Operations and Accounting – A New Financial Services Frontier for AI
To date, the major share of the AI spend within capital markets has been squarely focused on enabling front-office trading and customer-facing business functions, while middle- and back-office operations have remained largely unchartered territory. Investment operations and accounting systems have become increasingly sophisticated in their efforts to address the industry’s ever-changing accounting standards and regulatory compliance requirements, but thus far these applications are not ‘smart.’Instead, they are typically legacy solutions driven by hard-coded rules and processes that enable the inflow of structured data from external sources, such as counter-parties, custodians, securities exchanges,and clearing and settlement systems. Unlike front-office trading operations that utilize AI to make more enlightened decisions based on Deep Learning and Big Data analysis, the goal of the middle and back office is to perform accounting, regulatory compliance and other operational tasks with the utmost efficiency and precision.
No “Do-Overs” in the Middle and Back Office
Clearly there are big opportunities to leverage AI in the middle and back-offices. Examples include automating reconciliation processes, reducing the burden of exception management, and enabling faster, more effective remediation of identified errors. However, the middle and back-office calls for a substantially different approach to the use of AI — one that is driven as much by the depth and breadth of expertise in investment operations and accounting as it is by the AI technology itself. In the front office, bad decisions one day can be compensated by better decisions the next. Anomalies are expected as part of the asset management and trading process. Not so in the middle and back office, where numbers either add up correctly or they don’t. If they don’t, the exceptions must be quickly identified, reconciled and repaired to avoid undesired downstream consequences with regulators, auditors and stakeholders.
More Sophisticated AI Tools Don’t Always Produce More Sophisticated Results
Today’s most sophisticated, front-office trading models leverage advanced AI tools like Deep Learning with Advanced Neural Networks (ANN) to uncover new patterns, and reach insights and conclusions through interpretation of data – similar to how the human brain functions. Unfortunately, Deep Learning models are not yet an exact science. Like human brains, these tools can draw inaccurate conclusions. In the more precise world of investment accounting, there is little room for opinion — human or machine. Machine learning models must be thoroughly trained and tested to produce very specific and accurate outcomes. They must be designed to identify only appropriate patterns, then suggest or trigger appropriate actions relevant to operations and accounting processes. This takes highly specialized investment operations and accounting expertise, not only with regard to middle-to-back-office functions, but also across a continually expanding landscape of asset types, transactions, markets, regulations and industry operating models.
In the investment accounting space, machine learning can be used to reduce time and cost associated with data inquiries by providing relevant context. Once the machine learning model identifies an issue and where it resides, it can either suggest the proper course of action to resolve it, or autonomously initiate the appropriate workflow through “Intelligent Workflow Automation” (IWA). IWA technology learns from user behavior to identify and automate the appropriate workflow processes needed to locate and resolve the problem without manual intervention.For example, in the investment operations area, reconciling position holdings from custodians can be time consuming if there are differences in the quantities due to out-of-date factors. Pattern recognition algorithms can discover these breaks and resolve them quickly.
It is essential that the behaviors of IWA models are thoroughly scripted and tested by highly experienced and knowledgeable investment operations and accounting experts to ensure that target automations correctly perform the tasks at hand. No matter how sophisticated the models are, they will not produce valid results unless they are guided by specialized investment accounting and operations domain expertise to know what anomalies, parameters and drivers to look for.
Increasing the Value of AI with a Single, Unified Platform
What the financial services industry generally calls “integrated investment operations and accounting systems” are essentially a series of disparate functional applications or modules that are loosely wired together in an effort to more efficiently perform a range of middle-to back-office functions and services. To the extent they are effectively integrated, they endeavor to exchange data and automate hard-coded transactions from beginning to end in a serial sequence commonly referred to as “Straight Through Processing (STP)”. However, here no pattern recognition is involved –it is simply one specific event triggering another specific event with no enhanced intelligence.
Today’s modular investment operations and accounting systems lack the unified architecture needed to exploit the full value of AI. The full potential of machine learning and intelligent workflow can only be realized when an application can holistically recognize patterns and pinpoint exceptions across relevant functions, activities and data anywhere in the system. Only then can the system autonomously initiate the best actions or recommend the most appropriate next steps.
This process, however, is problematic where separate applications or modules have been cobbled together to look, but not really act like one. To truly enjoy the full benefit and value of AI in a middle and back-office investment setting, institutions will need a unified technology platform that provides a single database and user interface together with a rich collection of pre-integrated functions and common services. The platform also needs to be able to support all the diverse assets, transaction types and industry operating models that define an institution’s businesses. Successful solution pioneers in this new space will likely have long and successful track record in the industry, deep expertise in wide range of asset types and industry operating models, and an aggressive mergers and acquisitions strategy to continually deepen and widen that expertise.
Bottom line – AI tools have the potential to bring huge efficiency gains and cost savings to middle- and back-office investment operations, especially when embedded in software applications that singularly support ready access to all required data. However, successful deployment of these technologies also requires deep domain knowledge and expertise on the part of the application provider to truly optimize the capabilities and benefits of this innovative technology.
Investing into a more sustainable future: changing businesses from the inside out
By Shawn Welch, Vice President and General Manager of Hi-Cone Worldwide
As industries across the world are facing unprecedented uncertainty and anticipating the economic implications of the current health crisis, business leaders have the unique opportunity to seize the chance to make lasting, positive changes and re-interpret the business challenges in a positive way – without forgetting or minimising the toll the pandemic has taken. When trying to identify a way forward, the future must be sustainable. We must take this opportunity to find a more sustainable way for businesses and manufacturers to survive.
Environmental and economic concern have only increased the gap on what consumers want – more sustainability – and how much progress businesses can make without risking their viability. However, rather than giving up on ambitious goals, maybe we need to reframe the way we look at sustainability. So far, businesses have tended to react to consumer demands, often without looking into the long-term implications and research-based due diligence one would expect. Therefore, now is the right time to be more deliberate: to continue on the path towards a truly sustainable ‘new normal’, businesses need to consider the bottom line impact more than ever before and truly invest in changing their business models to become more sustainable.
To meet the UN’s ambitious 2030 Sustainable Development Goals, businesses ultimately must thrive – working towards establishing a circular economy remains crucial. Instead of a linear ‘extract, use, dispose’ approach, materials need to be respected and re-used as many times as possible, which is only possible if products are designed for re-use, re-manufacturing, repair or restarting. After all, any and all consumption comes at a price. In manufacturing, processes draw on resources to produce items that, once they have served their purpose, become surplus to requirements. Yet, to ignore this is to take an incomplete view of sustainability: instead, materials are extracted from waste to re-enter production processes. Reuse and recycling initiatives are central to this and great strides have been made in raising awareness of this need. The full environmental cost of production and consumption includes the choice of materials themselves but also the level of carbon emissions generated, and energy consumed.
Once products and processes have redesigned for a circular approach, this initial investment will often easily be recouped, especially if we start with looking at the facts when starting this crucial process. To make the Circular Economy a focus for any business very often means changing the business model. Here, investing in research and development is vital. In the packaging industry, for example, we are seeing that customers and consumers are increasingly more focused on sustainability, and that surprising changes can unlock societal and business value. Through minimising a product’s carbon footprint or making recycling easier for consumers, lifecycle-assessment-based product redesigns or using recycled plastics instead of larger quantities of cardboard, companies are identifying these more creative options and enjoying the long-lasting benefits that come with implementing them. In any case, leadership is key. A research-driven approach gets everyone on-board and seeing management committing to these goals as part of business plans helps cement these. At a recent Reuters Responsible Business Summit virtual panel, I was part of an interesting conversation. Here, Yolanda Malone, Vice President Global R&D Snacks PKG, PepsiCo, discussed how leaders have to drive the behaviours within the organisation and the tone for the culture. She explained that her sustainable plastics vision is a world where plastics never become waste. Only through putting the mantra of “reduce, recycle, rethink and reinvent” can we bring circular products to consumer. She stressed that, if we don’t reinvent, we will fall back into old habits.
Of course, consumer behaviours play a part and the easier the solution, the more likely consumers will get behind it. End consumers are becoming increasingly conscious of packaging. So, to be truly circular, we need to take into account the entire lifecycle. Mindset change needs to continue to happen. Consumers need to be clear about what their choices are. To achieve this, we must change our businesses from the inside out, allowing for close collaboration inside and outside of our organisations. Other organisations – such as governments and recycling organisations – will need to be involved in businesses’ efforts, multiplying the impact our investments will have. We must address all aspects of sustainability and, for example, have better recycling, a focus on infrastructure and emphasis on consumer education. To recover, reuse and recycle, the R&D must be in place and dedicated to sustainability. Partnerships are important as we, as other leading global companies realise, cannot do this alone. Collaboration is key when investing in a more sustainable, more Circular, future.
Securing Information Throughout the Supply Chain – Preventing Supplier Vulnerabilities
By Adam Strange, Data Classification Specialist, HelpSystems
The financial services sector is experiencing extreme disruption coupled with rapid innovation as established institutions strive to become more agile and meet evolving customer demand. At the same time, new market entrants compete fiercely for customers. Increasing operational flexibility, through the deployment of cloud infrastructure or via digital transformation initiatives, is critical for future competitiveness but it has also driven regulatory and security challenges, particularly around working with suppliers.
That said, the benefits of a diverse, interconnected supply chain are compelling: agility, speed, and cost reduction all weigh on the positive side of the equation, prompting financial institutions to pursue close, collaborative relationships with suppliers, often numbering in the hundreds or thousands.
Weakness in the supply chain
On the negative side is the increased cyber threat when enterprises expose their networks to their supply chain. In our modern interconnected digital ecosystems, most financial organisations have many supply chain dependencies and it only takes one of these to have cybersecurity vulnerabilities to bring a business to its knees.
As a result, breaches originating in third parties are common and costly – a Ponemon Institute/IBM study found that breaches being caused by a third party was the top factor that amplified the cost of a breach, adding an average of $370,000 to the breach cost.
Concern around the supply chain was also evidenced in a recent report we have just issued, whereby we interviewed 250 CISOs and CIOs from financial institutions about the cybersecurity challenges they face and nearly half (46%) said that cybersecurity weaknesses in the supply chain had the biggest potential to cause the most damage in the next 12 months.
But sharing information with suppliers is essential for the supply chain to function. Most financial services organisations go to great lengths to secure intellectual property, personally identifiable information (PII) and other sensitive data internally, yet when this information is shared across the supply chain, does it get the same robust attention?
Further amplified by COVID-19
Financial service organisations have always been a key target for cyber attacks. Our research showed that since COVID-19 hit, the risk has elevated further, with 45% of the respondents seeing increased cybersecurity attacks during this period. Likewise, hackers are rejecting frontal assaults on well-defended walls in favour of infiltrating networks via vulnerabilities in suppliers.
But financial services organisations must maintain reputations and ensure customer trust. Firms are keen to demonstrate that they are protecting customer assets, providing an ultra-reliable service and working with trustworthy partners. So, what can they do to better protect their supplier ecosystem?
At the very least, they need to ensure basic controls are implemented around their suppliers’ IT infrastructure. For example, they must ensure suppliers maintain a secure infrastructure with a minimum of Cyber Essentials or the equivalent US CIS certification controls. Cyber Essentials defines a set of controls which, when implemented, provide organisations with basic protection from the most prevalent forms of threats, focusing on threats which require low levels of attacker skill, and which are widely available online.
Likewise, they need to ensure good information management controls are in place and this begins with accurate information/data classification. After all, how can you apply appropriate controls to your information unless you know what it is and where it is?
How ISO27001 helps organisations put in place a data classification process
The international standard on information security, ISO27001, describes the basic ingredients for data classification to ensure the data receives the appropriate level of protection in accordance with its importance to the organisation. It comprises three basic elements:
- Classification of data – in terms of legal requirements, value, criticality and sensitivity to unauthorised disclosure or modification.
- Labelling of data – an appropriate set of procedures for information labelling should be developed and implemented in accordance with the organisation’s information classification scheme.
- Handling of assets – procedures for the handling of assets developed and implemented in accordance with the organisation’s information classification scheme.
Adoption of this methodology will help financial services organisations and their supply chain take a more data-centric information security approach. However, there are essentially four key stages for implementing a data risk assurance supply chain approach and these are:
1. Approval – in organisations with complex supply chains senior management, vendor management, procurement and information security will all need to support a robust risk-based information management approach. Details of previous incidents and their impact alongside the business benefits will be essential to gain stakeholder buy in.
2. Preparation – Organisations should start with Tier 1 suppliers and initially identify the contracts with the highest business impact/risk. They should identify and record information repositories and the data that they contain together with the responsible business owners. Define a business taxonomy based on information categories of that data and include supply chain factors such as what information categories are shared.
For example, they need to understand the business impact of compromise against each of the information categories. Have any suppliers suffered security incidents? What assurance mechanisms are in place? Once all this information is collated the organisation can create a data classification policy and define a set of controls for each data category.
3. Discovery – Select each data category and identify the associated contracts. Then prioritise the data category based on the risk assessment and verify that the data security controls and arrangements for each data category and contract meet the overall requirements. Once complete, hand over the contract for inclusion in the vendor management cycle.
4. Embed process – the overall objective is to embed information risk management into the procurement lifecycle from start to finish. Therefore, whenever a new contract is created there are a number of actions required which embed data risk at each stage of the bid, tender, procurement, evaluation, implementation and termination phases of the contract.
To summarise, organisations should start by researching the information risk and security frameworks such as ISO27001 and others. They should then focus on defining their business taxonomy and data categories together with the business impact of compromise to help develop a data classification scheme. Finally, they should implement the data classification scheme and embed data risk management into the procurement lifecycle processes from start to finish. By effectively embedding data risk management and categorisation into their procurement and vendor management processes, they are preventing their suppliers’ vulnerabilities becoming their own and are more effectively securing data in the supply chain.
Deloitte: Middle East organizations need to rethink their workforce in the wake of COVID-19
Organizations in the Middle East have had to take immediate actions in reaction to the COVID-19 pandemic, such as shifting to remote and virtual work, implementing new ways of working and redirecting the workforce on critical activities. According to Deloitte’s 10th annual 2020 Middle East Human Capital Trends report, “The social enterprise at work: Paradox as a path forward,” organizations now need to think about how to sustain these actions by embedding them into their organizational culture.
“COVID-19 has created a clarifying moment for work and the workforce. Organizations that expand their focus on worker well-being, from programs adjacent to work to designing well-being into the work itself, will help their workers not only feel their best but perform at their best. Doing so will strengthen the tie between well-being and organizational outcomes, drive meaningful work, and foster a greater sense of belonging overall,” said Ghassan Turqieh, Consulting Partner, Human Capital, Deloitte Middle East.
According to the Deloitte report, many organizations in the Middle East made quick arrangements to engage with employees in the wake of the pandemic through frequent communications, multiple webinars where senior leaders addressed employee concerns, virtual employee events, manager check-ins, periodic calls and other targeted interactions with the workforce.
The report also discussed how UAE and KSA governments have reexamined work policies and practices, amended regulations and introduced COVID-19 initiatives to support companies and the workforce in the public and private sectors. Flexible and remote working, team-building and engagement activities, well-ness programs, recognition awards and modern workspaces are among the many things that are now adding to the employee experience.
Key findings from the Deloitte global report include:
- Only 17% of respondents are making significant investments in reskilling to support their AI strategy with only 12% using AI primarily to replace workers;
- 27% of respondents have clear policies and practices to manage the ethical challenges resulting from the future of work despite 85% of respondents saying the future of work raises ethical challenges;
- Three-quarters of leaders are expecting to source new skills and capabilities through reskilling, but only 45% are rewarding workers for the development of new skills; and
- Only 45% of respondents are prepared or very prepared to take advantage of the alternative workforce to access key capabilities despite gig workers being likely to comprise 43% of the U.S. workforce this year according to the Bureau of Labor Statistics.
“Worker well-being is a top priority today, and similarly to the rest of the world, companies in the Middle East are focusing their efforts to redesign work around well-being by understanding workforce well-being needs,” said Rania Abu Shukur, Director, Human Capital, Consulting, Deloitte Middle East.
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