Clearing the Air: The Importance of Explainable AI in Capital Markets
Source: Finance Derivative
By its very nature, the investment management industry relies heavily on analysis to make good decisions. However, investment managers, like most people, will also use their past experiences as mental shortcuts to help simplify complex decisions – but this can lead to cognitive biases. That’s why “perfect rationality” will always be just out of reach for us as humans. Our very nature means that being truly objective at all times is impossible.
As such, AI and machine learning (AI-ML) can be valuable tools in enhancing human decision-making by overcoming biases with predictive analytics. Furthermore, due to the speed of these technologies, we can make decisions more quickly, generating cost and time savings. In fact, according to Accenture research, AI solutions will add more than $1 billion in value to the financial services industry by 2035.
Unfortunately, many investment management firms still hesitate to implement anything more than the simplest AI tools in 2023. One of the driving reasons behind this is the lack of “explainability” behind AI models and output. Humans find it difficult to fully understand or buy into the decisions and predictions made by AI, because they do not fully understand the inputs and framework. If businesses cannot trust AI, they cannot reap the rewards of improving efficiency, accuracy and reducing workloads. It’s time to turn that around.
The reins holding us back
Many firms have long been using statistical models to support decision-making. With the exponential growth in data, including cheap storage and low-cost computing, AI-based techniques have become popular as a way to deliver actionable results for businesses. Despite reservations about the potential of this technology, the consensus is that AI for capital markets can improve how firms operate their businesses. Indeed, banking as whole will be one of the two industries that will spend the most on AI solutions by 2025, according to IDC.
The problem is that organisations often invest in AI programs without achieving buy-in from internal stakeholders, which reduces their potential benefits. In short, people don’t trust what they don’t understand.
We can see this trend from the fact that simpler applications of AI, such as basic regression models have gained traction in the industry in recent years due to them being comparatively easy to understand. However, other models, such as Deep Neutral Networks, that use unstructured data to formulate their decisions – for example, on whether a transaction is fraudulent – are more complex and harder to track. As such, these tools are utilised far less frequently.
This uneven pick up of AI tools is exacerbated by the lack of transparency in some of the features that influence the decisions an AI algorithm makes. To put it another way, it may not always be clear how we get from Point A to Point B – often called the black box effect. This breeds distrust in the tool and if there’s no trust, there’s no buy-in. Crucially, this aversion to advanced technologies can lead to sub-optimal decision-making.
Building trust to get teams on board
Explainability is crucial in building trust in AI tools by transparently showing how an AI or ML model derives outputs from particular inputs. When models are explainable, users and their stakeholders understand them, trust them, and are more likely to use them.
One crucial way to do this is involving end-users in AI model design and establishing mechanisms to fine-tune models. The teams that use AI should work with the teams that build the AI.
Another solution is having measures in place to test the effectiveness of the outputs, such as continuously retraining the model with additional data, to grow confidence in the tool over time. When internal decision-makers fully buy into using AI-ML, they can enhance human intelligence with technology to help overcome cognitive biases that hamper human decision-making.
Reaping the rewards of hybrid intelligence
Making the most of AI-ML models is about enhancing human decisions, not replacing them. The benefits of hybrid intelligence are only unlocked when AI models are embraced side by side with human decision-making in operations, rather than an overreliance on one or the other.
By combining computer-processed data and human insights, firms can drive improved investment decisions, enhance risk management, and ensure better adherence to regulations without being bogged down by human error or bias. According to a recent Deloitte study, financial institutions that use AI in the investment process grow AuM by 8% and raise productivity by 14%. Today’s investment firms cannot afford to miss out on such gains.
In the current capital markets environment, the industry is faced with low margins, high pressure, and increasing competition. Enhancing human decision-making capabilities with advanced AI will be vital for firms to stay competitive.
This is not a landscape where humans will be replaced by machines, but rather human intelligence must be enhanced with machine intelligence to lower operational risk and uncover emerging opportunities. The business benefits of embracing hybrid intelligence will only happen when there’s trust and buy-in in the tools of the trade.
Enhancing cybersecurity in investment firms as new regulations come into force
Source: Finance Derivative
Christian Scott, COO/CISO at Gotham Security, an Abacus Group Company
The alternative investment industry is a prime target for cyber breaches. February’s ransomware attack on global financial software firm ION Group was a warning to the wider sector. Russia-linked LockBit Ransomware-as-a-Service (RaaS) affiliate hackers disrupted trading activities in international markets, with firms forced to fall back on expensive, inefficient, and potentially non-compliant manual reporting methods. Not only do attacks like these put critical business operations under threat, but firms also risk falling foul of regulations if they lack a sufficient incident response plan.
To ensure that firms protect client assets and keep pace with evolving challenges, the Securities and Exchange Commission (SEC) has proposed new cybersecurity requirements for registered advisors and funds. Codifying previous guidance into non-negotiable rules, these requirements will cover every aspect of the security lifecycle and the specific processes a firm implements, encompassing written policies and procedures, transparent governance records, and the timely disclosure of all material cybersecurity incidents to regulators and investors. Failure to comply with the rules could carry significant financial, legal, and national security implications.
The proposed SEC rules are expected to come into force in the coming months, following a notice and comment period. However, businesses should not drag their feet in making the necessary adjustments – the SEC has also introduced an extensive lookback period preceding the implementation of the rules, meaning that organisations should already be proving they are meeting these heightened demands.
For investment firms, regulatory developments such as these will help boost cyber resilience and client confidence in the safety of investments. However, with a clear expectation that firms should be well aligned to the requirements already, many will need to proactively step up their security oversight and strengthen their technologies, policies, end-user education, and incident response procedures. So, how can organisations prepare for enforcement and maintain compliance in a shifting regulatory landscape?
In today’s complex, fast-changing, and interconnected business environment, the alternative investment sector must continually take account of its evolving risk profile. Additionally, as more and more organisations shift towards more distributed and flexible ways of working, traditional protection perimeters are dissolving, rendering firms more vulnerable to cyber-attack.
As such, the new SEC rules provide firms with additional instruction around very specific prescriptive requirements. Organisations need to implement and maintain robust written policies and procedures that closely align with ground-level security issues and industry best practices, such as the NIST Cybersecurity framework. Firms must also be ready to gather and present evidence that proves they are following these watertight policies and procedures on a day-to-day basis. With much less room for ambiguity or assumption, the SEC will scrutinise security policies for detail on how a firm is dealing with cyber risks. Documentation must therefore include comprehensive coverage for business continuity planning and incident response.
As cyber risk management comes increasingly under the spotlight, firms need to ensure it is fully incorporated as a ‘business as usual’ process. This involves the continual tracking and categorisation of evolving vulnerabilities – not just from a technology perspective, but also from an administrative and physical standpoint. Regular risk assessments must include real-time threat and vulnerability management to detect, mitigate, and remediate cybersecurity risks.
Another crucial aspect of the new rules is the need to report any ‘material’ cybersecurity incidents to investors and regulators within a 48-hour timeframe – a small window for busy investment firms. Meeting this tight deadline will require firms to quickly pull data from many different sources, as the SEC will demand to know what happened, how the incident was addressed, and its specific impacts. Teams will need to be assembled well in advance, working together seamlessly to record, process, summarise, and report key information in a squeezed timeframe.
Funds and advisors will also need to provide prospective and current investors with updated disclosures on previously disclosed cybersecurity incidents over the past two fiscal years. With security leaders increasingly being held to account over lack of disclosure, failure to report incidents at board level could even be considered an act of fraud.
Organisations must now take proactive steps to prepare and respond effectively to these upcoming regulatory changes. Cybersecurity policies, incident response, and continuity plans need to be written up and closely aligned with business objectives. These policies and procedures should be backed up with robust evidence that shows organisations are actually following the documentation – firms need to prove it, not just say it. Carefully thought-out policies will also provide the foundation for organisations to evolve their posture as cyber threats escalate and regulatory demands change.
Robust cybersecurity risk assessments and continuous vulnerability management must also be in place. The first stage of mitigating a cyber risk is understanding the threat – and this requires in-depth real-time insights on how the attack surface is changing. Internal and external systems should be regularly scanned, and firms must integrate third-party and vendor risk assessments to identify any potential supply chain weaknesses.
Network and cloud penetration testing is another key tenet of compliance. By imitating how an attacker would exploit a vantage point, organisations can check for any weak spots in their strategy before malicious actors attempt to gain an advantage. Due to the rise of ransomware, phishing, and other sophisticated cyber threats, social engineering testing should be conducted alongside conventional penetration testing to cover every attack vector.
It must also be remembered that security and compliance is the responsibility of every person in the organisation. End-user education is a necessity as regulations evolve, as is multi-layered training exercises. This means bringing in immersive simulations, tabletop exercises and real-world examples of security incidents to inform employees of the potential risks and the role they play in protecting the company.
To successfully navigate the SEC cybersecurity rules – and prepare for future regulatory changes – alternative investment firms must ensure that security is woven into every part of the business. They can do this by establishing robust written policies and adhesion, conducting regular penetration testing and vulnerability scanning, and ensuring the ongoing education and training of employees.
Gearing up for growth amid economic pressure: 10 top tips for maintaining control of IT costs
Source: Finance Derivative
By Dirk Martin, CEO and Founder of Serviceware
Three years on from the pandemic and economic pressure is continuing to mount more than ever. With the ongoing threat of a global recession looming, inflation rising, and supply chain disruption continuing to take its toll, cutting costs and optimizing budgets remains a top priority amongst the c-suite. Amid such turbulence, the Chief Financial Officer (CFO) and Chief Innovation Officer (CIO) stand firmly at the business’s helm, not only to steady the ship but to steer it into safer, more profitable waters. These vital roles have truly been pulled into the spotlight in recent years, with new hurdles and challenges being constantly thrown their way. This spring, for example, experts expect British businesses to face an energy-cost cliff edge as the winter support package set out by the government is replaced.
Whilst purse strings are being drawn ever tighter to overcome these obstacles, there is no denying that the digitalization and innovation spurred on by the pandemic are still gaining momentum. In fact, according to Gartner, four out of five CEOs are increasing digital technology investments to counter current economic pressures. Investing in a digital future, driven by technologies such as the Cloud, Artificial Intelligence (AI), Blockchains and the Internet of Things (IoT), however, comes at a cost and to be able to do so – funds must be released through effective optimization of existing assets.
With that in mind, and with the deluge of cost and vendor data descending on businesses who adopt these technologies, never has it been more important for CIOs and CFOs to have a complete, detailed and transparent view of all IT costs. In doing so, business leaders can not only identify the right investment areas but increase the performance of existing systems and technology to tackle the impact of spiralling running costs.
Follow the below 10 steps to gain a comprehensive, detailed and transparent overview of all IT costs to boost business performance and enable your IT to reach the next level.
1: Develop an extensive IT service and product catalogue
The development of an IT service and product catalogue is the most effective way to kick-start your cost-optimization journey. This catalogue should act as a precise overview of all individual IT services and what they entail to directly link IT service costs to IT service performance and value. By offering a clear set of standards as to what services are available and comprised of, consumers can gain an understanding of the costs and values of the IT services they deploy.
2: Monitor IT costs closely
By mastering the value chain, a concept that aims to visualise the flow of IT costs from its most basic singular units through to realised business units and capabilities, businesses can keep track of where IT costs stem from. With the help of service catalogues, benchmarks, the use of a cost model focussing on digital value in IT Financial Management (ITFM) or what is often referred to as Technology Business Management (TBM) solutions, comprehensive access to this data can be guaranteed, creating a ‘cost-to-service flow’ that identifies and controls the availability of IT costs.
3: Determine IT budget management
Knowledge of IT cost allocation is a vital factor when making informed spending decisions and adjustments to existing budgets. There are, however, different approaches that can be taken to this including – centralized, decentralized and iterative. A centralized approach means that the budget is determined in advance and distributed to operating cost centres and projects in a top-down process, allowing for easy, tight budget allocation. A decentralized approach reverses this process – operating costs are precisely calculated before budgeting and projects are determined. Both approaches come with their own risks, for centralized overlooking projects that offer potential growth opportunities and for decentralized budget demands that might exceed available resources.
The iterative approach tries to unify both methods. Although the most lucrative approach, it also requires the most resources. So, the chosen approach is very much dependent on the available resources, and the enterprise’s structural organization.
4: Defining ‘run’ vs ‘grow’ costs
Before IT budget can be allocated, costs should be split into two distinct categories: running costs (i.e. operating costs) and costs for growing the business (i.e. products or services used to transform or grow the business). Once these categories have been defined, decisions should be made on how the budget should be split between them. A 70% run/30% grow split is fairly typical across most enterprises, but there is no one-size-fits-all approach, and this decision should be centred around the businesses’ overall strategies and end goals.
5: Ensuring investments result in a profit
By carrying out the aforementioned steps, complete transparency can be achieved over which products and services are offered, where IT costs stem from, and where budgets are allocated. From here, organizations can review how much of the IT budget is being used and where costs lead to profits and losses. By maintaining a positive profit margin, the controlling processes can be further optimized. If the profit margin is negative, appropriate, or timely, corrective measures can be initiated.
6: Staying on top of regulation
For a company that operates internationally (E.g. it markets IT products and services abroad), it is extremely important that it stays on top of country-specific compliance and adheres to varying international tax rules. To do so correctly it is necessary to provide correct transfer price documentation. This requires three factors:
- Transparent analysis and calculation of IT services based on the value chain
- Evaluation of the services used and the associated billing processes
- Access to the management of service contracts between providers and consumers as the legal basis for IT services.
7: Stay competitive
Closely linked to the profit mentioned in step five is the question of how to price IT services in order to stay competitive whilst avoiding losses. This begins with benchmark data which can be researched or determined using existing ITFM solutions that can automatically extract them from different – interconnected – databases. From there, a unit cost calculation can be used to define exactly and effectively what individual IT services – and their preliminary products – cost. This allows organizations to easily compare internal unit cost calculations with the benchmarks and competitor prices, before making pricing decisions.
8: Identify and maintain key cost drivers
Another aspect of IT cost control that is streamlined via the comprehensive assessment of the cost-to-service flow is the identification and management of main IT cost drivers. A properly modelled value chain makes it clear which IT services or associated preliminary products and cost centres incur the greatest costs and why. This analysis allows for concise adjustment to expenditure and helps to avoid misunderstandings about cost drivers. Using this as a basis, strategies can be developed to reduce IT costs effectively and determine a better use of expensive resources.
9: Showback/Chargeback IT costs
By controlling IT costs using the value chain, efficient usage-based billing and invoicing of IT services and products can be achieved. If IT costs are visualized transparently, they can easily be assigned to IT customers, therefore increasing the clarity of the billing process, and providing opportunities to analyze the value of IT in more detail. When informing managers and users about their consumption there are two options: either through the ‘showback’ process – highlighting the costs generated and how they are incurred – or through the ‘chargeback’ process, in which costs incurred are sent directly to customers and subcontractors.
10: Analyse supply vs. demand
By following the processes above, transparency regarding IT cost control is further extended and discussions around the value of IT services are made possible across the organization. A more holistic analysis of IT service consumption allows conclusions to be drawn promptly to enable the optimization of supply and demand for IT services in various business areas. This, in turn, will enable a more comprehensive value analysis and optimization of IT service utilization.
Following these 10 cost management steps, a secure, transparent, and sustainable IT cost control environment can be developed, resulting in fully optimized budgets and in turn – significant cost savings. Cost-cutting aside, automating the financial management process in such an environment can boost productivity substantially freeing up time to focus on valuable work, thus leading to overall business growth.
The business and economic landscape is full of uncertainty right now, but business leaders can regain control via cost management, not only to weather current storms but to set themselves up for success beyond today’s turbulence.
Banking on legacy – The risks posed by ‘stone age’ banking infrastructure
Source: Finance Derivative
By Andreas Wuchner, Angel Investor of Venari Security
If you consider the most significant motivating factors behind cyber-attacks – the promise of large financial reward and the opportunity to cause maximum business and social disruption – it’s little wonder that banks and financial institutions are amongst the most inviting targets for would-be cyber criminals. In fact, according to IBM’s recent report, ‘banking and finance’ was the most attacked industry for the five years between 2015 and 2020 – surpassed only by threats to critical infrastructure in recent years. Successful attacks can provide aggressors with a mass of sensitive personal and financial information, and even access to people’s money itself. Furthermore, a suspension of withdrawals and deposits can cause huge social disruption and reputational damage.
As banks have reacted to years of new regulation and emerging technologies, they often operate with a hugely complicated and disparate technology estates. This provides malicious actors with a wealth of potential attack vectors. A small breach from anywhere in this network can have enormous consequences, and lead to entire systems being overrun. As such, it’s crucial that security teams operate with the highest-grade security possible, including ensuring the strongest level of encryption standards. Banks need to look beyond regulatory tick-box commitments and ensure they are taking proactive and preventative steps to monitor and combat malicious attacks across their entire network.
However, the ability to react to cyber-threats across a vast estate requires speed and flexibility to quickly react and update security protocols. The sheer volume of legacy infrastructure slows this process down considerably leaving many security teams in a vicious cycle.
The threat of legacy infrastructure
A sizeable proportion of the banking industry still maintains a reliance on systems first developed more than 40 years ago. In fact, many ‘core banking’ systems, like payments, loans, mortgages and the associated technologies, are still coded using COBOL (Common Business-Orientated Language), an otherwise defunct programming language that is older than the internet itself. In the UK and Europe, COBOL remains the ‘backbone of banking services,’ while in the USA, as much as 43% of banking systems are built on COBOL, meaning it underpins much of our financial system.
This presents a huge security risk. While code has been regularly updated over the years, these systems were built when security threats were far less sophisticated, less well-financed and the burden of data was far less pronounced. For several years, governments have pointed towards legacy systems, built using COBOL, as a major cybersecurity threat, incompatible with modern security best practices and solutions, including multi-factor authentication. For example, data from Kaspersky found that businesses with outdated technology are much more likely to have suffered a data breach (65%) than those who keep their technology updated (29%).
A further security consideration is the diminishing number of people who are trained in maintaining COBOL systems. Every year, experienced professionals exit the industry, making it increasingly difficult to service legacy technologies and creating significant delays in patching threats once they’re identified. This lack of supply of sufficiently trained experts, and the demand they face, makes any updates extremely expensive and time consuming.
Furthermore, legacy infrastructure is preventing the secure application of encryption, posing its own distinct cybersecurity and regulatory risks. Encryption is often heralded as a silver bullet solution for data privacy and has been a continuing area of focus for regulatory bodies in recent years. However, banks remain guilty of poor deployment, maintenance and management of encryption – using outdated protocols and inefficient methods of analysing and understanding network traffic. This, coupled with legacy ‘core banking’ systems that are incompatible with modern encryption techniques, equates to a regulatory and security headache for security teams.
Adopting a new mindset
The risks posed by legacy systems and the volume of cybersecurity threats facing banks, mean a concentrated re-think of overall cybersecurity strategy is needed to prevent breaches and ensure data is protected long-term. Traditionally, banks have taken an ‘outside-in’ view – dedicating capacity, finances and knowledge to dealing with threats that are existing, known and well publicised. However, to aid long-term security, this should be superseded by an ‘inside-out’ proactive approach, whereby security teams are cognisant of their own internal systems and where the key vulnerabilities are found. Once banks have a detailed view of the security risks posed by their legacy systems, and specifically what data is threatened, they can address flaws, update these systems and build a stronger overall security posture.
The secure path ahead
Many of our successful high-street banks today have centuries of experience in dealing with social, economic and regulatory upheaval. However, the rapid development and deployment of technology continues to present a unique challenge. Many ‘traditional’ banks have built a complex technology infrastructure through decades of adjustment to new legislation and emerging technologies. While serviceable in the past, fintech start-ups are pushing the long-term viability of these systems to the limit.
Challenger banks have the luxury of being built from the ground-up, prioritising convenient digital services and features, and modern security processes. As the user base of these banks increase, customers are increasingly expecting these features and security from their existing banks, meaning even more complexity added to legacy infrastructures. As outlined by Deloitte, existing firms simply aren’t positioned to support the rising expectation of the market, exposing banks to additional risk and liability.
What’s more, it’s estimated that banks spend as much as 80% of their yearly IT budgets on the maintenance of legacy systems. While an immediate switch away from these systems is unrealistic, there is an opportunity to reduce wasted spend and divert spend towards modernisation efforts. However, while traditional banks may want to adapt quicker to technological advancements, they need to do so while continuing to minimise cyber risk and without jeopardising the security of their data or systems. This means placing cybersecurity at the heart of any modernisation efforts and maintaining a steady rate of change. As more of the technology estate begins to be modernised, the potential risks of regulatory non-compliance will also reduce.
Legacy systems need a considered update
Banking systems have heavily relied on legacy infrastructure for too long now, bringing difficulties in maintaining the highest-grade cybersecurity and in facilitating innovation. The risks presented by novel cybersecurity attack vectors and competition from new and emerging digital services offered by challenger banks are exacerbating these issues. As such, legacy systems need a managed modernisation in the long-term, facilitated in part by a managed redistribution of existing IT spend. However, to ensure long-term security overall, cybersecurity needs to be central to be at the very heart of modernisation efforts.