In Digitisation & Digital Epoch - What does the future of risk look like

Overview

Increasing use of technology and digitization across industry spectrum is giving rise to newer and complex issues. Addressing such risks associated with this paradigm shift and digital transformation will help organizations to manage the emerging risks and derive more value from the digital journey.

Inception of new risks and the transformation of existing risks:

We’re witnessing monstrous investment in digital transformation across industries. The spending is driven by a rapid expansion of advanced technology and a and an anxiety toward interruption by tech-empowered contenders

Numerous organizations have rushed to not only update their technology infrastructures but also transform their operating models, customer engagement models, and even fundamental business models.

Organizations recognise that digital transformation may help them seize new development possibilities while avoiding disruption. These same firms quickly discover that developing technologies introduce new dangers that they haven't faced before, as well as increasing the complexity of current hazards. The linked nature of these threats necessitates addressing them all at once rather than separately.

With this in mind, it's important to understand how far we've come, where we are, and where we're heading. In this article, we will examine Seven major risks that are currently laying the groundwork for the next decade of technological innovation.

Following Six we see key trends shaping risk in the digital era:

1.??Dealing with the artificial intelligence

This article is one of five trends outlined in Digitisation & Digital Epoch - What does the future of risk look like.

Artificial intelligence approaches and solutions are now being used by businesses for a variety of purposes, including medical diagnosis, detecting fraudulent transactions, robotic assistance in manufacturing, contactless shopping, job candidate selection and so much more.

These applications often operate like “secret elements” for decision making. If they produce results without explanation, they make detection of inappropriate decisions difficult. This exposes the organization to vulnerabilities, such as biased data, unsuitable modelling techniques, and incorrect decision making, in the algorithm lifecycle.

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Near-term worries about AI include privacy, bias, inequality, safety, and security. The majority of contemporary AI systems are 'narrow' applications, which are designed to solve a specific problem in a single area, such as a data filtration?task. Without major reform, such approaches will be unable to adapt to new or broader difficulties. While it may outperform humans in one domain, it does not outperform humans in others. However, the development of artificial intelligence that can learn and adapt to a wide range of obstacles has long been a goal in the area.

Organizations should seek openness and accountability in how algorithms make decisions; examine ethics, justice, and safety when using algorithms; and develop innovative techniques to successfully manage the novel risks brought by complex AI algorithms.

What does this imply for businesses?

• The programme, no matter how brilliant it is, lacks imagination. In actuality, an AI computer possesses the same creative abilities as its creator. It does not grow more creative as it learns. As a result, it's difficult to assign activities that need imagination to a computer programme.
• Programs, like humans, can make mistakes, and how they're programmed can have a big impact on this. They rarely see them in time, unlike humans. This means that it's still necessary to double-check an AI's output to ensure that no errors have been committed.
• Delays in proper redress of business issues in the absence of clear accountability guidelines for managing malfunctioning algorithm-dependent systems.
• As previously stated, programmes may have flaws. This could jeopardise the security of data entrusted to AI, thus it's critical to pay close attention to the software's security.
• Traditional risk management techniques, such as IT general controls and internal audits, may overlook algorithmic concerns, resulting in vulnerabilities.

What can businesses do to respond?

• Without good data, AI is useless. Have the proper controls and governance systems in place for inputs and data set selection.
• Implement standardised disclosure methods to notify important stakeholders when algorithms are used to make choices that affect them. Clear set of guidelines should be available for how AI models are created.
• AI model outputs continually reviewed to ensure accuracy and alignment with the model’s initial business purpose.
• Conduct independent audits or validation of algorithms on a regular basis using established baseline parameters to check the validity of the training data, assess model security, and improve model performance.
• Controls around logical security, programme change, computer operations, and programme development must be in place for technology assets supporting AI systems.
• To address algorithmic risks, collaborate with researchers, think tanks, and innovators to adopt leading techniques and cutting-edge tools.

2.??Advancement of Governance and Risk in Intelligent Automation

Intelligent Automation (IA) is revolutionising how businesses manage everything from finance and accounting to operations and human resources. Basic robotics process automation (RPA) and advanced process solutions like artificial intelligence (AI) unlock the ability to accomplish things quicker, better, and cheaper than before, and these technologies have become very straightforward to buy and install. However, as automation is introduced across different organisational functions subject to higher compliance or operational scrutiny, new risk and governance considerations have emerged, along with widespread adoption and reliance on IA and the pursuit of deeper cognitive capabilities — especially as automation is introduced across different organisational functions subject to higher compliance or operational scrutiny.

To fully benefit from automation, businesses must implement a holistic change management strategy that includes business-IT alignment, employee culture, and new controls tailored to the specific risks posed by automation technology.

What does this imply for businesses?

• Hackers may get access to an automated system or obtain significant amounts of confidential data using bots with excessive access and privileges, resulting in increased harm from cyber incidents.
• Bots are capable of completing a dizzying assortment of duties and activities without taking a break. Inconsistent developer skills and training, as well as a lack of change management processes and other controls, are only some of the variables that could lead to an unstable bot environment and a higher bot failure rate.
• Magnified complexity as a result of the fact that different forms of automation necessitate different types of controls, and old controls must be replaced. Controls for humans conducting background checks, for example, could be replaced with software robot (bot) specific controls for exception management and outliers.
• IT security systems are not self-automating. Automation, like anything else, should not be done in a vacuum. Everyone who has an impact on or is associated with data security, including front-line employees, must be involved. Processes must be tailored to the capabilities of the system. During implementation and training, systems rarely fail without some failure to buy into new processes.
• Difficulty reaching the full potential of automation due to an over-emphasis on cost-cutting, typically at the expense of other benefits like consistency, quality, and accuracy.

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What can businesses do to respond?

• When it comes to data security and access, there are a lot of "how" questions to answer. In terms of identification, authentication, and access provisioning, how do you think about bots? What controls, segregation of duties, traceability, and accountability have in place at company. How the company assigns, changes, monitors, and removes access, as well as the systems to which they have access.
• To allay employee worries, speed acceptance, and stimulate the identification of possible use cases for development, improve digital literacy and educate staff on the benefits of automation.
• Create new controls particular to each technology, such as built-in error handling capabilities, alert systems for process breakdowns, and manual exception handling for unexpected conditions, by digitising current controls using analytics and other technologies.
• Redesign the control architecture across enterprises, risk management, and internal audit teams, and test or audit automated processes with technology-enhanced tools.
• Unroll current change management models to account for bots, and improve current IT incident and crisis management procedures to support and triage possible bot-related issues.
• Create a centralised governance strategy to manage the risk of automation by defining where automation can and cannot be used, as well as policies for process design, programming, testing, continuous monitoring and maintenance.

3.??Defending against the ever-changing cyber-threat scenario

For businesses, cyber security has emerged as a major enterprise-wide risk. The nature of cyber-attacks has evolved over time, and the risk associated with it has resulted in significant exposure for businesses in varying amounts.

As a result of the digital transformation journey, cyber risk has moved to the front end of the organisation. Businesses must ensure that their cyber risk exposure is appropriately managed as they become more exposed to new technologies and digital ecosystems.

Cyberattacks have gotten more specialised and focused in recent years, focusing on specific organisations and individuals. The consequences of incidents have caused enormous harm, ranging from financial losses to operational service disruptions to the destruction of shareholder value and trust. The cyber risk landscape is expanding as new types of malware, such as automated phishing tools and crypto mining software, are integrated with developing technology. To protect against the onslaught, businesses must reassess their cybersecurity procedures on a regular basis.

What does this imply for businesses?

• Companies will gain agility, competitiveness, reaction time, and reach as they integrate digital technologies into core business operations. As a result, they will be more vulnerable to security dangers associated with digital business innovation. These dangers will necessitate a more sophisticated response and a portfolio that goes far beyond today's risk and security positions.
• Intelligent malware becomes more difficult to detect as it learns to imitate regular user behaviour in order to avoid detection.
• Integrating digital risk into an organization's overall risk management framework is a preferred method that necessitates organizational-wide initiatives and a cultural transformation.
• More incidents of physical harm, particularly as automated attacks breach or subvert physical systems like home automation systems and even industrial infrastructure.
• Digital risk management has become a need since it has a significant impact on corporate performance if it is not addressed immediately.

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What can businesses do to respond?

• Adoption of digital technologies provides organisations with greater analytical capabilities, allowing them to better understand their customers' behaviour and improve their services accordingly. However, these technologies also introduce associated digital risks, affecting the end customer's digital trust.
• Digital risk management should be a disciplined and structured business tool that aligns strategy, processes, people, technology, and knowledge with the goal of assessing and managing the risks that businesses face.
• Strategic issues such as reskilling and upskilling stakeholders, including internal personnel, investing in IT infrastructure, reinvesting risk management frameworks, and so on should be prioritised by organisations.
• Consumer behaviour has been positively influenced by the ease of use of digital platforms, the reliability of fulfilment, and the ability to effectively manage data processing. However, consumer awareness of the amount of personal information collected by organisations and their sensitivity to sharing personal data on digital platforms has indicated a greater need for organisations to manage digital risks.
• It should be a holistic, integrated, future-focused, and process-oriented approach that assists a company in managing important business risks and opportunities with the goal of increasing overall shareholder value.
• Digital transformation and digital risk management investments should be tracked on a regular basis, and spending should be changed as needed to achieve digital transformation and manage digital risks.
• Because these technologies are so diverse and are always evolving, businesses should have a system in place to assist them identify who poses a danger, how an attack might be launched, where their technological weaknesses are, and how they would respond to an attack.
• Any organization's team managing digital risk should keep an eye on emerging risks as a problem that has the potential to be substantial, and constantly upgrading their cyber architecture to stay up with the changing digital environment.
• Company should develop a wider perspective and a more inclusive approach since risks are constantly changing.

4.??Managing data to manage risk in the new reality

Data is the currency of today's economy. customers, products, sales, business partners, competitors, and suppliers drive company decisions toward performance and profitability. Quality data is an organization's most valuable asset in a global marketplace where systems, people, and processes are interrelated. However, it poses questions about data use, openness, control, accuracy, ethics, security, reliability, and privacy.

Organizations are re-evaluating established approaches to managing new data risks in order to gain the trust of customers, business partners, regulators, and other stakeholders.

What does this imply for businesses?

• In a data-driven organisation, inaccurate, insufficient, or out-of-date information assets increase the risk of making disappointing decisions, resulting in missed business opportunities, ill-advised acquisitions, poor capital expenditures, and a drop in employee morale and reputation.
• The perceived maturity of privacy compliance and the operational reality frequently differ. Data collected is at risk without strong data governance, and there is no way to detect or handle a potential privacy breach.
• Beyond digital security and personal data breaches, the dangers of increased access and sharing are numerous. They include, for example, the risk of violating contractual and socially agreed-upon data re-use terms, as well as the risk of acting against users' reasonable expectations.
• Organizations are legally required to demonstrate that they have taken all necessary precautions to secure personal data under data protection legislation. Individuals might initiate legal action to demand compensation if their data is compromised, whether intentionally or unintentionally.
• Increased attention on standardisation to control the high costs of processing data due to inefficiencies such as duplication of systems, numerous data standards, inability to commercialise data, and varied data protection techniques.
• Even when individuals and organisations agree on and consent to precise parameters for data sharing and data re-use, such as the reasons for which the data should be re-used, there is a high chance that a third party will use the data differently, whether intentionally or accidentally.

What can businesses do to respond?

• Technical measures must be taken to integrate preventative controls to preserve data, create awareness at all levels of an organisation, and guarantee that a data strategy is flexible to the upcoming privacy problems.
• Organizations should develop solid frameworks to assist minimise the risks associated with data, and then relate these risk mitigation aspects to appropriate executive accountability.
• Digital data, combined with cognitive technologies such as predictive analytics, is a powerful tool for gaining a better understanding of business opportunities and risks.
• Implement real-time transaction monitoring of critical company performance and risk indicators - prevention rather than detection
• Ensure regulatory compliance by providing well-managed and timely data and reporting. This is especially critical in light of certain regulatory obligations.
• Examine the underlying data to ensure that a system or process is working properly.
• Find out what causes needless costs, income leaks, and inefficiencies.

5.??How to Lead a Digital Transformation: Culture Plays a Big Role

Digital technology's rapid progress has profoundly altered the competitive dynamics of industries. Organizations must alter their companies to cope with an increasingly uncertain environment and to fully use the potential provided by new technologies. Despite the fact that digital transformation programmes are common across industries, they frequently fail because to inert corporate cultures that inhibit change.

To fully leverage the benefits of new digital technologies, the implementation of IT needs to be accompanied by transformation. Otherwise, the benefits from IT deployment remain marginal if only superimposed on existing organizational conditions. As a result, digital transformation encompasses more than just the use of digital technologies to digitalize products and services. Holistic changes are essential to support company improvements. Firms must digitalize and restructure their whole business models, as well as the underlying organisational circumstances such as structures, processes, and culture. Cultural change is seen as critical for successful corporate transition, particularly when dealing with disruptive technological transformations. Digital transformation requires the overhaul of culture beyond technology organizational updates or process redesign in order to reap the anticipated benefits.

What does this imply for businesses?

• You could have the most sophisticated digital strategy in the world, but unless your workforce is dedicated to supporting it, your effort will be wasted.
• Unprecedented levels of transparency into business decision-making and common culture via social media platforms and public forums have negative reputational effects.
• If your digital transformation is misaligned with your culture, you could experience slow user adoption and loss of productivity.
• Improved worker skills are needed to build a culture where technology and humans complement each other, which includes knowing how to work past machine limits and biases.

What can businesses do to respond?

• Determine which important behaviours can have the most impact on the organisation. Taking a methodical approach to changing culture is a beneficial activity because it allows leadership teams to gain clarity on the precise culture attributes they want for their company.
• To monitor employee engagement and connect with digital culture transformation projects, Holding mini town halls or having lunch with a few employees at a time, rather than sending out large emails, might be a more effective means of communicating and demonstrating new important behaviours. Alternatively, employing more "digital" communication platforms like Whatsapp may prove to be more effective at engaging a diverse workforce.
• Locate the unofficial leaders who can assist in bringing the cultural transformation to fruition. Informal leaders, who have the ability to influence people without a formal title or authority, are crucial in sowing change, particularly at the front lines. This is generally accomplished by having conversations with their co-workers to assist them comprehend the change from the ground up and what it means for them.
• Refresh organisational core values to include desirable behaviours like smart risk-taking, teamwork, and continuous learning that supports digital transformation, as well as performance measurements and reward structures that are consistent with digital culture goals.
• Closing the Employee-Leadership Gap uncovers a significant perception gap between the senior leadership and employees on the existence of a digital culture within organizations.

Summary

A significant turning point for the digital transformation will be 2023. The fundamental digital themes that will drive the upcoming decade of innovation are examined in this article.