4 steps to improve risk management

Risk management is a broad and overarching term. It reaches to and beyond finance, touching every aspect of an enterprise’s operations. Especially for enterprises, the intermingling of all risk-related activities across an organization is important not only to understand, but to build management strategies around. 

This methodology is known as enterprise risk management (ERM):

“ERM is a process, effected by an entity’s board of directors, management and other personnel, applied in strategy setting and across the enterprise, designed to identify potential events that may affect the entity, and manage risk to be within its risk appetite, to provide reasonable assurance regarding the achievement of entity objectives.”

Therefore, a holistic approach to risk management is considered to be the standard for risk officers and other members of the executive team. 

In this article, we’re listing five ways that businesses can improve their financial reporting and controls risk by creating a plan of action to integrate into their larger ERM processes.

1. Understand the breadth and importance of risk management

As mentioned, risk management is an umbrella term that essentially identifies potential and actual risk and empowers a business with the necessary tools to adequately identify and deal with potential risks such as fraud, material misstatement, and more. 

Fraud is a major challenge for most enterprises. COVID-19 proved this to be extraordinarily true. A survey carried out by LIMRA showed that 42% of its respondents had already experienced increases in attempted fraud since the pandemic began. 

As noted by the Corporate Finance Institute, assessment and management of risks is the best way to prepare any enterprise for circumstances that may get in the way of progress and growth. When a business evaluates its plan for handling potential threats and then develops those structures to address them, it will inevitably create risk tolerant processes that future-proof the organization. An in-depth risk management plan is also a sign to investors and higher-level stakeholders of the stability of your organization. 

In addition, progressive risk management ensures risks of a high priority are dealt with as aggressively as possible. Management will thus have the necessary information that they can use to make informed decisions and ensure that the business remains profitable which, believe it or not, is also important to stakeholders.

2. Decide how to manage risk

There are many ways to manage financial risk, and they can be best summarized using the 4Ts model; transfer, treat, terminate and tolerate.

Risk transfer means to assign an individual, group, or third party to be responsible for the risk. This method absolves the transferer of the risk implications, while compensating the person or entity receiving the risk for taking it on. More often than not, transferring risk simply means getting insurance; for example, an enterprise may work with a commercial insurance entity to offload potential financial risk for themselves, their stakeholders, and investors.

Treating risk is the next layer to consider in a case of financial risk in cases where the risk cannot be offloaded through insurance or other means. This is done by performing actions that reduce the likelihood of the risk occurring or minimizing its impact before it inevitably occurs. The best way to treat risk is to ensure that your team is equipped to predict and handle these risks as they come up. Training your team is vital.

The next method to manage risk is through terminating. Just like with treating risk, terminating risk is achieved by altering processes or practices to eliminate the risk completely. This could mean removing the process or area that is causing actual or potential risk to occur, as well. 

The final category is tolerating risk. This step is part of the overall risk management process, as organizations determine the level of risk that they are willing to accept in any given situation or area. When it comes to finances, an organization must consider the amount of financial loss they are willing to risk to perform any number of activities.

These steps and processes can be applied to risk management in a similar manner. However, the detection and investigation of individual financial risk events is much more specific and technical, requiring the expertise of auditors and accountants.

3. Employ tools, automate risk management

Enterprise risk management tools now go beyond traditional spreadsheet-based software. According to McKinsey & Co., 66% of enterprises were piloting or using automation technology in 2020, with predicted increases to come. 

Here are two key areas companies are exploring in 2021:

Robotic Process Automation (RPA) — This technology provides rules to “bots” which mimic simple, repetitive processes that humans often do. This could mean automating the compilation, download, and circulation of an ERM-related report. However, some other highly popular use-cases are onboarding, third-party screening, due diligence, and compliance monitoring. Upon implementing this technology, businesses report reduction of input errors, less human handling of sensitive information, and faster input and processing for overall time savings. Additionally, Gartner reports that “88% of corporate controllers expect to implement RPA in 2021.”

Risk Discovery Artificial Intelligence (RD AI) — According to research conducted by the Public Company Accounting Oversight Board (PCAOB), one of their biggest concerns as the audit industry develops is “over-auditing” due to lack of understanding of company risks. MindBridge’s RD AI platform finds potential risk across 100% of financial data, and explains these findings in a transparent way. The ensemble AI engine finds potential risks with 10x the effectiveness of rules-based tools, and at over 2000x the speed of manual entry. An ERM framework with deep accuracy, efficiency and effectiveness gains can be enhanced by the 4Ts in the figure below:

 Flow chart depicting the combination of the ERM process and the 4 T's of risk management.
Figure: ERM enhanced by the 4Ts model

 

4. Review risk management processes often

The final and most important way to improve your risk management is to review continuously. Meaning, check in on your risk management processes as often as you can. Set up a schedule of monthly, quarterly, or even yearly reviews. 

Even the strongest risk management processes are at the mercy of ever-changing external and internal factors.

An effective risk management plan will implement an ongoing basis to accommodate these changes, ensuring that it continues to be as effective as possible.

 For example, the Enterprise RIsk Resilient EcoSystem, a framework designed to incorporate the needs of larger organizations, is a testament to the need for an evolving mindset regarding risk management.

Diagram of the Enterprise Risk Resilient EcoSystem from Baker Tilly, speaking to the "modern world" and the need for flexibility in corporate risk management.

According to Jonathan Marks of Baker Tilly, the 8th largest accounting firm in the United States, 

“The Enterprise Risk Resilient EcoSystem is more complete than other published frameworks and is more reflective of the current state of “our modern world” and where we need to focus. Why? Regulators are expecting organizations to be using a data driven audit process and using the results or feedback to continually enhance their compliance program.”

 He continues:

“This means organizations should be strongly considering adding technology like MindBridge to the equation. It also means that if compliance, audit, and the general counsel are not working harmoniously there is a possibility risks will not be properly addressed increasing the likelihood of fraud.”

To learn how you can implement MindBridge into your risk management process, or to learn more about the MindBridge Audit Approach, click here.

For more articles like this one, visit the MindBridge blog

Financial automation: The good, the bad, and the future

Financial automation: The good, the bad, and the future | MindBridge

Well, it’s finally here. According to an article from Forbes Magazine, we have reached the age of automation. From AI and machine learning to financial automation and robotics, we’re officially an automatic civilization. Please, be kind to our new robot co-workers.

Okay seriously, this is important stuff, even if we did all see it coming. Especially when it comes to the ever-expanding world of finance.

In every industry, every business, and every firm, finances and how they are managed are vital to the growth and development of a company. Whether you’re a business owner, CFO, or part of the finance department, the role of automation in the future of finance is vital to your role, growth, and the evolution of your organization.

Financial automation doesn’t just mean automating payroll, although it doesn’t hurt to do that as well. Automating financial processes incorporates much more, including risk assessment, audit, and compliance among many other aspects.

An article from DigitalistMag outlines the capabilities of today’s financial automation services, describing the ability to “gain new insights from existing data to optimize credit decisions and improve financial risk management, automating business processes that previously required manual human intervention, and improving the customer experience.”

Financial management has evolved rapidly since the advent of computational technology. As this technology evolved, financial experts and professionals soon recognized that process standardization and centralization are absolutely necessary to increase the efficiency and effectiveness of modern organizations. As efficiency grew into a central tenant of management processes, financial automation became the next logical step for businesses and organizations.

In 2016, McKinsey estimated that 60% of all occupations have approximately 30% or more capabilities that can be automated with existing technology. Moreover, there has been a significant change in the understanding of what can be automated and what should be automated, which has become increasingly evident due to the unprecedented effect the COVID-19 pandemic has had on work

For businesses looking to hire and outsource their financial processes or professionals who want to simplify and streamline internal processes, it may be time to look at automating them instead. For many, this has already begun, as “CFOs around the world heavily invest in financial automation software as a next step in the evolution to enable enterprise transformation.” 

In this way, financial automation could lead to a complex or fundamental shift in how an organization’s core business is conducted.

Taking the first step toward financial automation can seem daunting. However, with more businesses adopting automation into their day-to-day financial practices, it’s clear to see the power this technology holds.

So, what exactly is financial automation?

What is financial automation?

For us mere mortals, financial automation can be as simple as automatically depositing your paycheck, paying bills, or saving a portion of your income per month. The concept is similar for businesses and corporations, but at a much larger scale, and with a lot more moving parts.

Financial automation is the process of utilizing technology options to complete tasks with minimal human intervention. These tasks would normally be accomplished by employees, which, in theory, frees up time for them to perform more complex tasks. 

According to another automation study from the McKinsey Global Institute’s automation research, current in-use technologies can fully automate 42 percent of finance activities and mostly automate a further 19 percent.

While many still consider financial automation and intelligent software to be on the horizon, organizations have already started to utilize cutting-edge tools and technologies such as advanced analytics, process automation, robo-advisors, and self-learning programs. A lot more is still yet to come as technologies evolve, become more widely available, and are put to innovative uses.

Levels of automation

The initial forms of automation were (and still are) macros and scripts: simple rules-based automation that repeated simple work with highly structured data –  things like general accounting operations, revenue management, and cash disbursement have an over 75% fully automatable ability with already existing technologies.

Robotic process automation (RPA)

RPA is the basis (above macros and scripts) to understand the capabilities of automation. An example of an RPA would be simple software that can perform repetitive tasks quickly with minimal effort, like some of the rote tasks mentioned earlier. 

According to the 2017 McKinsey research (also mentioned earlier), about a third of the opportunity in finance can be captured using basic task-automation technologies such as these.

Artificial intelligence (AI) and intelligent automation (IA)

On the other end of the spectrum is artificial intelligence. Artificial intelligence is theoretically achieved when software is able to make intelligent decisions while still complying with controls using algorithms or machine learning

Machine learning algorithms demonstrate the ability for computers to take in a constant stream of data, analyze that data for patterns and recommend solutions to problems humans can’t even see, proving vastly positive results in improving a company’s financial proficiency.

Once a dream for financial professionals and business owners, this form of financial automation software is becoming a reality, shaking up the way that tasks are performed, and even introducing other aspects such as forecasting into the mix.

Improvements with financial process automation 

The umbrella of finance – from payroll to predictive forecasts can involve menial and repetitive tasks which leave limited time and resources to focus on value-adding activities to grow your organization. When financial process automation is added, it serves as a pivotal support to free up needed resources and time. 

As these technologies can cover more ground and more deeply analyze company financials, many organizations are finding that AI and automation technologies are actively improving their bottom line. According to a survey from the Association of Certified Fraud Examiners via the Harvard Business Review, “organizations lose 5% of their revenue every year due to fraud. The typical fraud case causes a loss of $8,300 per month and lasts a full 14 months before detection. And lack of internal controls contributed to nearly one-third of all fraud cases.”

Risk discovery is just one aspect of financial automation, but a growing one.

As AI, RPA and IA continue to use machine learning to do more and perform more intricate tasks, offering insight into finances, we are seeing how this can be incorporated into an organization’s long-term organizational strategy. MindBridge, for example, has developed AI technology for risk discovery, a complex financial task that incorporates not only transactional analysis, but offers broader insights into financial health and integrity.

Want to learn more about how auditors are using AI?

By automating certain financial processes, “finance professionals can not only provide real-time insights into the current status of the business but, with advanced predictive algorithms, they can look into the future and proactively steer the business.”

Financial automation and its capabilities are excelling at a fast rate. With the help of AI, RPA, and IA, standard automation practices can be enriched beyond simple pre-programmed controls and scripts. From McKinsey & Company once again, AI algorithms can learn from historical datasets and the interactions of the financial professional with the system, thereby improving the matching rates tremendously. In this context, matching rates refer to the ability at which an AI system is able to tag users to certain data sets based on their profile of demonstrated usage. Furthermore, the AI technology allows automatic extraction of unstructured information from documents, such as emails.

Of course, return on investment is always a concern. It can take a lot of time and effort to implement new technologies, and savvy business leaders need to know that the tools and processes they put their money behind will work. 

According to Gartner, “AI augmentation will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally.” Basically, they define this term as the combined work of humans and technology, with the people at the center of the operation.

business value forecast by AI type | Graph
Source: Gartner.

If these forecasts are correct, executives should be clamouring for AI and automation investment. Even a small piece of this pie can level up your office, department, or organization writ large.

What financial process automation could mean for work structure

One of the biggest concerns associated with exploring financial automation and therefore implementing financial automation software is what happens to the employees and the roles formerly associated with those finance objectives. 

There’s no doubt that introducing financial automation will change the roles of many employees and even the manner to which employees are trained or progress toward career objectives. One thing is for sure though, automation will replace low-value, simple, and time-consuming tasks, thereby giving staff the flexibility to expand their roles, and spend more time on value-adding activities to help drive a company’s competitive advantage. 

In an article from PWC on change management, they outline five steps that can help firms adopting financial automation make the transition as smooth as possible:

  • Prepare for human capital risks like you’d prepare for any other risks
  • Help people find their way
  • Create organizational support for success
  • Expect changes to jobs, compensations, and structure
  • Learn new ways to develop your team

To unlock financial automation’s full potential, managers must be willing to re-engineer processes, and redeploy resources to optimize efficiency and output.

Another consideration for anyone looking to adopt automation and AI technology is assurance and verification. This verification work ensures that the technology in place is doing what it’s supposed to do, at the level of work required to meet compliance requirements and quality assurance standards.

Internal teams can “test” automations by utilizing what are known as “Test Frameworks” for applications. Some examples of framework tools come from SmartBear and Selenium. However, it’s a lot of work, and unless you have dedicated developers that can help your team test automation tools, you’re sort of stuck. For many businesses, it’s much easier to work with platforms and tools that have done this testing themselves by utilizing a third party.

A future with financial automation

Although IA and machine-learning algorithms are still considered in their infancy, that doesn’t mean finance leaders should wait for them to mature fully. According to McKinsey, many automation platforms and providers that struggled a decade ago to survive the scrutiny of IT security reviews, are now well established, with the infrastructure, security, and governance to support enterprise programs. “Where a manager once had to wait for an overtasked IT team to configure a bot, today a finance person can often be trained to develop much of the RPA workflow.” The exponential growth in structured data fueled by enterprise resource planning (ERP) systems, combined with the declining cost of computing power, is unlocking new opportunities every day.

MindBridge is a great example of a pioneer in unlocking the expanded capabilities of AI and RPA within the finance sector. With AI-embedded risk discovery, MindBrige can risk-rate 100% of the transactions in general ledger and sub-ledgers to produce an aggregated risk profile of the data that makes up the business’ financial statements, facilitating laser-like focus on the areas that matter.

The future of financial automation seems bright, already beginning to reshape the way in which financial services are performed in organizations large and small. Incorporating AI, RPA, and other forms of automation can seem daunting at first, as there are many tasks and organizational changes that go into implementing new technologies and processes. 

By empowering your finance team with AI co-workers, they reduce the time spent on mundane tasks, enabling your team’s human intelligence to shine operationally. Financial efficiency and accuracy means happy stakeholders, and a growing business. What’s not to love?

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