CFO Futures Magazine Spring 2024

CFO Futures THE AUTONOMOUS FINANCE MAGAZINE

ISSUE 05 / Spring 2024

The vision and value of Microsoft’s Copilot for Finance

AI & Autonomous Finance in Financial Services

An interview with Gurkan Salk, Microsoft General Manager of Copilot for Finance

HSO experts discuss the role of AI and Autonomous Finance in Financial Services

Autonomous Finance: How to manage impacts and adopt changes For Sara Sheehan, founder of Sara Sheehan Consulting, it pays to begin with the end in mind

Cybersecurity in the age of AI

Top findings from the Autonomous Finance Global CFO Benchmark A look at the top themes emerging from Aptitude’s Global Autonomous Finance Benchmark research and what that says about the path to AI-powered Autonomous Finance.

Cybersecurity continues to be a strategic priority for C-suite executives and technology leadership teams

A letter from our CEO Welcome to our newly renamed CFO Futures Magazine!

The name change reflects our excitement about the value AI and Autonomous Finance technologies will bring to global finance functions.

In this issue, I am happy to share the recently released findings from our Autonomous Finance Global CFO Benchmark Report, completed with support from our partners, Microsoft and HSO. Our survey of over 1,700 finance professionals across sectors and regions, has provided a unique snapshot of where organizations stand in their Autonomous Finance journey and their use of AI. Read on for some of the emerging trends, join us at one of our upcoming roadshow events and look for the full report out next month.

Additional articles include an excellent interview with Gurkan Salk, Microsoft General Manager of Copilot for Finance on the vision and value of Microsoft’s latest Copilot launch, a roundtable with HSO experts on the state of the finance function in Financial Services, an interview with Gary Simon, leader of the popular LinkedIn group, The Modern Finance Forum and more.

Happy reading!

Alex Curran CEO, Aptitude Software

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Contents 1.

Top findings from the Autonomous Finance Global CFO Benchmark

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A look at the top themes emerging from Aptitude’s Global Autonomous Finance Benchmark research and what that says about the path to AI-powered Autonomous Finance.

2.

The vision and value of Microsoft’s Copilot for Finance

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An interview with Gurkan Salk, Microsoft General Manager of Copilot for Finance, on the recent launch, the product vision and how it helps drive an Autonomous Finance function.

3.

AI & Autonomous Finance in Financial Services

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A panel of experts from Business Transformation Partner, HSO, discuss the state of finance functions in Financial Services and the role of AI and Autonomous Finance in this traditionally conservative industry.

4.

Autonomous Finance: How to manage impacts and adopt changes

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Change management is at the heart of any finance transformation. For Sara Sheehan, founder of Sara Sheehan Consulting, it pays to begin with the end in mind and understand the complexities of changing behaviors.

5.

Unpacking material weakness trends and implications

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Material weakness can harm organizational reputation and financial performance. We look at current trends in material weaknesses, what’s at stake and what organizations can do to reduce the chances of misstatements.

6.

Cybersecurity in the age of AI

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In 2024, cybersecurity continues to be a strategic priority for C-suite executives and technology leadership teams who must balance security investments with digital transformation.

7.

Five Minutes with...

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Going beyond the business to get to know Gary Simon, founder and Chief Executive of FSN Publishing Limited and leader of the popular LinkedIn group, The Modern Finance Forum.

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Top findings from the Autonomous Finance Global CFO Benchmark

By Sarah Werner

Over the years, technological advances have pushed the finance function forward, moving it from manual, paper-based processes to a function powered by cloud computing, data analysis and increased automation.

These technologies have enabled finance professionals to automate repetitive tasks, improve accuracy and gain deeper insights from data, allowing them to focus more on strategic decision making and adding value to the business.

However, with the maturation of cloud and cognitive computing tools and the adoption of AI in the finance function picking up speed over the last 12 months, a new phase is emerging which has been coined by Gartner as Autonomous Finance.

In a 2022 survey, Gartner found that, while 64% of CFOs believe Autonomous Finance will become a reality by 2028, few are making progress toward it.1 To better understand where CFOs and their teams are in their journey to Autonomous Finance – and if it’s a journey they want to be on – Aptitude, supported by Microsoft and HSO, commissioned third-

party research that surveyed CFOs and finance professionals across the globe. The focus was on understanding current priorities, the role of Autonomous Finance & AI and where finance teams fell along a continuum ranging from traditional to Autonomous Finance.

Through qualitative and quantitative research, several key themes started to emerge.

Defining Autonomous Finance

Research methodology

There are variations of the definition of Autonomous Finance but at Aptitude, we believe an Autonomous Finance function is one where:

We used a third-party to conduct a survey of over 1,700 finance professionals and CFOs across nine geographies and six sectors.

All respondents worked for organizations with revenues greater than £250 million GBP and self-reported as decision makers within their organization.

• Systems are self-learning, selfimproving, efficient and interoperable

10 qualitative interviews with global CFOs were also held to get a deeper understanding of key themes and trends.

• Tasks are optimized and intelligent • An enterprise-wide data platform supports real-time insights, enabling finance to be a strategic and trusted advisor to the business

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Geographies: ANZ, Benelux, Canada, DACH, Hong Kong, US, Scandinavia, Singapore and UK Sectors: Banking, Insurance, Platforms/Tech, Manufacturing, Media, CPG/Retail

https://www.gartner.com/en/finance/topics/autonomous-finance#:~:text=What%20Is%20Autonomous%20Finance%3F,%2D%20and%20back%2Doffice%20operations.

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AI is in place within finance, but there are laggards​ 100% 90% 80% 70% 60%

The US, Hong Kong and Singapore

90%

show the most progress on AI adoption

80%

while Benelux and the UK trail other

70%

geographies.

60%

50%

50%

40%

Global respondents cite lack of

40%

30%

understanding/expertise seen as the main

30%

20%

adoption barrier (38%) followed by data

20%

10%

privacy and security concerns (35%).

AI extensively integrated into various processes AI extensively integrated into various processes AI is used in some specific areas of financial operations AI is used in some specific areas of financial operations

Emerging themes Finance teams want to strategically support the broader organization and see technology as a way forward When asked what they wanted to spend less or more time on, finance professionals reported a desire to spend less time on ad-hoc internal requests, accounting and compliance and more time on strategic planning for their function/organization and data.

One surveyed CFO from a Global Assurance Organization commented, “Autonomous Finance has vast implications for a finance team.

This is a technological opportunity which actually could fundamentally change the landscape of what a finance function looks like. If I were to describe it to someone it would be real-time, touchless accounting.

That means that the finance function becomes an insight and decision-driving function and not an accounting function.”

When it comes to achieving that shift, a strong percentage of those surveyed believe that technology

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G lo ba l

G l U ob a S l

H US K

Si ng ap H or K e

Si ng A ap N or Z e

A C N A Z

A C C A H D

0%

D A BL CH

10%

U K Sc an di n U av K ia Sc an di na B vi L a

0%

100%

AI being explored but not yet implemented AI being explored but not yet implemented AI is not currently used in financial operations AI is not currently used in financial operations

is essential for efficiency and innovation (51%) or helpful (32%) in optimizing financial processes, reporting and opportunities within their organizations. When asked whether they preferred a single stack or best-of-breed approach to procuring financial software, only 25% responded that a single stack technology strategy is their preferred approach.

Finance is still a long way from automating core processes The research also explored where organizations were in automating core processes. The answer is that there is clearly still work to do. The survey data showed that:

Data is a top challenge…and a top opportunity In both the qualitative discussions and quantitative surveys, data came up as both a challenge for organizations and an area in which finance teams saw significant potential.

Data quality and reliability (44%) emerged as the primary obstacle to using financial data and analytics to make strategic decisions, followed by budget constraints for investing in analytics solutions (36%) and skills and training (36%).

• 50% have minimal or no selfservice reporting

During the qualitative portion of the research, one CFO summed up the data challenge stating, “Today, it takes a huge variety of different types of analytics to get at the core drivers, to understand what we need to do and make sure we don’t extract the wrong thing. We have to spend so much time just wrestling the data to the ground to generate these reports.”

• The number one priority for finance teams working toward Autonomous Finance is to ‘Automate process controls, accounting and close’

In addition to seeing data as a top challenge, however, it was also identified as the area where respondents felt their organizations

• 61% are still processing data weekly or monthly • Only 13% have access to real-time data

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would see the greatest ROI in the next 3-5 years when it comes to digital transformation.

CFOs who can create a detailed, real-time data foundation that is accessible to the rest of the business can create a significant strategic advantage for their organization.

AI is in place within finance but there are laggards Globally, 62% of respondents reported that AI is either extensively integrated into various financial processes (17%) or used in some specific areas of financial operations (45%). Digging into the surveyed sectors and regions shows which countries are lagging or leading in AI usage.

For instance, in terms of AI usage, Benelux and the UK trail other surveyed countries with 42% of UK respondents and 30% of Benelux respondents reporting that AI is not currently utilized in Finance, compared to the global average of 16%.

AI leaders include the US and Singapore with 31% of US respondents and 38% of Singaporean respondents reporting that AI is extensively integrated into various financial processes, compared to the global average of 17%.

When it comes to industries, Banking had the highest number of respondents, 75%, report that AI is either extensively integrated into various financial processes or used in some specific areas of financial operations. Insurance had the lowest reported percentage at these two stages at 50%.

The why behind AI In addition to wanting to understand the percentage of finance teams exploring AI, we also wanted to understand the areas in which they saw the most value.

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“

AI leaders include the US and Singapore with 31% of US respondents and 38% of Singaporean respondents reporting that AI is extensively integrated into various financial processes, compared to the global average of 17%.

Topping the list of AI benefits was improved efficiency (52%) followed by better accuracy (44%) and advanced data insights (37%).

What wasn’t top of the list?

Reduction in headcount which was tied for the lowest ranked in the list of nine benefits. Perhaps this indicates that most finance professionals see AI, not as a replacement for humans, but as a partner and copilot.

One interviewed CFO noted “The future of finance functions lies in achieving a higher degree of automation and autonomy, where routing processes are streamlined and decision-making is supported by predictive analytics. However, the human element remains vital for strategic thinking and managing complex business scenarios that require nuanced judgment.”

What do CFOs need to achieve Autonomous Finance?

Autonomous Finance is a strategic and competitive advantage for an organization, freeing finance professionals from low value and manual repetitive tasks and transforming the CFO office into a strategic contributor and business enabler.

that, to achieve it, a CFO needs four foundational elements in place: • A single and accessible view of all business data • A fully interoperable finance technology stack capable of processing large volumes at the pace of business • Advanced AI capabilities to drive insights from data • A finance architecture to automate manual process and the application of accounting policies We believe the combination of Aptitude Fynapse, Dynamics 365 Finance and Supply Chain Management applications, Copilot for Finance and the Azure ecosystem can power Autonomous Finance. This collective proposition delivers a truly unique and differentiated offering in the ERP market.

We’d love to share more details about our research and demonstrate our joint Fynapse and Dynamics 365 solution! Please reach out to book a demo or join us at one of our upcoming Autonomous Finance events.

Aptitude and Microsoft recently released a joint vision for Autonomous Finance and posited

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At-a-glance:

Autonomous Finance Benchmark Results To better understand where CFOs and their teams are in their journey to Autonomous Finance, Aptitude, supported by Microsoft and HSO, commissioned third-party research of over 1,700 finance professionals across sectors and regions. The results show a set of emerging trends and enable finance leaders to benchmark where they are today and identify a path to Autonomous finance.

Finance teams want to strategically support the broader organization and see technology as a way forward Would like to do less:

25%

23%

21%

Ad-hoc internal requests

Accounting

Compliance

44%

39%

35%

83%

Data

Believe that technology is Essential for efficiency and innovation (51%) or helpful (32%) in optimizing financial processes, reporting and opportunities within their organizations.

Would like to do more:

Strategic planning for function

Strategic planning for organization

Finance is still a long way from automating core processes

?

61%

50%

Are still processing data weekly or monthly

Have minimal or no self-service reporting

Only 15% of finance teams reported processing data in real time

36% reported that self-service is limited to IT/finance power users while 14% reported no or extremely limited reporting

People understand the need for finance to become business partners. But they don’t see that happening.

They still see us like messengers, consolidators, converters of data into a specific format. But I have seen more and more CFOs crying out for that finance business partner, to sit at the table and contribute.

Group CFO Multinational Telecommunications Company

Finance sees data as the number 1 challenge...

...and the number one opportunity

What are the primary obstacles you encounter in using financial data and analytics to make strategic decisions?

Rank where you feel the overall organization will see the greatest ROI in the next 3 to 5 years when it comes to digital transformation

44%

36%

36%

Data quality and reliability

Budget constraints for investing in analytics solutions

Skills and training

The why behind AI

1 Data analytics & business intelligence

Topping the list of AI benefits was improved efficiency (52%) followed by better accuracy (44%) and advanced data insights (37%).

Reduction in headcount which was tied for the lowest ranked in the list of nine benefits.

The vision and value of Microsoft’s Copilot for Finance

By Sarah Werner

Gurkan Salk, Microsoft General Manager of Copilot for Finance, and Leigh Pepper, Aptitude’s Chief Product Officer, discuss the recent launch of Microsoft’s Copilot for Finance, the product vision and how it helps drive an Autonomous Finance function.

Name: Gurkan Salk Title: Microsoft General Manager of Copilot for Finance Organization: Microsoft

Name: Leigh Pepper Title: Chief Product Officer Organization: Aptitude Software

Name: Mark Aubin Title: Senior Vice President of Product and Market Engagement Organization: Aptitude Software

Mark Aubin: Gurkan, first off, congratulations on the successful launch of Copilot for Finance.

How did you evaluate and prioritize capabilities and use cases for the initial launch?

Gurkan Salk: Thank you, and that’s a good question, Mark. From a product development perspective, we wanted to prioritize the most impactful use cases first – those that would help finance professionals be much more efficient and productive and get the right insights. We then picked use cases that had the broadest reach – horizontal use cases that most finance professionals use, like data reconciliation.

Traditionally, we would have asked customers what the systems should do. Now, we recognize the need to change that culture and ask, what can the systems do? That has changed our product development cycle. Throughout this whole process we have worked very closely with our early adopter customers, including in our own Microsoft finance department.

Mark Aubin: I was just thinking about how this process represents a shift in product development and product management. It’s no longer just listening to existing customer

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requirements and then designing a solution. Now, you’re actually helping them uncover new requirements because you’re at the forefront of technology. How did you work to shift your product team’s mindset from listening and then figuring out a problem, to finding new answers to problems that people might not be sure they have yet?

Gurkan Salk: Just like we’re shifting the culture of the finance department, our product team also went through a culture shift.

Developing a product that is innovative is very different than developing a product that solves a defined purpose. With that perspective in mind, we ran a lot of ideation workshops. Prior to these workshops, we trained our customers and our internal participants on what generative AI can do today.

Obviously, we did need to put some constraints in place to identify where the technology was too far off, and we needed to push those use cases to the future.

We then brought the teams together and explored what finance professionals spend time on and how we could make their days more efficient and more productive, while making it easier to do their jobs and obtain insights in a timely manner.

Leigh Pepper: It feels like with AI, you can use that analogy that says if you’d asked people how they wanted their mode of transport to evolve in the future, they’d have asked for a faster horse rather than imagining the idea of a car.

I think we’re at that point in product innovation, particularly around Gen AI, where product managers and product professionals are having to do all of those things that you’ve just outlined. They have to look at what the finance user is aiming to achieve as opposed to time and motion reviews of how to incrementally improve the current state. It feels like

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we’re at a stage where we’re going to see a huge leap forward in terms of the automation and optimization that Gen AI and Copilot can deliver.

data from different systems, input that into Copilot for Finance and, in a matter of minutes, get the root cause of why the forecast was missed.

Gurkan Salk: That’s a really good analogy, Leigh, and represents our thinking at Microsoft.

The way we’re identifying and prioritizing these use cases is that we are trying to meet the user in the flow of work. If the user spends most of their time in Excel, which we know finance professionals do, those are the processes that we’re looking to light up in Copilot for Finance.

Mark Aubin: As you’ve been working with your charter customers and internal finance teams, have you seen any tangible benefits?

Gurkan Salk: The initial use cases were around data reconciliation, which is and has been traditionally a very manual and time consuming process. The feedback we received from our treasury team was that accounts receivable reconciliation capabilities have helped them eliminate the time it takes to compare data across sources, saving an average of 20 minutes per account. Based on pilot usage, that translates to an average of 22% cost savings in average handling time.

Mark Aubin: That’s an excellent result, and certainly supports the argument for how AI can increase user productivity. Can you give us some insight into what’s next for Copilot for Finance? A sneak peek into the roadmap perhaps?

Gurkan Salk: One of the next use cases is variance analysis. It’s a process that’s still very timeconsuming for finance professionals.

Think about that process of matching your forecast against your actuals - how do you determine why you missed your forecasts? It requires finance teams to look at market conditions. Is it the recessionary period that impacted the forecast? Is it our sales execution? Is it a product issue? Teams have to go into several financial systems to understand the cause. So, we’re leveraging advanced data analysis feature by Open AI and that data analysis engine to turn that process from hours or days into minutes. Teams can collect all that

Mark Aubin: How does the broader Microsoft ecosystem add value to Copilot? Or conversely, what value does Copilot provide the broader Microsoft ecosystem?

Gurkan Salk: If you think about it, it starts with the very bottom layer, with that large language model and working with partners that provide AI capabilities and lighting them up in Azure as an API so that our customers know that they can trust this API, and that Microsoft will never share customer data externally or add it to these large language models - they know that this is a secure platform that our Copilot offerings are built on.

We then have the platform capabilities like Azure AI Studio and Copilot Studio. Those are the platforms we have developed for our partners and customers to develop their custom GPTs and to build their own Copilot capabilities. Microsoft uses the very same platforms to build our first-party offerings like Copilot for Finance.

Leigh Pepper: At Aptitude, we’re excited about using some of that tooling. We can see how the data that we hold within Fynapse - very rich, very well-structured financial data - can be that jet fuel that enables enterprise accounting clients to use Copilot in their flow of work, as you say, rather than having to leave the application to navigate other systems.

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Gurkan Salk: I think there are a lot of partnership opportunities as we think about these Copilot scenarios that leverage the analytical data that is held in the Fynapse accounting hub and subledger. In those cases, we can leverage Copilot capabilities in Fabric, Power BI and Excel.

Leigh Pepper: Absolutely and I think the partnership with Dynamics 365 and the ability to actually drill back from the data that’s in Dynamics 365 all the way back to the lineage and the source data that sits within the Aptitude Fynapse system provides the opportunity to leverage that richer data set.

Gurkan Salk: That’s exactly right.

I think that fits into our vision of autonomous ERP very well.

Mark Aubin: Leigh, you spoke about the role of the Microsoft ecosystem and the exciting things it can unlock for partners like Aptitude. Can you go a little bit deeper on how Aptitude is aligning our strategy and roadmaps and how we are looking at using solutions such as Copilot for Fynapse across the Aptitude portfolio?

Leigh Pepper: I think one of the things that Gurkan said earlier is that it’s really important that we enable finance professionals to work ‘in their flow’ or, in other words, within the tooling that they’re used to working in, whether that be Dynamics 365, Excel, or something else. If we can manage that data effectively and get it into an interface that users are very familiar with, one that’s in the flow of their work, I think it will help to drive high levels of efficiency for our joint clients.

We’re prototyping use cases using some of the Copilot Studio tooling, which really helps in a number of ways. First, it helps to simplify the implementation of new accounting platforms and ERP systems because we know that this process can be very lengthy and very costly. Using AI to look at the accounting rules,

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calculations and flows that they have in their current system and suggesting what that should look like in the Fynapse platform is a way that we believe can significantly cut down implementation time for clients. As an example, we’ve been using some of the Microsoft tooling in a few proofof-concept projects and we’ve seen the time to implement go from a typical three months down to three days.

The other area, as you mentioned, is around data analysis. We can process the data into the accounting entries that are required in a highly scalable, volumetric way, that is very, very efficient. Then, we can put it into a database that is able to handle lots of different views over that data, allowing a user to apply multi-GAAP analysis and view different balance types off of a single data set. Finally, we can use Power BI and Copilot capabilities to build out some of those AI scenarios. It’s leading to some really good proof of concept insights.

For example, we had a case where we built out some analysis using the last three months of financial data that had come through which showed a big anomaly in one of the offers and

promotions. A simple query over gen AI, using Microsoft Copilot was able to identify a particular issue on a single transaction. Then, because of the interconnectedness of Fynapse and Dynamics 365, instead of that just being at the very aggregated level, we were able to drill all the way back to that source transaction within Fynapse for the user to look at.

This saved someone from having to scroll through hundreds of thousands of entries to try and reconcile the error.

Mark Aubin: That’s the key. Being able to detect those variances and those anomalies almost in real time rather than at a specific period end. Bringing those AI capabilities more upstream to the point of contract, the point of transaction will make companies much more agile.

Leigh Pepper: I agree. Having the whole architecture AI-enabled, from the source systems through the accounting hub processing, into the data and analytics layer and then out into the generative AI models allows for that semi real-time capability with anomaly detection before period end close which is where it really adds value. The partnership and the solution we’ve built, and what you

“

Using AI to look at the accounting rules, calculations and flows that they have in their current system and suggesting what that should look like in the Fynapse platform is a way that we believe can significantly cut down implementation time for clients.

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guys are building on the Microsoft side, can really transform how finance departments are thinking about their operating model and how they move to autonomous.

Gurkan Salk: It’s exactly what we want to see. Microsoft generative AI creates value for the customer not only by saving the user time, but also by allowing the organization to act quickly to address something that could cause them to lose money or miss an opportunity in the market.

Mark Aubin: What steps should an organization take when they’re thinking about deploying Copilot?

What do you think they should focus on? There’s always that intersection of low hanging fruit and what’s achievable versus pursuing true transformation.

Gurkan Salk: We think we’re at another big paradigm shift where generative AI will transform the way software works. We’re getting away from those button clicks and forms over data, to a world where the user interacts with the software much more freely, much more efficiently to get the results. In the case of Copilot

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for Finance, we’re transforming the way finance professionals work.

If you think about Microsoft’s vision of autonomous ERP, what we have today are Copilots that assist users.

But as we progress in that journey of autonomous ERP, we want to minimize the interaction points that the user has with the system. We want the system to help you so that they don’t have to do the mundane tasks, the system does that for you.

I think in the short term, it should be all about what new capabilities you are able to do in Excel that you couldn’t do in the past. But finance should also be able to see the vision of where we’re going with these generative AI capabilities in the future so that the users are prepared and understand the journey.

see this inflection point where you’ll access your primary interface, for example Excel, and then you click Copilot to help you. Then I think one day we’ll suddenly find everyone is just going into Copilot and accessing data and solutions from there - it will be interesting to see how that adoption curve progresses.

Mark Aubin: Excellent. Thank you both for your time and I am very much looking forward to seeing where 2024 and beyond takes us.

Gurkan Salk: Looking forward to the continued partnership with Aptitude in the Finance space!

Mark Aubin: That’s why I think the genius of the Copilot name is so perfect because it truly is a copilot for the user. It’s empowering finance users by placing the information they need right in front of them.

Leigh Pepper: I agree, the name is perfect. At some point we’re going to

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10 AI use cases for enterprise finance data

Fynapse is the most forward-thinking, AI-ready Finance Hub on the market. Through our open architecture and APIs, Fynapse can access and bring together real-time, finance-controlled data sets to create a trusted, AI-ready data foundation.

We’ve compiled 10 of the AI use cases we’re most excited about.

Read the full blog:

1

Anomaly detection

2

Analytics & reporting

3

Data analysis & data model generation

4

Addressing compliance change

5

Product documentation & training

6

Predictive risk management

7

Generative financial forecasting

8

Morning reports

9

Product troubleshooting and logic analysis

10

Accounting rules consolidation

By using machine learning, a user can automatically detect unusual transactions by analyzing past data and familiar patterns. This method improves the detection of fraud and the management of risk.

Finance users can ask nuanced, conversational questions about reports or charts, making data analysis more interactive, understandable and adaptable.

Finance teams can use unstructured data to find and connect data points, creating a data model for the product and natural language processing (NLP) to extract meaningful insights from unstructured data.

NLP can analyze and classify documents and extract useful information like client details, products and processes affected by regulatory change to reduce costs and the risk of non-compliance.

AI allows teams to source product instructions, definitions and general information, tailored to a user’s skill level and language. This can improve user’s skills and reduce onboarding time.

AI can be used to predict potential financial risks by analyzing patterns and trends in historical and real-time data and automate actions based on the parameters and rules set by an organization.

AI could enable finance departments to take a set of forecasting principles and equations and allow users to generate forecasts based on human language queries. This enhances the accessibility of forecasting tools, brings in public domain data and democratizes financial insights by enabling more people to actively contribute to and understand the forecasting process.

Finance teams receive AI-based reports and summaries of recent system activity delivered to users on a screen or by email to provide important information and highlight key metrics or areas of concern.

If users have questions or issues and want to understand the flow of their data, AI can help. AI-driven troubleshooting can speed up problem-solving, expedite issue resolution and empowers finance teams.

Analyze your set of accounting rules to understand which are redundant and how to streamline them. This can reduce the time to close and the number of rules and logic you are managing. https://www.aptitudesoftware.com/blog/ten-ai-use-cases-for-enterprise-finance-data/

Interested in learning more?

Reach out for a demo of Fynapse and we’ll show you the AI use cases we’re exploring.

See Fynapse in action

HSO experts roundtable:

AI & Autonomous Finance in Financial Services

By Sarah Werner

We assembled a panel of experts from Business Transformation Partner, HSO, to discuss the state of finance functions in Financial Services and the role of AI and Autonomous Finance in this traditionally conservative industry.

On current challenges facing the Financial Services industry Name: Tom Berger Title: Vice President and Industry Director for Financial Services Organization: HSO

Name: Jim Bretschneider Title: Executive Vice President Organization: HSO

Name: Tobias Menzel Title: Industry Director, Financial Services, DACH Region Organization: HSO

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Tom Berger: I think if we were to start a conversation about challenges in the financial services industry today, it starts with the overarching theme of doing more with less.

Jim Bretschneider: Absolutely. And underneath that, I think there are a couple of things going on. There is a good amount of consolidation - a lot of M&A activity. Often the business case is really around economies of scale and as a result, the cost of doing business needs to go down through automation. Finance is constantly working to attract the best talent. To address all these things, you need to have the best systems in place and reduce the amount of manual work as much as possible. Those jump out as some of the main challenges.

Also, if you are talking specifically about Insurance, I think there is a push towards more integrated systems. For instance, if you are in a Brokerage you need to have full visibility from your operational system - your AMS, your CRM - into the finance systems to be able to deal with producer compensation and other things in one big workload.

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On regional differences across Financial Services

one to do it. I don’t know about what you both think.

Tobias Menzel: From a European, especially continental European perspective, we are having a tough decade. Bear in mind we had this really low, zero interest policy set by the Central Banks and traditionally the cost to income ratios of European Financial Institutions have been traditionally bad. So, if part of your income equation went down, the focus over the past decade was really managing your cost base. So even though there were market demands for more digitalization on one side you could not simply react to that demand.

Jim Bretschneider: Yes, I agree with you – there is still a ways to go when it comes to automating finance. A lot of organizations are still dependent on disconnected, personal Excel sheets. To have a reasonable chance of using AI and other tools to automate your processes you’ve got to have a shared system, a corporate or organization-wide system, and not be dependent on the hundreds of Excel sheets that people are using to do their jobs.

Instead, you basically were trying to manage your cost base and changing regulations - work that did not help a bit to transform that digital experience for customers, for finance teams, for anyone. From my perspective, we are facing a huge traffic jam around digitalization and automation and – speaking for the continental European market – we really have to catch up with AngloSaxon Banks and Insurers.

Tom Berger: We’ve absolutely seen slower growth in Financial Services in Europe whereas US Financial Services firms, in particular capital markets in the US, have seen tremendous growth and as a result, have displayed some irrational behaviors. Interestingly, that hasn’t been the case in Insurance necessarily.

On the Autonomous Finance journey Tom Berger: The phrase Autonomous Finance is an interesting one because I think that the Finance suite, especially in conservative industries like Banking or Insurance, is probably the most conservative part of the of the business so I have not really seen anyone move toward an autonomous state. I think that people are interested in and learning about it. But no one wants to be the first

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You’ve got to get your processes in order first and then you can start moving from manual processes into automated processes then from automated process into AIsupported or AI-managed processes.

Even the best organizations are still somewhere on that journey. I don’t think anybody is getting to the point where all this is happening from endto-end, but you’re starting to see pockets.

I would say one example is AP invoice processing, where organizations are starting to process these using AI. As the comfort level gets high enough, teams are starting to simply review the work that AI produces.

Tobias Menzel: From a European perspective, we haven’t seen that many Financial Services institutions who have already moved towards

an Autonomous Finance function.

From my personal perspective, this is because they simply haven’t recovered from the finance transformation programs that have taken place over the past 12-15 years where you had a lot of systems and underlying processes standardized and transferred into low-cost shared service centers. Here the ultimate goal was to free up valuable time for onshore finance resources to truly act as a business partner and strategic leader for the organization.

But very often, unfortunately, the corresponding governance procedures were not in place, so you had this tremendous amount of investment, but the original business case failed to materialize.

Now, I think a key challenge, as I think about Autonomous Finance, is how to explain the difference between traditional finance transformation and an Autonomous Finance journey.

What’s the gap and what is the promise of Autonomous Finance?

How do we help companies pursue Autonomous Finance in a way that avoids the huge investments undertaken in the past that failed to fully deliver? I think this is really key.

On the relative infancy of AI Tom Berger: It feels like longer, but we’ve only really been talking about AI for a maximum of twelve months!

We have to remember we’re talking about – not a sales function, not a

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What’s the gap and what is the promise of Autonomous Finance? How do we help companies pursue Autonomous Finance in a way that avoids the huge investments undertaken in the past that failed to fully deliver? I think this is really key.

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marketing function – we’re talking about applying AI to the financial core of the business. Giving a machine autonomous authority over the finance function is a far leap from where finance functions are currently at. Yes, finance teams are eager to understand how they can do it, but they need the assurance that if they do it in a highly regulated environment, it won’t end their business.

We’ve all seen cautionary tales of trades happening or decisions made without human oversight. At the end of the day Finance teams want to make sure that this is done in a comprehensive and secure way and with partners that they can truly trust with their business. It’s a lot to put on the table.

Jim Bretschneider: I think it’s going to be a journey. The systems that companies are using 3 to 5 years from now are going to look very different than the systems that we’re seeing today.

It’s a matter of getting started on the journey. In the beginning it’s not about handing over every task to AI. It’s having tools that can support you – that notice when something looks a little different or doesn’t fit a pattern. That dig into the details or the underlying documentation to help you understand an allocation or the makeup of a complex journal entry.

That builds a series of accounting rules for your review. I think we’ll see a lot of these copilot scenarios as opposed to just having AI to take over.

Tom Berger: 100% agree. I think another area where AI can help is providing rapid access to data. One of the interesting things I’m hearing my customers ask for right away is the ability to ‘chat’ with their data by using natural language processing to surface data points or to provide a Controller quick access to a particular report, for example. Of course, teams still need to make sure

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The margins are so thin in Financial Services, and everyone is struggling to extract more value. Driving costs out in any way they can is key to the business. that they are accessing the data in a secure way and that they’re not giving permissions to access certain data to the wrong people.

I think everyone just wants to make sure that they’re doing it in the right way. At the end of the day, it’s a journey and it needs to be taken in a careful and systematic way.

On AI regulations – or lack thereof Tobias Menzel: What about the US regulations? What I’m seeing is the European Union commissioners are still discussing AI - is it moral is it anti-moral, what are the laws that need to govern use? Typical continental European behavior. I would expect that it’s much more ‘liberty and freedom’ from a US and Canadian perspective?

Tom Berger: Honestly the regulators haven’t caught up. The US President just created an office for this, basically a CIO for AI. I think that the regulators are way behind, and it could prove to be very dangerous. For now, from a regulatory perspective, existing regulations hold true, but I don’t think the existing regulations that I’ve read have adequately addressed the AI issue.

I think companies are self-regulating right now. Companies are more concerned about data leakage.

They’re more concerned about

mistakes. They’re concerned about hallucinations.

I’ll give you an example. I just got off the phone with a very conservative Bank, and they are saying ‘We need to do this right. We need to be very, very careful. We’re not jumping into this, and we are not going to risk our business based on this shiny object.’ At the same time, there’s this acknowledgement that when the floodgates open – and they will open - it will be a race because people will see it as a multiplier and a competitive differentiator. It will be another way to extract a few basis points from the bottom line.

Toby, you said it in the very beginning.

The margins are so thin in Financial Services, and everyone is struggling to extract more value. Driving costs out in any way they can is key to the business. You’ve made your workers work harder. You’re extracting as much productivity as you can from them. What else can you possibly do to extract additional productivity?

That is the central story, whether you’re above the line or below the line in these businesses.

Jim Bretschneider: Great points, Tom.

On guiding clients into the future of finance Jim Bretschneider: That reminds me of an Insurance Broker we’re currently working with who was looking to

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modernize their finance applications.

To start they were thinking about this in a relatively traditional way – putting everything they could think of onto their ERP solution because that was how it was always done.

Now we’re working with the Finance team to help them design a solution approach that matches their goals – in this case there are a few key elements. The first is building a finance architecture that supports an effective M&A strategy and allows them to access data from their acquired entities quickly an in a structured way.

The second is attracting and retaining producers, the independent Insurance Agents that sell their products. To do this they need to build an automated data flow to support Insurance Broker transactions to ensure they pay out the correct amount, as quickly as possible.

With these goals clearly established, we’re in a better place to discuss that actually loading up your ERP is not going to help you meet either of those goals. However, with an accounting hub supporting an ERP solution with a thin General Ledger, it’s easier to ingest data from

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acquired entities and centralize and configure those data flows in a more efficient way – while still using your traditional reporting tools.

Now you can really start to automate a lot of these processes that typically required data to travel from system to system via hard-coded integrations. Each element of the architecture is performing the job it was meant to do with seamless integrations establishing that consistent linkage.

On the value of partnerships Tobias Menzel: I think a big difference between Microsoft and other major ERP players is the fact that you can still think big, but you can start small.

This really is a completely different approach to this idea of having to be full stack from one vendor to ensure everything works.

Tom Berger: That’s a great point, Toby.

I think about the composable ERP message that Microsoft VP, Georg Glantschnig has promoted from a finance and operations perspective.

It’s completely in line with the bestin-class technology ecosystem that we are delivering through our partnership with both Microsoft and Aptitude.

Tobias Menzel: Exactly. And this underpins the whole premise of Autonomous Finance or any change initiative from my perspective, because you can have this big vision but implement these progressive solutions that drive change without requiring huge, upfront investments prior to seeing any value.

Our partnership with Microsoft and Aptitude offers the chance for Finance functions to create a new finance architecture that combines accounting hub and subledger technology, an accounting rules engine and then the Modern ERP/ thin General Ledger offering from Microsoft – all tightly integrated to make reconciliation and drill back so much easier. And now, as of just last month, you have this announcement from Microsoft around Copilot for Finance. It’s extremely exciting to think about how this is going to help finance conduct their daily business.

It’s really game changing.

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Autonomous Finance: How to manage impacts and adopt changes

By Sara Sheehan

Change management is at the heart of any finance transformation. For Sara Sheehan, founder of Sara Sheehan Consulting, it pays to begin with the end in mind and understand the complexities of changing behaviors.

Name: Sara Sheehan Title: Founder and Executive Consultant Organization: Sara Sheehan Consulting, LLC Location: Dallas, TX

Sara Sheehan, PCC, is a consultant and Executive Coach who works with C-Level executive leaders designing organizations, developing business strategies, managing change, optimizing talent and leadership development, and solving complex human performance problems.

Her mission is to help leaders, teams, and organizations adopt change. She co-creates the plan with her clients to manage change, develop and align leaders, and implement strategic initiatives. Many clients are asked to lead change within their organization but do not have the specific project experience and capabilities to lead the work. With the right thought partner and a customized approach, they have the direction they need to effectively lead the most challenging projects in their career with ease.

Sara’s 25-year professional career includes working with leaders in Fortune 100 companies and leading consulting firms.

Finally, Sara’s expertise spans change, organization design and effectiveness, talent development, training, marketing, business building, and business development.

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Extensive change management is required to support the finance function in implementing artificial intelligence, Autonomous Finance, and cutting-edge technology transformation projects that will genuinely change how the world works. The past 25 years have proven that digital transformation projects fueled by a traditional finance module can bring consistent processes, ways of working, and software features and functionality that allow the business users in finance to work smarter and have one data source for decisionmaking.

However, clients can set themselves up to fail with ERP implementations during global design by not making tough decisions on process changes that would facilitate smooth adoption of the system out of the box. Strong governance on business processes like procurement (e.g., buying approval and review processes with preferred and approved vendors based on spend categories, etc.) and minimizing or eliminating all system customizations play a big role in long-term success.

Now, we are at a critical juncture that will determine the future culture of

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finance teams and potentially even reshape the leadership role of the CFO. Adding the goal of achieving Autonomous Finance alongside a broader digital transformation brings four watershed moments for senior executives to consider how they best proceed, starting strategically with the end in mind.

How will Autonomous Finance impact the organization, roles, and employees? How can we clearly understand where work is getting done and by whom?

For those concerned that Autonomous Finance will impact their job, there is cause for concern.

Employees will need to understand clearly how implementing the technology will change what they do, as it most certainly will. The best way to map out where work will be done in the future is by borrowing a Lean Six Sigma tool, SIPOC, to map out the process from beginning to end by role.

SIPOC stands for source, input, process, output, and customer. If you can map out your finance processes with this detail and confirm what individuals and systems may be involved in each step, you will have

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a clearer picture of where work has shifted.

The short answer is that employees can shift lower-value work to Autonomous Finance solutions and focus more on problem-solving, strategy, and decision-making. This will undoubtedly change the type of work team members do and what’s done by systems and tools. After the process is documented, you’ll be able to ascertain where work is done and may be able to redirect individuals to higher-value work within finance or even to other areas of the business like procurement or supply chain.

How will Autonomous Finance impact governance, and will principles of appropriate use support behavior change? What decisions are required on user access to functions or data?

It is critical for organizations implementing Autonomous Finance to determine the appropriate use and governance, as well as conduct reviews of work completed by AI tools. Leaders must have a clear point of view on governance that they share with staff early and often during the implementation.

Appropriate use could include a

list of the types of functions, tasks, or prompts with parameters so employees have a clear picture of what tasks will be automated. For example, clearly understanding the prompts to complete month-end or quarter-end will help all concerned.

Conversely, employees must know that requesting a list of all salaries and bonuses at the VP level and above is unacceptable to satisfy their curiosity. Just like implementing any ERP system, user profiles and access to specific functions and data must be very clear and part of the implementation at the outset.

Finally, individuals must know they are responsible and accountable for thoroughly reviewing work completed

by Autonomous Finance solutions, as errors may need to be corrected before release. The review process is a critical step.

Painful lessons will undoubtedly be forthcoming for businesses relying solely on system-generated finance results. Further, reviewing the quarterly financial reports developed by an Autonomous Finance solution before releasing performance to investors is critical for a public company.

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Behavior change in any context is difficult. We are changing what we do. When it is a routine task that has a well-developed habit supporting it, it’s even harder to change the behavior.

How do these technologies impact finance, and what mitigating actions must be implemented to ensure finance can operate post-go-live and ensure leaders get the information needed for decision-making?

The work to understand business impacts must be considerable and detailed across all finance teams using Autonomous Finance solutions. This will require a facilitated discussion with subject matter experts and process owners to review how the process is done today and how it will be done in the future.

Teams will also need to document what is changing, the risk and level of impact on the business, and what needs to be done to make sure these impacts are addressed.

This is a resource-intensive effort, and it may require subject matter experts and their teams to come together with a change leader for a series of meetings to document what’s changing and develop the mitigating actions that need to be completed. If the work is done at too high of a level, there will undoubtedly be critical changes to the business that are not addressed, leading to a dreaded fire drill to correct problems that could have been avoided.

Finally, employees need to understand, according to their role, what they will need to stop, start, and continue to do to support a successful implementation of these technologies.

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How do I get my finance team to adopt new ways of working?

Behavior change in any context is difficult. We are changing what we do. When it is a routine task that has a well-developed habit supporting it, it’s even harder to change the behavior.

According to James Clear in Atomic Habits, it takes approximately 66 days to form a habit fully. However, once it’s formed, a neural connection is established to send messages in our brain to complete a task. It’s hard for the brain to break a habit once that neural connection has been made. That’s why organizations need to fully understand what

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Selecting change agents across the organization at varying career levels will help you get a clear picture of the sentiment in the organization, understand how things are going locally, and identify resistance or barriers to success.

behaviors need to change at the task level regarding what employees or business users will do differently in the future and what new behaviors will support a healthy organizational culture. This will require a planned approach throughout 30, 60, and 90 days to embed new behaviors.

Without a planned approach, the behaviors will not stick.

Every part of the change strategy matters. Each aspect of a solid change management strategy is essential; all parts come together to support success. The leaders need to be visible and committed.

It would be helpful if a mobilized, active change network were in place to distribute communications and collect feedback or sentiment from the organization. A change agent network is the first line of defense in a significant project that can solve problems locally, distribute communications, and collect feedback from their teams.

Selecting change agents across the organization at varying career levels will help you get a clear picture of the sentiment in the organization, understand how things are going locally, and identify resistance or barriers to success.

A robust communication strategy is also critical to program success. Understanding your past organizational change history and current organizational change readiness is helpful context that can provide input to communication and training plans. Thorough training of end users engaging with Autonomous Finance solutions are required.

In summary, Finance teams are about to embark on a considerable journey, and change management will certainly help them achieve the adoption of new behaviors. It’s not an easy transformation to navigate, so start getting prepared early and don’t hesitate to ask an expert for help.

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State of material weaknesses Unpacking material weakness trends and implications

By Mark Aubin

Material Weakness can harm organizational reputation and financial performance. In this article we look at current trends in material weaknesses, what’s at stake and what organizations can do to reduce the chances of misstatements.

Name: Mark Aubin Title: Senior Vice President of Product and Market Engagement Organization: Aptitude Software Location: New Mexico Mark Aubin currently serves as SVP of Product and Market Engagement at Aptitude Software where he is a member of the Product Leadership Team, works to identify market opportunities and ensures the successful positioning of our suite of products.

Mark brings over 25 years of experience in enterprise financial applications and has served in senior roles as a software vendor, consumer, and consultant. He has deep finance and operational knowledge across diverse industry sectors and has been focused on software solutions for financial regulatory compliance and modernization since 2007, including co-founding and leading product and technology for RevStream, a leading Enterprise Revenue Recognition and Management Solution.

Since its acquisition by Aptitude Software in 2017, Mark has served in several strategic roles, including SVP of Sales, Solutions Consulting, and Account Management for North America and Chief Innovation Officer.

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Misstatements in company financials may seem mundane until they hit front page news with ripple effects that can impact stock prices, senior leadership teams and shareholder confidence.

Recently, companies like Credit Suisse, BNY Mellon, Mattel, Marcum and others were called out for misstatements in their financial reporting. While the reasons vary across organizations, research into material weaknesses and their most common causes can show us what most often leads to financial misstatements.

What is a material weakness A material weakness, as defined by the Securities and Exchange Commission (SEC), is a deficiency, or a combination of deficiencies in Internal Control over Financial Reporting (ICFR) such that there is a reasonable possibility that a material misstatement of the registrant’s annual or interim financial statements

https://www.sec.gov/corpfin/cf-manual/topic-4#:~:text=4320.8A%20material%20weakness%20is,detected%20on%20a%20timely%20basis.%20%5B

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will not be prevented or detected on a timely basis.1 Said more succinctly, it’s an admission by an organization that the internal controls around their financial reporting may not prevent a misstatement.

Companies with material weaknesses are required to report them in their public SEC filings – an action which can result in additional costs, risks and reputational damage. If companies fail to address these material weaknesses, they can result in misstatements and the delivery of incorrect information to company stakeholders.

Current state of material weaknesses A 2023 report from PwC found a resurgence of material weaknesses in public company disclosures.

Specific findings include: • The number of material weaknesses disclosed in a company’s 10-K jumped 73% from 2021 to 2022 • Material weakness numbers increased 25% in the first quarter of 2023 relative to Q1 2022 • 55% of material weaknesses reported related to either the financial close process, personnel inadequacies/segregation of duties or IT general controls

What’s behind material weaknesses There are likely some common themes behind these trends.

found that the percentage of material weaknesses attributed to ‘lack of accounting resources/expertise’ has steadily increased from 34% in 2021 to 48% in 2022 and 55% in 2023.2 This shortage shows few signs of improvement with U.S. accounting graduates with either a Bachelors or Masters in Accounting falling 7.4% between 2021 and 2022 – the largest drop since the mid-90s.3 Additionally, the data suggests that a high turnover of resources increases the likelihood of material weaknesses.

Whether related to restructuring efforts or resignations, insufficient change management and a lack of knowledge transfer can lead to an increase in errors.

Increase in IPOs and SPACs in recent years While IPOs and SPACs have slowed down in the last year or two, in 2021 IPOs (including SPACs) enjoyed a record year with 2,340 new issues raising $428.9B. That’s following a 462% jump in proceeds raised

by SPACs between 2019 to 2020.

These companies typically have fewer resources and a leaner operating model, which can result in weaknesses related to inadequate personnel, oversight and level of reviews.

PwC’s research found that “Fortythree percent of all US IPOs since 2017 disclosed at least one material weakness before going public and most de-SPAC companies are likely at greater risk for fraud within just two years of going public due to material weaknesses and internal control deficiencies in a number of key areas.”4

Lack of skilled accounting

weakness between 2019- 2023, 226 companies or almost 30% disclosed them in multiple years.

Andrew Imdieke, an assistant professor of accountancy at Notre Dame’s Mendoza College of Business has done research on why and when a company’s remediate strategies will likely be successful or fail. He explains, “I became very skeptical about the extent to which other companies were really fixing these problems,” said Imdieke. “There were these cases where a company would report a material weakness in inventory and then say they fixed it, but then a year later, you’d see a restatement related to the same exact problem.”

In his research he found that companies that are disclosing that they’ve solved the problem in less than a year are significantly more likely to be in the failure category later. “They need to take the time to let these remediation processes operate and test the effectiveness of their strategy,” observes Imdieke.5 Inadequate financial controls In some instances, material weaknesses stem from poor or lacking controls around disclosures themselves and from inadequate financial controls around the close and reporting processes.

KPMG found that from 2022 to 2023, material weaknesses stemming from the timeliness, accuracy and completeness of disclosure controls increased from 21% to 43%.

Additionally, KPMG found the top two process-related areas responsible for material weaknesses in 2023 were identified as:

Failing to test remediation measures “The widening shortage of accountants has begun showing up in financial statements,” reports the Wall Street Journal. A KPMG Report

The KPMG report cited above also found that, of the 768 companies that filed a report with a material

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• Financial Close/Reporting (57%): Defined as failure to design and maintain formal accounting policies, procedures and controls over

2 https://kpmg.com/kpmg-us/content/dam/kpmg/pdf/2024/trends-in-material-weaknesses.pdf 3 https://www.wsj.com/articles/accounting-graduates-drop-by-highest-percentage-in-years-5720cd0f https://www.pwc.com/us/en/services/consulting/cybersecurity-risk-regulatory/assets/pdf-cyber-r-and-r-fraud-risks.pdf 5 https://mendoza.nd.edu/news/time-is-on-managements-side-study-shows/

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significant accounts and disclosures to achieve complete, accurate and timely financial accounting, reporting and disclosures, including accounting for complex features associated with warrants, segregation of duties and adequate controls related to the preparation and review of journal entries • Systems (33%): Where information technology general controls (ITGCs) related to the Company’s information technology (IT) systems were ineffective. Therefore, the automated process-level controls and manual controls dependent upon the accuracy and completeness of information derived from those IT systems were also ineffective because they could have been adversely impacted.

This could point to the increased Finance IT complexity in organizations today and their struggle to consolidate, standardize and report efficiently.

What’s at stake?

Companies disclosing material weaknesses in internal controls can face repercussions, including reputational damage and market backlash due to diminished investor confidence. Share prices can dip and the organization may trigger regulatory scrutiny from bodies such as the Securities and Exchange Commission (SEC).

Additionally, credit rating agencies may downgrade the company’s creditworthiness. Therefore, swift and effective action is necessary to restore trust, ensure regulatory compliance, and safeguard the company’s financial stability and stakeholder relationships.

What can companies do about it?

While there are several potential reasons for material weaknesses, a company can often improve their controls, data and systems

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environment to address pressing issues.

1. Implement strong internal controls: Establish robust internal controls that include segregation of duties, proper authorization processes and regular monitoring of transactions. This ensures that errors or irregularities are detected and corrected promptly.

2. Establish a culture of accountability: Ensure leadership communicates that it’s safe and encouraged to come forward with broken processes or identified issues when they are noticed.

3. Eliminate as many manual and spreadsheet-based processes as possible: The less data is moved around and duplicated the better. By automating core finance processes, removing data lifting and shifting and implementing a trusted data foundation companies lessen the risk associated with manual processes.

to both reputation and financial performance. Recent trends indicate a resurgence in the disclosure of such weaknesses, with root causes ranging from a shortage of skilled accounting professionals to deficiencies in financial controls and inadequate remediation strategies.

To mitigate these risks, companies must prioritize the implementation of robust internal controls, foster a culture of accountability, and establish clear policies and procedures. In some cases, a finance data and accounting platform like Aptitude Fynapse can help finance teams increase productivity and lower costs through the automation of data and accounting processes.

By taking decisive action to strengthen their controls, organizations can safeguard their reputation, ensure regulatory compliance, and maintain the trust of stakeholders in an increasingly complex financial landscape.

4. Create clear policies and procedures: Document clear and comprehensive accounting policies and procedures. Ensure that employees understand their roles and responsibilities in the accounting and reporting processes.

5. Streamline processes: Invest in software and automation tools that streamline accounting and finance processes and provide transparency in the application of accounting rules and provide source to post visibility into the transactions that support journal lines and balances.

6. Monitor and test: Continuously monitor and test internal controls to identify any weaknesses or deficiencies. Implement regular reviews of control activities and perform testing to ensure effectiveness and compliance with established procedures.

The prevalence of material weaknesses in organizational internal controls presents significant risks

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Cybersecurity in the age of AI

By Chandra Kulkarni

In 2024, cybersecurity continues to be a strategic priority for C-suite executives and technology leadership teams especially considering the recent Securities and Exchange Commission (SEC) regulation regarding Cybersecurity Disclosure requirements for U.S public companies.

This requirement combined with an unusual combination of evolving technological trends, global polycrisis and locational privacy regulations have the potential to disrupt traditional information security (IS) models and measures.

The CFO balancing act Name: Chandra Kulkarni Title: Information Security Officer Organization: Aptitude Software Location: California Chandra Kulkarni is the Information Security Officer at Aptitude Software and heads the Information Security function. He has over 20 years of information security and technology experience. Prior to Aptitude Software, Chandra was a Managing Director at KPMG’s San Francisco Office leading the Information Security advisory services and consulting practice with a focus on SaaS and Fintech.

He is a passionate security blogger and has frequently been a panelist and trainer at security conferences. His interests include technology transformation and the anthropocentric security organization.

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CFOs today need to strike a delicate but important balance between allocating resources to transformational technology initiatives such as cloud integration/ migration, AI strategies and cybersecurity initiatives.

If technology changes outpace the development of cybersecurity controls at an organization, the risk of cyber threats – whether due to remote working, large data set transfers or ransomware attacks – can result in data breaches or security incidents which have the potential to derail or delay technology transformation plans.

Finding opportunities amid challenges At Aptitude Software, we believe the current environment presents opportunities to CFOs/CTOs/CIOs/

CISOs to improve their organizations’ cyber security posture and information security program through a focus on the following areas: • Enhancement of security governance frameworks and alignment of assurance efforts with clients, partners and third-party vendor organizations.

• Secure use of generative artificial intelligence (GenAI) through collaboration with internal and external stakeholders across products, IS tooling and processes.

• Reorienting security behavior and culture programs to strengthen the human element of cyber security.

Security governance Security frameworks and standards have recently been revised to reflect the changing global environment while global privacy, security and sovereignty requirements continue to evolve in a divergent and discontinuous manner.

Aptitude is embracing this change in 2024 by upgrading to new ISO 27001:2022 and PCI-DSS Version 4.0 certification standards. This

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Additionally, we expect to further improve our security posture through modularization of product and data architectures across multiple cloud services. upgrade will strengthen our cybersecurity reporting to our board and stakeholders and ensure that IS measures and performance metrics are closely aligned to our client and business needs. We expect to deliver benefits to our clients and partners by bringing the same approach to the table when supporting their risk management programs.

Additionally, we expect to further improve our security posture through modularization of product and data architectures across multiple cloud services. We expect our clients to see significant benefits from this localization and alignment including: • An increase in the depth and breadth of our client security assurance • Greater flexibility in meeting client needs across multiple geographies • An increase in the depth of our IS coverage Examples of such alignment include Aptitude’s recent Cyber Essentials Plus certification to meet the assurance needs of our UK-based government sector clients.

AI initiatives The increased use of AI is significantly transforming the world of cybersecurity and is revolutionizing

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the process of real-time monitoring, threat detection and mitigation.

ISO/IEC 42001:2023 provides valuable guidance to organizations for establishing, implementing, maintaining and continually improving an internal Artificial Intelligence Management System (AIMS).

Having laid a foundation for secure use of AI through formal but evolving policies and guidelines based on ISO 42001, Aptitude is now using AI across multiple IS processes including AI-oriented vendor tools for Malware Protection and Cloud Native Protection Platforms for our cloud applications. These tools provide features utilizing AI and machine learning to significantly improve the speed and efficacy of our vulnerability management and incident resolution processes.

We are also using AI tools to make nuanced cloud configuration changes to resolve vulnerabilities and misconfigurations. AI is helping us deal with the continuing gap between demand and supply of Information Security resources as well as reducing information security alert fatigue.

On the product side, we are working closely with partners such as Microsoft to bring AI tooling to our Autonomous Finance products like Fynapse. We expect this partnership to deliver positive outcomes for our

clients including through use of their data within our Autonomous Finance product portfolio.

Security behavior and culture Aptitude’s information security culture and training program partners, including phishing simulation vendors, are also using AI across their training platforms. Such use includes AIdriven dynamic selection of phishing security test templates as well as recommending AI-driven optional learning based on user engagement.

This combination of phishing tests and personalized learning will help us inoculate employees against social engineering and human-agencydriven cyber security threats.

Aptitude is also using humancentric design features and nudge techniques to reduce friction within our information security program and drive optimal and effective use of IS controls across internal and external stakeholders. We expect these design principles to be utilized across multiple aspects of our IS program including broad initiatives such as information security training, third-party risk management, vulnerability management as well point applications in use of MultiFactor Authentication (MFA) for our products.

Conclusion A three-pronged approach of securely embracing AI-driven technology innovations, closer security alignment across the stakeholder value chain and a focus on the human element of cybersecurity can help C-suite teams drive quantum improvements in the performance and assurance of information security programs.

At Aptitude, we expect our focus on these areas over the next 3-4 years to significantly enhance our client IS assurance.

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© 2023 KPMG LLP, a Delaware limited liability partnership and a member firm of the KPMG global organization of independent member firms affiliated with KPMG International Limited, a private English company limited by guarantee. All rights reserved. NDP423526

5 Minutes with...

Going beyond the business to get to know Gary Simon, founder and Chief Executive of FSN Publishing Limited and leader of the popular LinkedIn group, The Modern Finance Forum.

By Sarah Werner

For the last 18 years, Gary Simon has been thinking, researching and writing about the office of the CFO. He’s grown his FSN brand alongside the LinkedIn group, ‘Modern Finance Forum’ to one of the top 5 groups for CFOs globally on LinkedIn and a platform for strong debate and dialogue for CFOs and other senior finance professionals in different industries across the globe.

Name: Gary Simon Title: FSN Publishing & FSNTalent Organization: Chief Executive

You’ve been thinking about the office of the CFO for many years now, what are the biggest changes you’ve seen in the finance function as a whole?

Location: UK Gary Simon is a leading figure in the UK accounting and finance profession. He is a Fellow of the Institute of Chartered Accountants in England and Wales; a Fellow of the British Computer Society; and the author of four books on financial software and information systems. He is the leader of the FSN Modern Finance Forum on LinkedIn, with a network of more than 58,000 senior finance professionals worldwide.

Request to join the Modern Finance Forum

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​ he bulk of Gary’s professional experience T has been as a senior consulting partner with Deloitte, working at Board level with global 2,000 companies and large public sector organizations. He set up FSN Publishing, as a provider of thought-leadership and research to the accounting profession in 2005 and FSNTalent, a search business for senior finance professionals, in 2024.

So, my experience stretches back 42 years – I know it’s difficult to believe! In that time, I’ve seen huge amounts of change, but it’s really accelerated in the last 20 years. One thing I’ve noticed is a shift away from the general ledger as the complete source of finance information. It’s still important in terms of statutory processes, but in terms of using it to try and understand the main levers in the business – it’s just not really that helpful. Today, I see 80% of the useful data, analytics and nuggets of insight coming out of other solutions.

Another big change is clearly automation which I’d expand to include hardware and software

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I think another big change is the willingness to consider other qualifications for roles within today’s finance function. For years, the gold standard was a chartered accountant or CPA, which is still an important qualification but now you might look to a math graduate, a data scientist, finance data engineers or people who have expertise in other areas of the business. interoperability. When I started out, this was a huge issue. You couldn’t just take data from an IBM system and put it on a system from Unisys.

And it wasn’t only the hardware, but also the operating systems that wouldn’t allow that integration of data. I remember carting around 10 megabytes of data on a huge disk platter the size of my desk and literally picking it up and putting it in another machine – it’s just unthinkable today. It’s been a revolution.

The third thing I’d say – which is a result of all the things I mentioned above – is this cultural change where finance has gone from being inwardly focused, where everyone had to come to finance to get the answers they wanted, to this idea of Finance as a business partner that can support the wider organization with selfservice data. Finance has become much more outwardly focused and visible.

How about finance professionals themselves, what are the changes you’ve seen there?

I think it’s something that’s affected all professions, which is increased

Spring 2024

specialization. The breadth of the finance remit has significantly expanded which reduces the effectiveness of a jack-of-alltrades finance professional. Now you need people specializing in tax to keep up with global changes in tax regimes, you need accountants who are learning Python or how to write AI algorithms, you need FP&A specialists to reforecast in an instant.

I think another big change is the willingness to consider other qualifications for roles within today’s finance function. For years, the gold standard was a chartered accountant or CPA, which is still an important qualification but now you might look to a math graduate, a data scientist, finance data engineers or people who have expertise in other areas of the business. You can’t be credible with business leaders in and around a large enterprise unless you have team members with an appreciation for the challenges facing that area.

We just published some research that looks at the future of recruitment in the finance function and it shows that despite all the doom and gloom that pervades Europe in particular, finance functions are expected to

grow. Responses showed 30% are going to grow in 2024/25 with 53% reporting that they expected to stay the same. That means less than a quarter expect to shrink which is very encouraging.

Worth noting though that growth is not going to be in the traditional areas of financial accounting, governance and compliance. It’s going to be in those new areas of AI, data management, FP&A and analytics.

The people who are going to lead the charge are the ones who have strong analytical capabilities.

I want to talk about your community.

You’ve built the Modern Finance Forum from scratch to almost 60,000 members!

I’ll let you in on a secret. I was, and still am, very interested in art. I paint as an amateur and years ago, I joined a community called Paint Doodle. Basically, everyone would show their work and members would constructively comment to help others improve their technical skills.

The community founder joined every single conversation without fail. He served as a guru and guide and was just completely passionate about it.

That’s the approach I have taken in building the Modern Finance Forum.

It is all encompassing, all embracing – it can take over your life! But for a community to work you must have a genuine desire to help the people within that group. Essentially, I’m there almost every day. I feel that if someone has taken the trouble to write than you must take the trouble to respond – even if you just acknowledge the comment. I’m lucky to have good moderators who help me keep up.

Unless the subject matter is in your DNA, unless you’re credible to talk about the topics at hand, unless you’re constantly bringing fresh ideas and new developments to the attention of your audience, they’re going to run away. We now have 4

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million post views a year and, on average, 25,000 people coming to our community a day.

That’s incredible. What was your initial vision for the community?

We’ve really stayed true to our vision of a community for senior finance professionals - 82% of our members are in senior roles. A tone of enthusiasm and respect is set by our moderators, and we’ve never had any issues with keeping things polite and thoughtful. We’ve also brought our community together in person, with larger functions pre-covid and lately with smaller, focused dinners.

mentor people to become fellows for the British Computer Society. When you are in a field that is changing every day, it’s easy to get up excited, to want to work on the next thing – there’s never a boring moment. You just try and keep up!

Honestly, there have been no real lows, just opportunities to learn, I guess. I’ve been very lucky.

What’s next for FSN and the Modern Finance Forum?

Any career highs or lows?

Just last month we launched FSNTalent, something I am very excited about. FSNTalent is a new approach to recruitment designed to help organizations find finance talent.

It’s been a fantastic ride. When I saw computers come on the scene – literally I was involved in the very, very first PCs – the Commodore Pet. I was lucky enough to work with a couple of other accountants who decided to specialize in computing. We just sat in an open plan office with a bunch of computers, surrounded by our shared computer magazines and just bounced ideas off each other and learned together.

Over the years, I’ve recruited hundreds of Finance people, especially in my career with Deloitte.

But what spurred me on this journey was talking to a lot of CFOs in our Modern Finance Forum. They were fed up with recruitment. Often, it’s done poorly by recruiters who don’t understand finance, the business they are recruiting into or the rapidly changing role of the finance professional.

Our knowledge grew and we progressed from one machine to the next. It’s a passion. Today I coach and

Our research actually showed that 53% of businesses are unhappy with the finance talent they end up with!

Spring 2024

That’s a pretty poor statistic but not surprising when you consider traditional recruiting agencies are increasingly using AI engines to match CVs to job specs. By taking this approach you are completely missing out on the human element and those necessary skills that may come from roles outside the finance sector.

We believe we can do this a lot better by understanding the business and the individuals we’re working with.

We’re not going to be a recruitment factory. We’ve got a great community to tap into and research that is showing us where finance leaders are headed, what they need to do and what characteristics they need to become finance leaders which we can use to guide candidates and companies we’re working with. It’s an exciting next step.

Get the FSNTalent research results

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