ARTIFICIAL INTELLIGENCE (AI) Can and is, transforming legacy finance processes -and is AI continuing to advance.

AI tools have immense potential to drive the next wave of innovation in the finance sector, addressing the ever-evolving needs of businesses and consumers and by automating these financial processes.

“ CFOs and financial leaders can expect AI to become an integral to all aspects of finance in the immediate future and AI is revolutionising the way that CFOs and their departments work,” says Pierre Montersino, a strategically driven and dedicated Chief Technology Officer and transformation leader with significant experience specialising in driving Business and IT transformations, business change and excellence.

Pierre has has successfully delivered People and Business transformation programmes across a range of sectors globally, leading multi million dollar large-scale transformation and has a passion for delivering sustainable change in a digital and cloud environment. Pierre has worked with brands including the Bank of England and Metro Bank (UK).

“AI is already helping CFOs to improve the financial performance of their businesses and achieve their strategic goals,” he says.

“As AI technology continues to develop, it is expected to see even more innovative and powerful AI tools emerge in the coming years.

“Companies that strategically leverage these solutions will be able to increase productivity, make better decisions, and future-proof their operations.”

AI can add value and has the potential to revolutionise the way that CFOs manage their finances and by automating tasks, improving accuracy, reducing risk, and gaining insights, AI can and does help businesses to improve their financial performance and achieve their strategic goals.

Camino Search’s Assistant Director, Tom Garratt spoke to Pierre to ask him more about the change that’s taking place in finance and the tools that are helping CFOs shape efficiency in their finance functions.

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​The interview

Tom Garratt (TG) How can AI add value to financial systems within a business?

Pierre Montersino (PM) Artificial Intelligence (AI) can add significant value to financial systems within a business by enhancing efficiency, accuracy, and decision-making. Here are several ways in which AI can contribute to financial systems:

·        Automating of repetitive tasks - automating many of the repetitive and time-consuming tasks, such as data entry, reconciliation and reporting, frees up the team to focus on more strategic and value-added activities.

·        Improving accuracy - improving the accuracy of financial data and reports by identifying and correcting errors can lead to better decision-making and improved financial performance.

·        Reducing risk - identifying and mitigating financial risks by analysing data and recognizing patterns can help businesses to avoid costly losses.

·        Gaining insights - A CFO or HoF can gain insights into their financial data that would be difficult or impossible to obtain manually. This information can be used to improve operational efficiency, make better investment decisions and develop new products and services.

·        Data Analysis and Reporting - AI-powered algorithms can analyse vast amounts of financial data quickly and accurately. This enables businesses to generate real-time financial reports, identify trends and make data-driven decisions promptly.

TG: What AI tools are currently available on the market for CFO’s?

PM: There are a number of AI tools that are currently available on the market to improve their financial management processes. (Source: Best AI Finance Tools of 2023 by Nicholas Allyn)

1.      Datarails FP&A Genius - CFOs and FP&A analysts will find Datarails a game-changer. Known for automating manual work and allowing finance professionals to concentrate on their strategic value, Datarails has further enhanced its offerings with the introduction of FP&A Genius, an AI tool that readily answers ‘what if’ and scenario questions, reducing the time taken to provide accurate responses.

2.      Domo - For data analysis and integration, Domo has been a market leader since its inception in 2010. It specialises in integrating data from various sources, merging them into a unified, user-friendly dashboard designed for business decision-makers.

3.      Booke.AI - Booke uses AI to automate bookkeeping for finance teams, fixing uncategorised transactions and coding errors, simplifying communication with clients, and automating more of your work.

4.      Rebank - Rebank is an advanced financial and legal database that uses AI to categorise transactions based on country and currency. It takes care of the finance and tax regulations involved when dealing with international transactions, ensuring strict adherence to these regulations for each jurisdiction.

5.      Nanonets Flow - Nanonets Flow is an innovative platform that uses AI to make finance tasks easier. It helps finance professionals by automating complex processes, so they can focus on making important decisions and growing their business.

6.      Planful Predict - Like FP&A Genius, Planful Predict is a tool for high-level CFOs and CEOs. It helps making more accurate and fast decisions as it takes the place of time-consuming number-crunching and reporting.

7.      Trullion - Trullion uses AI to connect structured and unstructured data together into one platform. This allows finance teams to minimise cost inefficiencies, ensure up-to-date compliance and save time through automating the accounting process.

8.      ZeroTax AI - ZeroTax.ai (https://zerotax.ai/) is transforming the tax landscape and making the lives of taxpayers easier. ZeroTax.ai is an innovative platform that leverages AI algorithms to streamline the tax compliance process.

TG: How can AI be used by CFO’s to automate processes?

PM: CFOs can leverage AI to automate a wide range of financial processes, streamline operations, reduce manual tasks and enhance decision-making. Here are some key areas where AI can be used by CFOs to automate processes:

·        Data entry - This can be automated saving the CFOs and their teams a significant amount of time and reduce the risk of human error.

·        Reconciliation - By automating the reconciliation process (for example bank statements and credit card statements) can help CFOs to identify and correct errors quickly and easily.

·        Reporting – Financial reports such as balance sheets, income statements, and cash flow statements can be automated, freeing up CFOs (and their teams) to focus on analysing the data and making informed decisions.

·        Auditing - By automating the audit process could identify potential compliance issues and risks that can help a CFO ensure that their businesses are compliant with all regulatory requirements.

·        Fraud detection – As Fraud is becoming more advanced, AI tools are being used to develop fraud detection systems to identify suspicious activity, helping the CFOs to protect their businesses from financial losses.

·        Budgeting and forecasting - AI can be used to create more accurate and timely financial budgets and forecasts.

·        Investment management - AI can and is being used to develop investment strategies and making better investment decisions.

·        Risk management - AI can be used to identify and mitigate financial risks.

·        Tax compliance – The compliance processes for the finance department can be automated to ensure that businesses generating consistent data in compliance with all applicable tax laws and regulations.

TG: How can AI be used to improve the quality of data within Management reporting?

PM: AI can significantly improve the quality of data within management reporting by automating data validation, cleaning, and enrichment processes. Here are several ways AI can enhance data quality in management reporting:

·        Automating data cleaning and validation - automating the process of cleaning and validating data can help identify and correct errors and inconsistencies.

·        Enhancing data completeness - AI can be used to identify and fill in missing data in management reports. This can help to provide a complete and more accurate picture of the business's performance.

·        Identifying data anomalies – Achieved by identify anomalies in data, such as sudden spikes or drops in values. This can help to identify potential problems or areas for improvement.

·        Generating insights from data – By generating insights from data that would be difficult or impossible to obtain manually. This information can be used to improve the quality of management reports and make better decisions.

TG: How can AI be used to create leaner, high -performance functions?
PM: AI can be used to create leaner, high performance functions in several ways, including:

·        Automating tasks - Many of the repetitive and time-consuming tasks involved in many functions, such as data entry, reconciliation and reporting can be automated, releasing employees to focus on more strategic and value-added activities.

·        Improving accuracy – AI can improve the accuracy of the data and reports by identifying and correcting errors, leading to better decision-making and improved performance.

·        Reducing risk – Risks can be mitigated by analysing data and identifying patterns that may indicate potential problems. This can help businesses to avoid costly losses.

·        Gaining insights – By using AI to analyse the data to identify repetitive trends and insights that would be difficult or impossible to obtain manually. This information can be used to improve operational efficiency, make better decisions, and develop new products and services.

TG: How can AI automate a finance tech stack?
PM: AI can automate a finance tech stack in several ways, including:

·        Automating data entry: Through the automating of the processes of data entry data into financial systems and other software applications, saving finance teams a significant amount of time and reduce the risk of human error.

·        Automating reconciliation - By automating the reconciliation of financial accounts (for example bank statements and credit card statements) helps help finance teams to identify and correct errors quickly and easily.

·        Automating reporting – More and more reporting is being done by AI to automate financial reports, such as balance sheets, income statements, and cash flow statements freeing up the finance teams to focus on analysing the data and making informed decisions.

·        Automating auditing - AI can be used to automate the audit process by identifying potential compliance issues and risks. This can help finance teams to ensure that their businesses are following all applicable regulations.

·        Automating fraud detection - AI can be used to develop sophisticated fraud detection systems that can identify suspicious activity more quickly and accurately than traditional methods. This can help finance teams to protect their businesses from financial losses.

TG: What are the benefits of AI to a CFO?
PM: AI offers numerous benefits to a CFO in various aspects of financial management and decision-making. Here are some key advantages of AI for a CFO:

·        Improved decision-making - CFOs & HoFs can make better decisions by providing them with insights from data that would be difficult or impossible to obtain manually. For example, AI can be used to analyse large datasets of historical financial data, market trends, and customer behaviour to identify patterns and opportunities that would be difficult to see with the naked eye. This information can then be used to make more informed decisions about budgeting, forecasting, investment, and risk management.

·        Increased efficiency – By automating the repetitive and time-consuming tasks involved in financial management, such as data entry, reconciliation, and reporting, can free up CFOs and their teams to focus on more strategic and value-added activities.

·        Reduced costs - CFOs could reduce costs by automating tasks, improving efficiency, and reducing errors.

·        Identify Fraud - AI can be used to detect and prevent fraud, which can save CFOs millions of Pounds each year.

·        Enhanced risk management - CFOs will be able to identify and mitigate financial risks by analysing large datasets to identify patterns that may indicate potential problems. By identifying and mitigating these risks, CFOs will be able to protect their businesses from financial losses.

·        Improved compliance - AI can help CFOs to ensure compliance with all applicable financial regulations by automating tasks and identifying potential compliance issues. For example, AI can be used to generate regulatory reports, monitor transactions for suspicious activity, and ensure that tax obligations are met. By automating these tasks, AI can help CFOs to reduce the risk of compliance violations and fines.

TG: How can AI support financial institutions in meeting sustainability and ESG (Environmental, Social, and Governance) reporting requirements?

PM: AI can support financial institutions in meeting sustainability and ESG (Environmental, Social, and Governance) reporting requirements in different ways, including:

·        Data collection and analysis – CFOs will, with the aid of AI tools will be able to collect and analyse large datasets of ESG data which, can be a time-consuming and challenging task manually. Additionally, AI tools can be used to automate the process of extracting ESG data from a variety of legacy sources, such as corporate reports, financial statements and sustainability frameworks.

·        Risk assessment – CFOs will be able to assess their ESG risks by generating reports to analyse ESG data to identify potential risks, such as climate change risk, social unrest risk, and governance risk.CFOs will be able to develop models to predict ESG risks which can help to make more informed decisions about their investments and lending practices.

·        Reporting – The CFO AI will be able to generate ESG reports that are accurate, comprehensive, and compliant with all applicable regulations. AI can be used to automate the process of compiling ESG data, generating reports, and identifying potential compliance issues. AI can also be used to generate customised ESG reports for different stakeholders, such as investors, regulators, and customers.

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