The global impact on food security is one of the major priorities at the COP27 climate summit. Recently the Commonwealth Secretary-General called on other leaders to collaborate and learn from each other to transform their future strategies.

Patricia Scotland, the Commonwealth Secretary-General, emphasised that for countries to deliver a more productive and sustainable agricultural industry and ultimately be more resilient to climate change, we must utilise big data and other digital technology. New digital tools can transform business plans within the agricultural chain and tackle productivity, harvesting, finance and supply chain management issues.

At COP27, Commonwealth Secretary announced a new policy guide focusing specifically on global food security. This guide is one of the first to explore how digital technology impacts the agricultural industry. Scotland believes that this policy guide is a critical step, not only for the Commonwealth but also for small, developing and middle-income nations. The guide supports policy leaders in recognising key areas that can improve and develop this market.

Agriculture is responsible for food security and employment in most Commonwealth member states, with over half of the collective 2.5 billion people residing in rural regions and connected with smallholder farming.
Created by the Commonwealth Connectivity Agenda, the framework discussed in The State of Digital Agriculture in the Commonwealth guide explores various regions based on their current digital technology, infrastructure, and enabling further digital progression and suggesting strategies for progress.

According to the policy guide, while regions like Africa lack some critical data infrastructure, considerable progress has been made through digital innovation, new technologies and services. In Asia, technologies for agriculture have progressed across the region, but overall affordability continues to challenge the most vulnerable communities.

The business development market, financing and investments remain underdeveloped within the Caribbean and Pacific Small Island nations. In Europe, Canada, New Zealand and Australia, smart digital technologies are widely used, and the policy guide encourages other regions to collaborate and learn from these innovations to assist them in making continued progress. While speaking about climate resilience and food security at COP27, Secretary-General Scotland emphasised that further efforts must be made by the public and private sectors to recognise the potential of digital and big data solutions for the agricultural industry.

A recent study by Harvard Business Review suggests companies expect finance teams to be more strategic, collaborative and automated. Increasingly, businesses are requested to provide financial details quickly and support leaders in achieving their goals. Finance professionals are, however, facing the pressures of daily administrative duties, which means fulfilling this strategic role is more challenging than expected. Many industry professionals believe it’s time for finance teams to automate tasks and start focusing on core strategies. 

Finance teams have a tradition of utilising new technologies that make the technical aspects of their jobs faster and simpler. Tech-focused businesses and associated C-suites are adopting automation to accelerate their efficiency and performance. The affordable and improved technology will likely transform the function of a finance team.

Many industries are adopting automation within their accounting teams. Businesses have automated processes delivered by their finance teams, such as financial close, accounts payable, financial planning and analysis. While automation impacts accounting services, there is still much to be done in this industry. According to a Deloitte report from 2020, over 75% of respondents said their business accounting processes are predominantly manual or require significant manual input. Under 4% of respondents suggested that their business has implemented robotic process automation (RPA), while around 2% had integrated machine learning and artificial intelligence (AI). 

Considering the existing economic and financial conditions, geopolitical uncertainties and increased inflation, finance teams are under further pressure to raise their performance levels and focus on their corporate strategy. The Harvard Business study suggested that 89% of finance teams can provide unique and valued input on business challenges. A further 83% believed there is a potential risk to their business if the finance team doesn’t contribute to the overall strategy. However, many believe that finance departments are held back by basic tasks, which prevents them from adopting this more strategic role.

Automation doesn’t necessarily remove humans completely from a process, but it enables machines to focus on repetitive work. While professionals can increase their productivity and drive key business objectives. If finance teams spend a large portion of their time on manual activities, they lose the opportunity to explore data and deliver high-value insights. By automating tasks, finance teams are in a stronger position to add more value. 

In finance, automation enables businesses to identify missing payments and remove potential errors. Automation can improve the analysis of customers and reduce or eliminate findings that can lead to poor decision-making and planning.

Applying automation to financial close

In a Trintech survey, over 50% of financial professionals said that meeting deadlines and timescales were the biggest challenges in the financial close process. Manual processes and reduced use of financial automated solutions can impact the ability to generate insights, particularly when working in a remote or hybrid environment. According to EY, over 60% of CFOs said their closing process is manual. When asked what stopped businesses from implementing the most efficient financial close, lack of automation and manual errors were considered notable factors. There is a growing recognition that manual activities and a lack of automation directly impact the challenges experienced during financial close but many are yet to have a solution to this issue.

Automation presents several benefits, but there are challenges related to the implementation process. Businesses must understand these issues and be prepared to create the necessary solutions. Before launching automation, companies must determine whether to automate their existing workflows or restructure them. Prioritising areas for automation must focus on repetitive tasks that are more likely to incur errors and recurring costs. Financial operations represent the core of many businesses, especially if these changes can be risky. Some solutions require organisations to invest considerably to implement the necessary changes to their systems. 

One of the biggest challenges to overcome is the underlying fear of employees and getting them to invest in the automation process. Some finance members may be concerned about being replaced by automation and other technology. Others may be worried that their team is piloting automation for the rest of the company. It’s critical engaging with employees to eliminate any negative perceptions of the process and highlight the benefits. 

With further technological advancements, businesses may fall behind their competition if they fail to recognise the benefits of automation. Shifting from manual to automated processes can be very beneficial, increasing performance, saving time and reducing the chance of fraud. Finance teams are now a central part of business operations. The CFO today is directly associated with key strategies. As technology becomes more sophisticated, businesses can automate more activities. 

Finance teams are dependent on the continued availability of accurate data. Leveraging data solutions and other technologies are signifcantly beneficial for forward-thinking businesses, creating more insights and widening capabilities. 

Representing data using graphics like charts, animation and infographics are regarded as data visualisation. Visual displays and representing information in this manner help communicate complex data relationships and data-driven insights in a form that makes it simple to understand and determine a structured plan. The primary objective of data visualisation is to assist in recognising patterns and trends from large data sets.

There is a significant volume of data available today, and to generate any benefit from such considerable data, real-time analytics has become critical for all industries, including finance, to gain a competitive edge. The finance industry is experiencing a significant digital transformation and growing pressure to innovate. To achieve this digital transformation is delivered in various ways, and by leveraging data visualisation, the finance industry can utilise benefits like:

A more comprehensive view into customers’ behaviour and needs

Timely financial intelligence to make informed decisions

Enhanced client reports

Innovative fraud detection

Detailed view of risks across the entire business

Some data visualisation tools in the finance industry include:

Risk reporting and analytics – integrating a range of data sources into a singular source can be challenging. This is the case with banks when reporting risks and performance figures. The main challenge is generating reports that highlight the risk areas applicable to the industry, like market credit, operation risk and so on. Data visualisation is the ideal choice in these cases since data can be consolidated in real-time from multiple sources to create reports that can provide visual analysis. Data analytics can also enable quality data checks across sources to generate error-free reports.

-Client reporting and CRM – client relationship management systems and clients’ reports go together for the finance industry. CRMs provide and help improve relationships with customers. Client reports give finance businesses a complete overview of the customer, risk analysis and other things. Integrating big data and data analytics in real-time provides visual reports with clear information required to make informed decisions and support examining client spending patterns and other variables.

Managing liquidity – finance companies must manage liquidity effectively and have real-time access to all liquidity positions such as currency, locations and relevant products. It’s critical to compare financial figures against standard ratios on an ongoing real-time basis. 

Data visualisations make comparisons simpler by providing clear visual reports and risk analysis. Integrating data receipts from other sources provide detailed information to predict and analyse liquidity. 

Customer analysis – determining customer needs and behaviour is a critical part of the finance industry and helps businesses create new products and services to meet customer requirements. By empowering finance businesses to interact with their customers, data visualisation technology can provide them with relevant and modern information to offer financial products created to customer needs.

Integrating with social media – social media is a creative way for finance businesses to market products and improve their relationship with customers. This provides big data which can be integrated with CRM applications. Data visualisation tools can connect all data sources and provide data analytics is very important for these companies. 

Enhanced identification – using data visualisation, the visual results can be produced for any data without managing filters and sorting lots of details. A range of graphs and charts can be generated instantly to highlight specific details. 

Collaborating and sharing data – The reports produced can be shared with multiple teams, simplifying data sharing within a finance business. Teams can collaborate and work together, whether it’s in the exact location or not. 

Detecting trends and anomalies in data – One of the main concerns for a finance company is determining fraud. Reports created with data visuals can help detect patterns that may be overlooked because of the sheer amount of data. These reports can help eliminate the potential for financial fraud. Many financial institutions have separate dashboards for fraud detection and risk management. 

In conclusion, data visualisation is a powerful tool and can significantly support the finance industry. By applying data visualisation services, consultants with experience within the finance industry can create a unique and competitive edge for their customers. 

With the significant advancement of technology, our lives have experienced considerable changes. By leveraging innovative technologies such as AI, ML and Big Data, we are transitioning into a new stage of innovation where industries worldwide are automating manual processes. This has made our lives similar and seamless, and the finance industry has also embraced this shift towards digital.

Artificial intelligence has emerged as a pivotal part of this digital transformation. In a report by McKinsey Global Institute, it’s estimated that utilising AI to improve core finance functions and provide customised services to customers will increase industry value by over $250 million.

A range of innovative tools is continuing to reshape the finance industry, and this is only the beginning. As we progress to the next stage of technological discovery and development, we must explore what role AI will play in disrupting the finance industry, its influence on businesses and how it will create a range of new opportunities.

The finance industry is recognising the significant transformative potential of AI. Industry analysts believe that by leveraging AI, the finance industry can save $1 trillion by 2030. Another study by Narrative Science a few years back suggested that over 30% of financial service businesses had already adopted AI-focused solutions such as predictive analytics and voice recognition services.

The emergence of innovation is predominantly focused on the customer experience. New AI-powered tools like chatbots are becoming a necessity for many new businesses on the front-end experience. Process and task automation and other analytics strengthen and elevate finance services on the back end. As suggested by Gartner, Robotic Process Automation (RPA), as an example, provides a very cost-effective service, amounting to around a third of the compensation provided to an offshore employee and about a fifth provided to an onshore employee. RPA does the manual work, utilising a rule-based system that automates repetitive tasks
AI in finance focuses on machine learning, but automation plays a significant role in banks. The finance industry has benefited considerably from machine learning. Banks can gather and explore vast amounts of finance-related data. Machine learning is a discipline of AI which enables machines to learn and progress by using data and not relying on human intervention.
Voice recognition is another modern innovation that applies AI to perform banking operations through voice commands. At the core of this technology is Natural Language Processing (NLP). This AI-driven technology is used to design a range of virtual assistants and chatbots.
In the financial scene, leveraging AI provides two distinct advantages; firstly a big increase in efficiency, and secondly, reduced stages that could be exploited for fraud. The trend of AI-focused lending initially emerged within the tech startup and was then rapidly adopted by other entities. Since market investment is mostly dominated by individual fund managers, it might be difficult to understand their influence on AI. However, AI-focused funds can considerably reduce the possibilities of human error through their ongoing evolving rules and algorithms.
Other significant factors behind the increasing demand for AI in finance include the development of cheap and efficient resources, the digitisation of financial services and the rise of new data on individuals and organisations.
The progression in advanced technology like Artificial Intelligence has transformed the financial industry. With the rise of next-gen tech applications disrupting the industry, technologies like AI and ML have significant potential to transform the sector for the better. Investment banks and financial startups are now utilising the best AI to enhance profits, maximise efficiency, eliminate errors and generate the best returns.

Automation can support business and the success of the finance function. In terms of the responsibility of CFOs, there is further recognition of the need to integrate digital measures within finance. Many finance leaders, however, focus on strategic challenges while remaining predominantly reliant on traditional systems incapable of delivering the desired results.

Any progress and evolution of the CFO is dependent on innovative tools and is capable of automating selected financial functions. Progress appears when finance shifts from silos to increased integration across the internal value chain. Automation in finance must focus on processes which eradicate the separation of silos within financial activities. Manual, repetitive tasks require automation, optimisation processes and elimination of the possibility of errors, so human intervention is limited and focused on more strategic tasks.

Through automation, financial services can adopt a more performance, value-based approach rather than being the traditional cash manager or gatekeeper. New technologies make it possible for financial processes to deliver results in near real-time to CFOs. Eliminating silos and automating manual tasks means CFOs can reshape the finance industry and their financial skills. Transforming activities means finance professionals can focus on critical business areas.

Simple automation measures for finance can include introducing onboarding performed by suppliers i.e. accessing a portal to input accurate information (which suppliers will likely do to receive prompt payments) will reduce errors significantly. AI/RPA technology can deliver faster, less human-focused invoice and purchase matching, accelerating payment approvals. Automation processes can enhance the overall AP team morale by limiting time spent focused on purchasing supplier enquiries, performing reconciliations and other compliance duties.
CFOs also have a duty to control the risk of fraud. Automation, particularly automating payments can reduce that risk. Manual activities can unintentionally create opportunities for fraud. Deploying automation can validate selected payment processes and ensure incorrect payments do not occur.

Integrating automation offers several operational benefits. Enhancing accuracy and reducing manual data entry is just one aspect. Focusing on improving workflow and process automation is another area. The benefits of automation are diverse, ranging from improved staff morale and retention to transforming finance into a value-centric business.

Failing to consider finance automation can leave CFOs exposed and limited by traditional services. Attempting to meet the strategic challenges of a business when dependent on conventional systems and manual activities can be very challenging. The future of the finance function isn’t focused just on technology, but it is a significant factor to consider. Success will depend on determining how the finance function operates and supports a business.

A new survey of finance professionals found many are unprepared to meet the demands for more insights and information, despite ongoing significant transformation efforts already in place. The national survey from Deloitte’s Centre for Controllership and IMA (The Institute of Management Accountants) discovered that 76% of finance professionals confirm their controllership functions have started their transformation journeys but nearly 95% report additional work i