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. 

At the recent Sibos annual conference, digital innovation was pinpointed as very significant for financial inclusion. Sibos is an annual networking event delivered by Swift for the financial industry. Beginning as a seminar in 1978, the event has developed into a leading forum for the global financial community to explore and collaborate in areas of payments, securities, cash management and trade. This year’s conference agenda prioritised progressive finance for a changing world, with over 500 representatives discussing areas such as supporting the digital landscape to manage uncertain times and promote sustainability.

At the event, digital innovation was discussed as holding tremendous promise for financial inclusion and financial health. The underlying theme of the conference was focusing on progressive finance in a changing world that could not come at a more critical time.
There has been significant progress in the last few years, with approximately a quarter of the global adult population having secured access to financial services. More adults are included in some manner, enabling new opportunities for millions of previously disconnected. Investment in vital digital infrastructure, including enhanced connectivity, has delivered the foundations for further development. The rise of digital payments has spurred a considerable increase in account ownership. In the last few years, nearly 40% of adults in developing economies opened their first account to receive a wage or a government payment. Furthermore, millions of small merchants are either paid or make payments via their phones. This has enabled financial service providers, particularly new fintech players to be more innovative in the delivery of new products. The rise of mobile activity and new customer data channels by leveraging big data and AI means more creative and innovative ways to deliver financial products.

With every new technology, such as digital currencies, we must remember to focus on the problem, the solution, and what future we are visualising to enable long-term success. The conference message discussed that one of the priorities is ensuring innovation doesn’t create harm but delivers key digital services, like cybersecurity and digital literacy, that can support marginalised communities to manage their financial services safely and efficiently. Fairer competition and innovative payment systems were also discussed, as supporting markets work better, including for small-scale customers, but this was considered only the start, and there is the opportunity to move beyond not harm to implement positive changes.

Representatives at the event explained innovation shouldn’t happen just to maximise short-term returns. Instead, we should focus on the value generated in the long run. The value of customers translates into value for firms. Members were asked their opinions on managing their finances, planning and meeting future goals during periods of disruption and building further resilience. All of these factors were considered good business sense since financially healthy customers are better customers, and businesses that can provide these services differentiate themselves from others.

For the moment, only 55% of adults in developing economies can access emergency money within 30 days, and another study indicated that nearly half of respondents from OECD nations have no money left at the end of the month. In some areas, we have witnessed an increase in access to finance and, at the same time, a decline in financial health. We must determine the best solutions to these challenges and bring them to scale. Focusing on finding an approach to solve the reduction in financial health could be through encouraging partnerships that provide services within the entire value chains. Collaboration across the industry and government is critical to creating an inclusive digital infrastructure that enables services beyond finance, like health and education. These represent the foundations of sustainable development. If this is managed correctly, digital innovation holds great potential for financial inclusion and financial health. We should focus on a better future with shared experiences and use events like this to deliver a more secure, trusted and effective digital future that works for everyone.

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.