Financial analytics has become a critical factor for success in modern business. Most companies are starting to invest in big data analytical tools to deliver cost savings and increase revenue and productivity. According to reports, the data analytics market is expected to expand considerably, exceeding $221 billion in 2027.

The rise of technology plays a pivotal role in supporting market growth. At the same time, challenges such as increased competition to changes in customer preferences and compliance rules and financial analytics for companies have become valuable tools for delivering informed decisions and enhanced performance. Financial data analysis provides critical insights into operations and various industry trends, managing risk and resource allocation. Financial data is essential to remain competitive and on top of industry trends.

The Reasons and Benefits of financial analytics for Businesses

Enhanced decision-making: In today’s environment, it’s become even more important for companies to make quick decisions based on transparent and reliable insights. One valuable tool for this process is financial analytics for businesses. By interpreting financial data, companies can determine performance patterns and make critical decisions. Financial analytics enables companies to perform calculated risks. It allows businesses to proceed with data-driven plans that could give them the added boost required to drive further success in the future.

Trend Identification and Analysis
Identifying and measuring trends can be a powerful tool for financial analytics. By measuring data points over a selected period, companies can create valuable insights into their market position, performance and potential growth opportunities. Growth opportunity assessment depends heavily on identifying trends and analysis. Financial service businesses can explore customer behaviours and market conditions to determine new investment products that meet requirements, creating new revenue opportunities.

Managing and mitigating risk
Financial analytics provides tools to measure risk and implement the necessary response. For example, a bank can explore its loan portfolios with financial analytics and introduce actions needed against high-risk loans. The bank can then implement stricter credit plans or increase the rules for collateral to alleviate any potential financial losses. Risk management is an essential part of financial analytics that businesses should consider. Through detailed assessment of financial data, companies can identify potential risks and introduce safeguards to eliminate potential cases of economic loss.

Opportunities to save money: Allocating resources correctly is a vital part of financial analytics for companies that can result in cost savings and higher profits. With the support of financial analytics, a company can measure spending and determine where to invest funds to enhance efficiency and reduce expenses. Cost savings opportunities are a vital part of financial analytics for businesses. By gaining deeper insights into operations and investments, companies can make data-driven decisions that improve success in the long term.

Complete transparency: Financial analytics enables businesses to explore past financial data and use it to predict future scenarios. This predictive element of analytics improves budgeting and forecasts and provides organisations with the necessary details to prepare for market changes or impacts on resource allocations. Overall, investing in financial analytics for budgeting and forecasting enables companies to have more clarity when allocating resources, maximising potential profits and reducing overall expenses.

Creating a competitive advantage – financial analytics gives businesses a competitive advantage. By utilising financial insights, companies can understand trends and patterns that could be missed by competitors. For example, analytics can determine customer purchasing behaviours and which demographic prefers online transactions. With this level of data, companies can be more strategic with resource allocations and develop marketing campaigns to attract new customers.

Detecting and preventing fraud: Businesses can greatly benefit from financial analytics by minimising potential fraud cases. Fraudulent activities can be very damaging, financially and on a reputational basis. Financial analytics can provide insights into suspicious customer behaviour, like large transactions from various locations.
Regulatory compliance – Remaining compliant with current regulations is critical in operating a successful business. Companies must be aware of all relevant legislation and take action to remain compliant. By having access to financial information and detecting any possible compliance issues, businesses can initiate the necessary steps. Financial analytics can support the delivery of more thorough audits, ensuring they are compliant with all regulations.

Allocating resources effectively: Maximising resource efficiency is an advantage of utilising financial analytics. Businesses can assess their data to determine ways to lower costs, enhance operational productivity and create new growth opportunities. By accurately measuring and understanding data, businesses can utilise critical resources and position themselves for long-term success.

Improving communication with stakeholders: Financial analytics has proven critical for stakeholder communication. It enables businesses to deliver transparent and structured reports and digital insights on financial performance that build stakeholder trust and confidence. Furthermore, improved forecasting options help stakeholders understand the business in more detail and its future development plans. Analytical tools enable more informed strategic decisions, increasing transparency and positioning them for long-term success.

Adapting and transforming business activities during challenging times is vital. According to EY, progression and future success are more likely if CFOs can focus on six complex human-based factors. CFOs recognise from experience that successful transformation is challenging and requires their input. 

A recent study between EY and the University of Oxford Said Business School discovered that at least three-quarters of CFOs have experienced some form of transformation over the last five years, but many CFOs still fail to recognise that acceptance from other employees is critical in determining the progress of transformation. Research indicates that successful transformation leaders are more efficient at managing workplace stress and pressure, and by managing these six key factors, they increase the potential of transformation considerably. 

Key drivers of transformation success for CFOs

1. Inspire: create a vision that is presented to all and represents a comprehensive explanation of ‘why’. Business leaders may not recognise the importance a vision can have in terms of inspiring others and creating a sense of purpose. The time and investment spent on delivering a vision can be lost. About half of the finance workforce affected by a successful transformation plan stated that didn’t clearly understand the leadership vision.

CFOs may not value the power of a shared purpose in inspiring teams. According to the study, CFOs must maintain the human aspect of transformation as a priority. Leaders need a good understanding of the future and its impact on individuals and groups. Generally, CFOs will consider program milestones and business goals rather than personal and individual targets. CFOs must invest in a plan that supports individual journeys to provide people with a sense of ownership, belonging and control of their positions.

2. Create an empathetic and authentic leadership plan that aligns with the finance vision. Successful transformation needs leaders to show courage and empathy, especially around workforce expectations and priorities. While clarity of the vision is important for gaining momentum, CFOs must demonstrate empathy, and show connections between the transformation vision and the benefits to the business and the workforce.

3. Purposely build an environment that supports the workforce and their roles. Successful transformation requires people to invest and commit to the journey. While leadership is vital, creating a transformation culture where everyone feels engaged in the journey is even more necessary. In the EY survey, 46% of finance leaders welcomed ideas from junior staff members, and only 31% of finance employees believes leaders listened to their ideas. CFOs must focus on the personal aspect of transformation and ensure people feel empowered and capable of voicing their opinions. With this in mind, CFOs must actively listen and respond to employee feedback.

4. Empower – delegate decisions and focus on delivering a culture of safety testing. Transformation journeys are not set in stone and can change depending on certain events. In the EY study, successful transformation leaders suggest that taking a step back or changing paths wasn’t necessarily a bad idea. Leaders must set expectations that can adapt when needed and communicate the changes transparently and as early as possible. Traditional finance functions on a basis that requires precision and working to specific metrics at particular intervals. This approach creates a culture of no surprises, which can at times, hinder innovation. The study suggests that finance leaders were more inclined to believe that failed testing would result in a negative impact on their careers, but as transformation becomes more regular, CFOs must encourage creativity and innovation that ensures their business is capable of adapting and learning. CFOs must create a safe environment, ensuring people feel welcome to experiment and test without negatively impacting their careers. 

5. Construct a way of showing how technology will deliver the financial vision. Blending technology with the necessary skills is critical in enabling transformation. Innovative technology is often a priority for finance leadership transformation plans. The study shows that 38% of CFOs identified technology and digital innovation as top priorities for accelerating transformation. That said, only 40% of senior finance leaders, including CFOs, determined technology as the top three challenges in delivering a successful transformation. 

6. Collaboration: create a plan for collaboration, and deliver new ways of working. While nearly half of the finance leaders believe processes were created to deliver collaboration within the business during transformation, only 31% of finance employees agreed with this. The gap here is critical when compared to other functions. It suggests the bigger challenge that finance professionals don’t feel that leaders are finding or valuing their efforts during the transformation. To increase success, EY research suggests that creating a space for new ways of thinking is essential. CFOs must segment siloed and hierarchical ways of working, and implement a multi-discipline approach that enables new perspectives and allows everyone to be involved in the transformation.

Transformation success will come from putting people at the forefront of new plans. CFOs have a holistic view of a business and are well-positioned to determine the tone of practices required for transformation. Today’s CFO must consciously focus on empowering people and lead with a vision with a ‘we’ not ‘me’ approach. 

Data has become the new currency in today’s financial landscape, and the fintech industry is leading the way by leveraging technology to tackle challenges and deliver better financial solutions.

Financial businesses are competing to transform their activities, and with the existing economic conditions, customers are demanding far more services and solutions, with increasing availability of new data, new data management policies and the potential of cyber attacks rising. The various ways of managing data can be vital tool to tackle challenges in the finance industry. Fintech has transformed traditional banking, delivering innovation to a market previously considered unchangeable. New businesses have challenged the norm, driving financial companies to change and move away from legacy systems.

There is now a significant opportunity for finance companies to use the data available in fintech. This will help companies work through the new landscape and improve data access, leading to more effective customer-focused services and enabling banks to remain competitive in a digital world.

Data stands at the core of financial services, from credit ratings to regulatory compliance and fraud detection. The volume of data available in finance is considerable, and the demand to explore and measure this information is more critical than ever. There are several key areas where fintech can drive improvements in access to data for finance companies.

Firstly, data security is a top priority for all businesses as cyber-attacks are rising, with studies suggesting that businesses experienced a 77% increase in attacks in 2022. This figure represents a significant threat for financial companies as finance holds valuable information that makes businesses potentially more vulnerable to cyber security threats. The fintech industry offers innovative ways to protect data via advanced encryption processes, sophisticated authentication and blockchain-focused solutions. These progressive forms of technology can support finance companies in protecting customer information, building stronger relationships and defending themselves against possible reputational and financial loss.

Delivering a more flexible approach

Data interoperability is critical in today’s financial ecosystem. Customers increasingly depend on various financial providers, while demanding an effective experience and customer service. Existing legacy systems used by many incumbents often lack the flexibility and available services needed for seamless data exchange, resulting in relatively slow and unstructured customer service.
Fintech companies offer solutions to these challenges, utilising open banking processes and APIs, enabling the integration of services between various groups, and improving collaboration and data sharing.

The enhanced use of data can improve business operations by changing the way financial companies determine plans, manage risk and support their customers. Data-focused decision-making, supported by new techs like AI, ML and big data analytics is all possible because of solutions presented in the fintech industry.

The fintech industry can strengthen the financial sector by providing solutions that can improve operations and enable companies to create services that meet customer needs and ensure they remain competitive. By rethinking how we use data and utilising the potential of fintech, finance companies can streamline their operations, improve customer experience and make better decisions, driving growth and increasing competitiveness in the industry.

The fintech industry has a significant opportunity to generate positive changes and improve data access for finance companies. It is the responsibility of the finance industry to recognise and implement the services available and the fintech providers to continue generating new solutions to improve operations. Through collaboration, the fintech industry can reshape traditional finance companies, unravelling a reformed, efficient and secure financial future while enabling a customer-focused approach leading to accelerated future business growth.

Operational efficiency is a priority for corporate leaders, with AI gaining accelerated traction across industries. While AI has shown multiple benefits and shown significant results, those in regulated industries like finance, are raising specific questions concerning security, data validity and general ethics surrounding AI, especially regarding data privacy. Whether a finance-focused business is applying AI to improve contract management, provide a better customer experience or improve fraud detection, the measures controlling how data is used and retained remain critical.

Colby Mangonon, Associate General Counsel at Evisort believes that financial, legal, IT and operations teams should assess the appropriate data privacy regulations when planning to integrate AI to ensure they are compliant and avoid any potential issues with customers, stakeholders or regulatory groups. Mangonon believes that finance businesses should ensure integrating AI is protected by a structured information security framework and data processing policies to safeguard customer data.

Applying AI to finance

As finance businesses develop their technology stacks to improve efficiencies, many have reinforced their technology with AI-focused solutions to enhance the results of their operations. Some finance companies have started applying OpenAI’s GPT products to enable advisors to deliver vital research and data. For example, a payment processing leader is leveraging AI to differentiate between authentic and mistaken fraud detection and avoid card declines. Another financial business is applying AI to deliver customised contracts and digitally work with internal stakeholders to meet all requirements. AI also delivers multiple opportunities to enhance revenue-focused operations, like accelerating customer services like loan processing or onboarding.

Aside from the benefits, the legal aspect within finance businesses is very aware of the challenges AI presents with privacy and security for customers, stakeholders and business data.

Concerns over Artificial Intelligence (AI)

While AI-driven technology can be very useful for daily operations, there are some concerns about the specifics of data at the business level. Some questions are more specific when exploring generative AI models. For example, ChatGPT has already received added scrutinisation while governing bodies explore the potential legal implications of applying this technology. For example, Italy recently banned the platform, with other EU nations raising concerns about how AI-related data tools meet the standards of GDPR.

Aside from the regulatory concerns, several financial businesses are cautious of using public third-party AI tools for fear that data could be exposed. Leading organisations like Goldman Sachs Group and JP Morgan have temporarily banned using ChatGPT for business communications while they determine a safe and effective way to apply these technologies.

These concerns don’t mean we should avoid AI to protect data in finance, but it means in legal teams must carefully consider each solution to ensure they meet regulatory standards for data privacy and security. Protecting your business when applying AI requires a deep understanding of the specifics and the parameters used to build their technology. Finance leaders should determine the specific data planning to implement into an AI model, as this plays a critical role in selecting the best platform for your organisation.

When exploring business solutions, businesses should consider the following: what are the AI data training practices used, what are the security frameworks and measures, and is the provider using a custom AI model or a third party?

Being careful in examining AI solutions, finance leaders can leverage all the benefits of AI and continue to remain compliant with regulatory standards while eliminating the risk of compromising data.

As AI continues to gain traction in the enterprise tech landscape, legal teams within finance companies will be responsible for meeting data privacy standards and allowing businesses to enhance their operations. With this mindset and a structured approach, businesses can deliver better outcomes and create a competitive edge.