Predictive analytics is becoming a critical tool for businesses looking to determine the results of key decisions before committing to them. The benefits are evident but implementing the tech can be a challenge. With rising inflation impacting costs and fears of recession affecting demand for services, companies across the country are decreasing their spending and exploring new growth opportunities.

Identifying where, when and how much to invest is critical, but it’s vital during a challenging downturn when choices can have a profound impact on the growth prospects of your business once the economy recovers. In an attempt to adapt their investment plans, companies are increasingly applying predictive analytics to support them in assessing opportunities and risks. 

James Petter, VP of data storage business Pure Storage, believes risk management is a major discussion point among CFOs and regulatory teams, especially in the current economic climate. Senior leaders consider risk management a top priority, assessing their economics, financial structures and technologies. Businesses contain lots of data, and most are trying to determine how to use this information. Often, companies are focused on the current market conditions and responding to these but moving forward, there is likely to be more of a push on looking ahead, and predictive analytics will play a significant part in this. The rise of predictive analytics is no surprise to Shankar Balakrishnan, VP for Europe at Anaplan. Balakrishnan refers to businesses using historical data to navigate challenging times as someone driving by only using their rear-view mirror. Balakrishnan believes companies must utilise more data on potential outcomes and react smarter to possible disruption. Anaplan recently partnered with the South Central Ambulance Service Foundation NHS Trust to support its predictive potential. By applying machine learning and predictive insights to their data, Anaplan determined the number of emergency call the ambulance teams would receive at any given time. This process allowed the trust to deliver resources more efficiently. 

The challenge of implementing predictive analytics 

For finance leaders, the challenge is understanding what to focus on. One initial area to work on is automating functions in the back office. Applying technology, such as robotic process automation and AI-focused data analytics, improves the processes, tackles skills gaps and improves efficiency. It can also provide intelligence that can support forecasting and planning. Automation like this allows employees to focus more on value-added tasks.

Bearing in mind the potential risk and uncertainties, few leaders will want to make critical investments and resourcing plans on instinct. Risk management may be a priority in a crisis, but can business leaders avoid this crisis in the first place? Whether it’s a pandemic or cyber attack, making effective plans under pressure requires accurate and data-focused insights. Successful risk management needs data to deliver various scenarios and options. For example, in the travel and tourism industry, predictive analytics may prove critical to enable them to recover from significant disruption experienced after Covid. Aircraft manufacturers are using technology to find the best times to perform maintenance tasks, and airlines are using similar technologies to predict demand for flights and plan their staffing and fuelling requirements. Quality data and predictive analytics are critical to risk mitigation within the finance industry. They are vital for fraud detection, auditing and other types of advanced work.

The overall success of this technology depends on the quality of data fed into the system. Insights created on incomplete inputs could be misleading and potentially cause harm to a business. Implementing predictive analytics isn’t a one-time process. It takes time and effort to examine the findings, understand them and alter the system accordingly. It’s important to have clear goals when implementing analytics, adapt them when necessary and continuously revisit them to ensure the business is getting what it needs. Accuracy and compatibility are critical when measuring performance across various teams.

If leaders work with inaccurate data, they risk making inaccurate decisions. Similarly, if teams spend hours validating data, it makes the entire process impossible for decision-makers to react quickly. Despite the challenges, the benefits of predictive analytics are clear. With the insights it delivers, predictive analytics offers significant value for business leaders, converting data into critical information for a business.

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.

As finance businesses continue to evolve their services and offerings, a new approach towards data and analytics is needed to meet rising demands.

Big data and analytics are important elements of today’s finance industry and go in collaboration with the challenge in improving the capabilities of data management for finance businesses. The key question is how do data analytical tools and technologies add further value to the financial services industry?

New data-focused services can improve revenues and overall costs reduced, improving competitiveness. Security can provide customers with enhanced and safer services. Successful AI-focused businesses target their service to the new era of tech-savvy millennials. 

Emerging fintech is unravelling the power of big data to determine customer behaviour and create structured risk assessments, which can set them apart from other established financial institutions. The speed of real-time data enables disruptive fintech and challenger banks the ability to adapt to a rapidly changing industry, along with a more comprehensive understanding of customer relationships.

Customer-focused analytics has become a key priority. This is a significant transformation from the past when the financial industry was mainly product-focused. Data insights, systems and operations are focused on the customer. As a result, it’s critical to understand how to determine changing markets and customer requirements.

Risk management has improved and digitisation has established the way for automation by increasing agility and innovation, as well as generating revenue for data. Data analytics has also made regulatory compliance simpler by establishing a platform for a business and enabling real-time frameworks with regulators. Realising the value of big data requires an analytical perspective as this support transforming data into valuable insights.

This is where a data analyst comes into play. Big data analysts recognise this process and what information to look for that will translate into value and enhanced customer satisfaction.

Rates of adoption for business intelligence platforms are rising as more businesses integrate with big data, seeking to enhance findings from large data sets. Digitisation in finance has allowed disruptive technologies such as advanced data analytics, AI, machine learning, big data to transform how fintech can compete in the market. Data analytical tools have become more sophisticated and so are more necessary to businesses today.

As the finance industry works towards a data-driven priority, businesses need to react to these changes in a structured manner. Those looking to remain competitive must be willing to adapt and understand how to use data skills on the job.

Artificial Intelligence or AI has transformed the financial services industry worldwide. In just a few years, the industry has become more dependent on technology supporting data aggregation, security, products and services. The initial launch of AI technology primarily focused on deriving insights. Since then, the adoption of AI has progressed to other areas of the finance industry, including fraud detection, customer identity and other authentication techniques.

The finance industry is continuing to automate and improve various areas of business with robotics and AI. We are likely to continue seeing a shift towards accelerated machine learning in enhancing human impact across the business. AI and ML have already established a better understanding of customer behaviours and preferences, enabling the finance industry to create a more personalised approach at scale and improve the overall customer experience. Moving forward, this element of AI will become even more important in the finance industry. The ability to provide a more custom and personal customer experience is valuable in finance. AI sits at the core of delivering these features. It can be in the form of personal loan offerings based on a range of parameters. Customers no longer need to select off the shelf products. Instead, individuals have access to unique offerings designed especially for them. AI-powered lending plans is another emerging trend. Portfolio management and retirement planning with the support of AI can deliver intelligent investment plans tailored to each individual.

As the finance landscape continues evolving, we will likely see emerging regulations beyond protecting bank data and other personal information. Having the power to detect trends in large data sets, AI can determine unique information based on data, such as online purchases or website visitors. 

The finance industry has the opportunity to select from a wide range of use cases to determine how they can apply AI to their advantage. They also have the data available to leverage the insights and deliver value for their customers and clients. Incumbent businesses will need to adapt and explore their operations, shift away from legacy processes and harness the real benefits of AI. With AI still evolving, early adopters of this industry will likely gain a significant advantage and the necessary experience to succeed. Businesses that fail to adopt these measures until established will risk falling behind their competitors in the future.

In terms of fintech, AI offers several disruptive opportunities. While these may present a threat to the incumbent banks, there are also many opportunities for traditional banks to partner with fintech. Banks have the added advantage of having an existing large customer base, while fintech has access to new technology and AI features. With the right plan in place, there is a chance to deliver a win-win situation for banks, fintech and the customer. Over the next few years, we will likely see a rise in automated technology interacting with the end-user. With the pandemic showing the importance of remote services, bots and other similar technology will become even more familiar in the finance world. A recent survey by EY discovered that 64% of financial businesses plan to significantly increase the use of AI technology within the next two years. Analysts believe AI will become a vital part of the finance industry, generating new revenue channels and automating processes to enhance the customer experience. No area of the finance sector is likely to remain disconnected from AI in the future. 

The Fintech industry has generated significant changes, disrupting many industries, particularly the financial sector. Fintech has created several benefits in finance, improving payments processing, insurance and money lending. The rise of fintech has provided a unique customer experience and enabled people to embrace the transition to fintech.

The majority of fintech customers tend to be choosing traditional financial institutions as there are several challenges that fintech needs to tackle to continue this technological revolution. Some of the main areas to focus on relating to trust, transparency, security and customer trends. 

Security and User Privacy

Across Europe, the use of financial technology increased by over 70% during 2020, supported by considerable investments into fintech. A rise like this comes with new challenges, one of which is developing new security concerns. Cybersecurity cases are rising, and unfortunately, fintech businesses are a prime target for cyberattacks. The fintech industry holds significant valuable information that needs to be protected.

Maintaining a grasp of new technology

According to a recent survey by Gartner, over 50% of financial services CIOs believe that most businesses will work with digital technology and that these channels will yield higher revenue and value. This statement emphasises the importance of fintech on the future of business performance.

Businesses that rely on traditional management systems will not keep the competitive edge needed to maintain momentum with the shift towards digital technologies. Many companies consider the transition to digital as a necessity rather than just being a good idea.

Emerging technologies such as cloud computing, AI, ML and big data offer several benefits for businesses looking to reduce overheads. They also provide the potential to improve the overall user experience. The move to these technologies, however, does come with initial costs and some risks.

AI provides a considerable competitive advantage by creating deeper insights into customer behaviours, enabling financial businesses to assign the right product to the right customer at the right time.

The Quality of Software

Finance businesses that apply the latest business technology create an advantage in the journey towards digital. The ability of new cloud technologies depends on flexibility and scalability. Having flexibility means cloud technology can enable systems to evolve alongside a business. Successful fintech businesses are dependent on reliable IT technology resources.

Industry Regulations

Regulatory compliance has become a challenge within the finance sector due mainly to the rise in regulatory fees attached to earnings and credit losses. There is a growing number of regulations that financial businesses must comply with, and compliance can present added pressures on resources.

The future of the fintech industry is relatively clear. Financial technology is going to have a significant influence on the finance industry. Developing a functional financial solution will require considering all of the challenges mentioned.

Leading global analyst provider Gartner has recently confirmed the release of it’s latest Magic Quadrant for Cloud Financial Planning and Analysis Solutions.

Analytics remains a vital element of new software technology, particularly within the last year. Gartner believes that automation will be the main driver for new product purchases over the next year within business intelligence and analytics, including data science and embedded BI. Gartner has also forecast that nearly half of all analytic queries to be performed via search, automation, voice or natural language.

The rise of natural language and conversation analytics will generate a new wave of technology users within the BI and Analytical arena. It is due to this uptake that Gartner believes we will experience a rise of nearly 15% of these tools in enterprises, with significant growth of data and analytics users within businesses. Analysts at Gartner also believe that this rate of growth will stimulate other innovative businesses to modify their business models.

The latest Gartner report outlines of the development of ‘modern’ analytics and business intelligence tools over the last few years. Traditional platforms are being transformed by the development of augmented analytics and machine learning, as well as the rise of visual-based data system providers. Gartner states that those leading the natural language processing arena are more likely to be capable of setting a higher pricing level for their products compared to their competitors.

In their latest Magic Quadrant, Gartner summarises the overall strengths and weaknesses of over 20 key providers, regarded as the most significant within their market. Gartner provides a graphical representation of vendor performance based on their overall ability to execute and their ability to reach their overall vision. The graph is split into four quadrants: nice players, challengers, visionaries, and leaders. 

Based on last year, Microsoft and Tableau were regarded as market leaders in this space. This year, Gartner has placed Microsoft in a more commanding lead, improving its position on the ‘ability to execute’ section of the Gartner graph. Microsoft provides excellent functions, especially for its price, enabling users to perform detailed analysis relatively easily. Gartner believes that Microsoft will remain a leader for some years to come. Tableau, however, has recently announced new natural language processing and automated data management services which strengthen its portfolio further.

Qlik maintained its leadership status based on Gartner’s definition of consisting of a strong product roadmap and its global reach compared to other competitors. Other mentioned businesses include ThoughSpot, a business that is leading the augmented analytics industry. The business raised nearly $150 million in new venture capital and released ThoughtSpot5 last year, containing its innovative voice-driven analytics systems referred to as SearchIQ.

In terms of challenges, Gartner highlight Microstrategy as a key business. The company has invested heavily in augmented analytic services and has received high customer scores based on its range of product capabilities. The system also enables detailed analysis of large data sets and recently launched a new offering which it describes as a ‘new class of enterprise intelligence’, known as HyperIntelligence.

WIthin the Visionaries section, Gartner highlight TIBCO Software, Sisense, and Salesforce as nearly equal leaders and all having the potential to be the leader in 2020. Gartner suggests that TIBCO showed the most improvement in the last year due to a number of recent acquisitions which have enabled them to expand their offering in data science and management. The business also improved its embedded analytics product and launched a new AI analytical tool known as Spotfire X. Sisense raises dits funding to $200 million showing its interest in acquiring enterprise-level customers. The business has emphasized its focus on machine learning and launched a new Data Cognition Engine that can understand large data volumes and can produce nearly instant analytical responses.

Within the Niche Players, this year are more traditional BI providers such as Oracle, IBM, and Board International, as well as more specialist embedded analytical providers like Logi Analytics and GoodData. One business, in particular, Looker, gained the highest increase within this section, ending the year with a growth funding round valued at $100 million. The business also released new integrations for data science workflows and new developer tools in Looker 6, as well as integration with Google BigQuery.

Implementing digital technology can create a number of challenges to financial operations. Investment business The Carlyle Group recently launched a CPM platform to support its business objectives.

With the continued rise of digital technology, financial businesses and utilizing innovative systems to transform people and processes to enhance business performance through an improved and more flexible service. Through the implementation of new technology, businesses are creating more time to focus on analysis and improving their overall strategic decision-making process.

A few years ago, investment company Carlyle Group started exploring new methods to support digital technology within its financial and enterprise systems that provided a simplistic and easier option to their existing services. At this time, the group utilized three separate systems for planning, budgeting, and forecasting but intended to launch one system that could integrate all of these services into one platform. Carlyle Groups financial planning and analysis group used SAP Business Objects Planning, a traditional tool that no longer provided options to support annual budgeting, quarterly forecasting, and long term plans. Carlyle Group was focusing a lot of time and effort on consolidating and handling information due to technical limitations faced with their systems in place. The Group highlighted that its existing Hyperion Financial Management system required significant customization to meet business needs. The business also relied on a custom HR budgeting and forecasting service that met the needs of a complex investment business but was a single-user system and required added support with excel-based data integrations.

To progress further into the digital era, Carlyle Group knew they would need to implement a more modern, flexible platform, capable of scaling to meet its existing and future business needs. Carlyle explored a range of tools to determine which one suited the company from an FP&A perspective. In the end, the business picked OneStream Software LLC integrated CPM platform.

OneStream operated in the cloud or on-premise and allows businesses to focus on reporting, budgeting and forecasting, all within one integrated system. The CPM platform can tackle the requirements of most businesses as well as the more complex reporting needs of other companies and specific groups.

Financial benefits of the move Carlyle Group selected OneStream for its budgeting, planning and forecasting services but the platform also supported their consolidation and reporting processes, combining this area into one platform. Aside from the productivity benefits, the business also experienced an improvement in their IT infrastructure, making life much easier for both users and system managers. The new platform means a reduction in data movement between systems, making it easier to manage and implement periodic upgrades. So instead of launching a series of upgrades to multiple systems that can take some time, the group can upgrade one application in a matter of hours. OneStream has met all the requirements of Carlyle Group. Through the delivery of a single platform, all data is gathered in one place, making processes simpler and quicker.

The business now has much more access to information and has greatly reduced manual, time-consuming data tasks. Carlyle Group has also highlighted a number of other notable benefits, such a reduction in consolidation times by over 50%, despite a massive surge in data generated. Standard processes that previously took up to a week to deliver, such as expense budget updates, can now be implemented in the same day, in literally a few minutes. Since implementing the new system, the group has expanded their use of the OneStream platform by developing point planning solutions for specific expense areas, generating scenario models to support business strategy and review discussions.

In today’s business world there are a number of emerging trends that are impacting and influencing the digital workplace. The rise of AI and machine learning is, for many, a decisive factor that has raised engagement and empowered people. New insights enable businesses to utilise tools and applications to deliver their jobs. By following how people use these systems, machine learning can create learning pathways to the individual to enhance their use of a service, increasing efficiency and productivity levels further.

The focus on engagement and empowerment and the rise of user adoption of other platforms are transforming the way businesses work with technology partners. Users are now expecting suppliers to have adoption management specialists and have a specific management methodology to implement new technologies within the workplace. The level of adoption and user satisfaction is becoming a specific factor to measure overall performance. Applying this process can empower employees to generate better outcomes.

The rise of innovative and intelligent technology

Technology today is capable of gathering information from users and implementing changes to their functionality to enhance user experience and improve business activities. Many businesses are applying machine learning processes to analyse business activities and monitor any changes or potential disruption to their overall business. Performance. Such techniques are enhancing efficiency, saving money and improving overall business performance levels.

A streamlined, more simplistic service

In order for certain application to integrate with other systems that employees commonly use today, there is a growing trend of a more simplistic user interface emerging. Recent innovations have enabled a certain task to become simpler by using a streamlined and user-friendly system. Despite this ‘simplistic’ shift in devices, many experts highlight that applications are still continuing to become more intelligent.

A smarter digital workplace

May clients are keen to explore methods of enhancing their digital workplace strategy and design a brand that really makes them stand out from others. The emergence of smart spaces, that focus on combining environments with people and processes to generate higher levels of efficiency and productivity.

The business of the future is looking at taking a more holistic approach, combining HR, Finance, IT and other business areas together to deliver a collaborative strategy that promotes culture, enhances inclusion and is more cost-efficient. Many clients have adopted a smart space strategy resulting in massive energy saving costs by measuring multiple sources of data on heating, cooling, weather and other factors.

Machine learning and analytics can play a critical part in optimising space utilisation. Due to recent accounting regulation changes, space expenses for a business are clearly visible on balance sheets. This means many businesses are looking for ways to reduce their overall office space footprint whilst continuing to maintain high levels of employee satisfaction.

Some businesses are utilising data from other relevant room-booking applications, combined with Wi-Fi and sensor information to determine where people are and how they are working together. Other businesses are designing physical collaborative areas as an alternative option to underused video-conferencing services and are experiencing an increase in engagement and a reduction in costs.

Data authenticity is clearly on the main agenda

Data has become an essential tool for businesses to achieve their underlying goals. This growing reliance on data, however, has generated concerns with the use of unverified data sources. Research by Accenture suggested that nearly 80% of business executives believe that companies are implementing their most critical systems and strategies based on data, yet many have not invested in the systems to verify the authenticity of the data. If analytical professionals avoid the verification of data their decisions could potentially be detrimental to the business. For those that are implementing verification, strategies rely on machine learning to verify data from various applications, smart space and employee engagement, enabling accurate assessments and the ability to continuously improve their business processes.

Some leading businesses are utilising machine learning to predict financial results. These companies have confidence in ML to generate a more accurate prediction of what their figures will be in the future. Data verification is a growing trend and represents another part of the bigger movement towards collaborating to create solutions.
Analysts believe that throughout this year, businesses will be more proactive to engage and empower their employees. IT teams will likely increase their efforts to communicate with employees to create a better understanding of how technology can really empower their everyday lives. AI and Machine Learning will play a pivotal role in this new trend of engaging and empowering people.

Through further insights, IT can display the tools and applications available to employees and display everything that can be done to perform their jobs to their best ability. Through a better understanding of how people use applications, machine learning can create learning pathways to each individual to enhance the adoption of specific services, increasing both efficiency and productivity.

German enterprise business SAP has confirmed it is planning to expand into the Chinese market by exploring new partners within the nation.

In the last year, SAP expanded its cloud solutions for businesses operating on the Alibaba Cloud platform, a section of the Chinese e-commerce leader. Within the agreement, both businesses announced they would collaborate on innovation and commercialisation of new products.

At the World Economic Forum in China, Deepak Krishnamurthy, the Executive Vice President of China stated to media that the business believes in the partnership model and equally believes in focusing on innovation in the Chinese market. Krishnamurthy highlights that they have over 3,000 developers within China and are working on a significant acceleration plan for the nation. SAP believes there is an existing opportunity gap in China, stating that around half of businesses in the U.S. and Europe are currently looking at smart factory solutions, compared to a lower rate of around 25% in China.

Krishnamurthy highlights that SAP customers are within globally connected supply chains, and SAP can support customers manage their supply chain choices by utilising data streams.
Current trade battles between the U.S. and China have caused disruption to trade flows. Businesses are shifting their manufacturing activities from China into other regions within Southeast Asia. Importers from the U.S. and China are also exploring products from other areas that are not affected by tariffs.

Other analysts suggest that as businesses look to move their supply chains into the Southeast Asian region, small and medium companies will implement new technologies into their daily operations, that could lead to a significant opportunity believed to be in the value of $1 trillion.

Syncfusion has released its latest product, the Bold BI, a detailed cloud-based business intelligence platform. The enterprise solution will provide companies of all sizes with complete access to new data insights.

Bold BI will enable analysts and other users to generate innovative dashboards and also includes a detailed data integration platform to manage complex data tasks. Bold BI connects the process of raw data and generating actual insights in record time.

Daniel Jebaraj, the VP of Syncfusion explains how excited they are to announce the availability of the Bold BI platform, highlighting that they have been developing leading software systems since 2001. Jebaraj states that their systems are utilised by many business intelligence companies today.

With years of experience in developing business intelligence solutions, Syncfusion was able to deliver a unique system. Jeberaj believes that Syncfusion has created a solution that means companies are no longer required to select a specific employee or team to understand their data. Bold BI will allow most mid-sized companies to access data insights that can really influence their business.

The Bold BI platform will provide integration with over 80 common data systems including Azure AQL Data Warehouse, Oracle and Microsoft SQL Server. Bold BI also includes the following features:

-The ability to collect data from multiple sources generating insights across entire data sets.

-Complete end-to-end support from onboarding to completing the product

-Drag and drop custom features

-Real-time operation via the interactive dashboards

-Complete integration with Office 365 and Active Directory

Jebaraj explains that it is easy to exclude human support as an additional feature, but Syncfusion believes this is what makes Bold BI unique and so useful. Users of Bold BI who experience challenges can utilise the support teams at Syncfusion to assist with their projects. In short, Syncfusion wants their users to succeed and Jebaraj highlights that they are committed to providing both the tools and the experience to achieve this.

Bold BI provides solutions for a number of industries including finance, IT, insurance, healthcare and telecommunications.

About Syncfusion

Syncfusion is a leading enterprise technology provider for software development, providing a range of web, mobile and desktop systems. Over the years Syncfusion has become a trusted global partner for many complex applications. Today, the business has over 12,000 customers, including established financial businesses, large IT consultancies and Fortune 100 companies.