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.
Coaching professionals in the finance industry believe that finance transformation will become one of the most in-demand skills over the next few years.
As roles continue to evolve after the pandemic, many new skills are becoming more in demand for finance professionals. Having specific knowledge of recovery management, innovation, new technology and building agile finance transformation plans are some of the skillsets emerging.
The strategy adopted for hiring these particular skill sets is complex. Some positions are likely to be required on a more regular basis. Finance professionals are seeking people capable of finding solutions and supporting further growth for the long term.
On the other side, businesses that recognise their finance transformation will take several years are hiring professionals with the necessary skills on a contract basis, recognising that the role will be more short-lived. In other words, there will be individuals moving into positions that will only be required for a short time and, once completed, will likely move on to another business and possibly do a similar job on a larger scale.
The concept of a technological transformation in finance was discussed back in 2018 when Deloitte released a series of predictions relating to digital technology for CFOs, assessing how the finance world would change in the future. Deloitte explored what finance leaders doing and what technology was available and asking exactly how finance could add more to the success of a business.
One prediction from the report was that the proliferation of APIs would encourage further data standardisation but that many businesses would find it challenging to manage and clean up their data.
Many companies fail to implement all of the necessary steps to align and integrate data, which ultimately means, they miss all the potential of this digital transformation.
Finance analysts don’t believe businesses are going to run out of opportunities within finance transformation anytime soon. Two of the main skills required in the coming years is finance transformation, combined with the appropriate data analytics skills to maximise the increased volume of data produced in the future. Individuals that are well trained and have strong knowledge of finance transformation will be very much in demand.
The combination of digital technology with the rising demand for talent are two trends reshaping the finance industry. Businesses are facing challenges of transitioning to digital and the importance of the finance function in this transformation.
The challenges faced during 2020 created the impetus for many to adapt and integrate new digital services that appeal to their customers. The function of the CFO has been critical in driving this digital transition. IT, strategy and business leaders are vital in assessing business opportunities and ensuring the most efficient allocation of revenue and capital. The finance team consistently adapts processes to ensure the business remains focused on transforming rather than repetitive traditional tasks that hinder overall performance.
The function of the CFO has also had to embrace its digital transformation. By reshaping particular areas of the role with a digital-focused approach, businesses can leverage the potential growth of an organisation.
The pandemic also showed the importance of real-time data and the speed and agility of analytics. During Covid, many businesses responded quickly to technology investments, allowing employees the right tools to perform vital functions. Companies had to show resilience and have a mindset that focuses on innovation and technology. CFOs are encouraged to leverage creative and innovative digital communications to enhance connectivity and engagement, generating new opportunities and increasing dialogue within the business.
Data and technology progression will remain important in delivering continued progress in finance, enabling businesses to attract and retain the best talent, support decision-making and provide greater financial transparency. Businesses need to maintain a check on changes through their culture, talent leadership and innovation in technology. By creating clear expectations, strong talent leadership, and continuously evolving through technology, the function of the CFO will become even more critical, and a business will experience accelerated growth.
The UK financial services industry is experiencing a significant shortage of talent, intensified by the rising demand as a result of the pandemic.
According to a study by the Association of Professional Staffing Companies (APSCo), job vacancies within the industry increased by nearly 38% between Q1 and Q2 of this year. The findings follow on from the report from the Professional & Business Services Council and the Financial Services Skills Commission discovered that on average, 32% of UK businesses were facing shortages within financial, professional and business services.
According to the APSCo findings delivered by BI specialists Vacancysoft, hiring levels within the financial services industry had already exceeded last year’s by the end of July by nearly 7%. Ann Swain, the CEO of APSCo, explains that the data indicates that despite the many challenges, the recovery from the pandemic is well underway, reflected within the financial services industry, where reports suggest a considerable demand for these skilled services.
Swain highlights that this trend is likely to continue throughout this year but, employers will continue to face talent shortages, which have been intensified further by the rise in hiring levels. As a result, recruitment agencies will play a significant role in supporting employers to find the talent needed to ensure an efficient recovery from the pandemic.
Research suggests that IT professionals continue to be the most in-demand skillset, with over 15,000 new jobs advertised this year, a figure that already exceeds the job count for last year. APSCo discovered that leading business JP Morgan has over 2,200 vacancies this year, equating to an 18.3% increase on the previous year. Global investment and financial services business Citi announced over 1,550 vacancies, recording a 39% increase last year.
The skills shortages and changes in employee demands would collectively create a record change in talent strategies within the finance industry. We are experiencing massive volatility and changes in the industry. Businesses have had to adapt and change much quicker to respond to changes and demands for new talent. Despite these shortages, many are not focusing on prioritising their recruitment strategies. The finance industry must recognise the changing landscape and ensure their plans and offerings to employees match market shifts and industry competitiveness.
Businesses are either overwhelmed by too much data, limited access to their data or being held back by the technology they use to measure their information. The influence of digital technology in finance has been ongoing for years. The capacity to automate manual tasks by applying innovative technologies has enabled the finance industry to transition from applying conventional measures to a more insightful analysis of a business.
While more businesses are applying analytics in some shape or form, recent reports suggest that only 14% of finance-related businesses display success in assessing large amounts of data created by systems to generate valuable insights. Finance teams that have utilised tools to enhance their forecasting, improving model scenarios can explore new insights that enhance decision-making.
Based on responses from senior finance executives worldwide, over 80% of analytics is missing the mark. One of the main reasons for this is that many businesses are not extracting the value and insights from their data.
The survey discovered that its data is holding many businesses back. Findings suggest that only a little over 10% of organisations consider themselves as ‘data proficient’, capable of actively managing their data and equipped with the necessary tools and resources required to deliver the insights and competitive advantage they need.
Ignoring the value of operational data
While many businesses have focused on enhancing their analytics, most are missing the real value of insights. To have a complete overview of the business, data from other systems and processes need integration and alignment with financial data to deliver insights and support decisions that enable a competitive advantage.
Ignoring the Information Systems Strategy
The development of new technologies has enabled many struggling finance-related businesses to maintain pace. While these new technologies may be useful, successful organisations need a more holistic approach towards their strategy, yet many are not focusing on this. Studies indicate that over half of finance-related businesses are not capable of consistently adding new data sources to improve their understanding of their business, and under half can utilise their non-financial data. However, when businesses discuss their most important tools for analytics, most points towards AI and ML and at the bottom of the list are usually the necessary building blocks required for delivering an efficient analytics system.
Focusing on the bigger picture The results of the latest studies are consistent with other experiences across the market. Many medium to large businesses are struggling to reach the efficiency and agility required in their processes. This is usually down to dependence on traditional spreadsheets or fragmented systems that are not adequate for the business.
Innovative businesses continue to improve their analytical insights by unifying their processes to deliver a single version of the truth for their financial results, budgets and forecasts.
Converting trends in data into actionable insights
Business leaders are taking the next step by combining transactional data, processes and systems consistently into their analytics. Accessing this type of confirmation from operational systems and combining it with financial data provides these businesses with real-time views into vital trends that support decision-making that impacts future results. Efficient and unified reporting and planning systems require the necessary analytical infrastructure and the right talent. In today’s rapidly changing global economy, having information systems that generate insightful and actionable analytics is no longer a ‘nice to have’ option but a critical element for the future.
As the industry transforms, there will be winners and losers associated with the fundamental changes in the finance industry as a consequence of big data. Rising competition, combined with the breaking down of traditional measures replaced with alternative systems, will impact the businesses we see today.
Customers will likely benefit from enhanced products and services, and businesses will be more capable of managing risks and overall efficiency. However, there is the potential that some customers may be excluded from selected markets and will inevitably experience exposure to new risks.
In a recent study, the Institute of Chartered Accountants in England and Wales (ICAEW), explored how the finance industry has changed because of the increased availability of new data. Unlike other businesses, employees in the financial services industry will experience the value of big data. While customers can decide which companies to purchase from, financial services are a critical part of our daily lives. The collection and use of data are valuable to the industry, meaning there needs to be careful consideration of the ethics involved.
The growing reliance on data enables customer behaviour to be shaped by digital technology, which feeds into the supply of data. Plans and decisions regarding big data have a direct social impact across the entire finance industry. As customers become more sensitive and aware of data in business, financial service providers will have to ensure they maintain their responsibilities.
Several principles can support financial businesses with managing and resolving any ethical tensions.
Accountable for Big Data
Big data and new technologies are increasingly important to businesses today, but industry experts have pointed out that many organisations lack the skills and experience in this field. The complexity of these technologies must factor in as this understanding is vital in determining strategy, company values and culture. A chief data officer should be recognised as an asset within the senior leadership team to ensure accountability within an organisation and with regulators.
Business Management in the era of Big Data
Finance businesses are often complicated, running from a range of systems. Operating normally in this new world of big data will present new challenges that will require time, investment and new resources to help businesses prosper. Despite its significant rise, big data isn’t something for the finance industry. An element of the transition to big data will be focusing on existing data and using this information in new and innovative ways.
As the industry progresses, businesses must show that they have analytical capabilities, appropriate measures and suitable data storage facilities to use big data properly. Without these core elements, they will potentially be at a competitive disadvantage and at possible regulatory risk from generating inaccurate findings that could result in unfair treatment to customers. Having higher volumes of data also poses potential issues of cyberattacks.
Treating all customers fairly
All financial companies must be capable of consistently showing that they implement equal treatment with their customers. As companies evolve with the growth of big data, organisations will have to determine how they interpret fairness and how they intend to keep customers at the core of their business.
If a business relies on historical data, it may generate bias created by how information is collected. This trend can continue and be reinforced in areas where there are gaps in data. This can lead to ethical issues of using data for customer decision making and product design. Customers need to have a clear understanding of the impact of making a selected big data decision against them. Businesses should then notify customers why decisions were made and include the relevant criteria. The customer can then determine whether the information is correct or not and provide corrective support. This type of feedback mechanism offers more transparency to the customer and enhances data accuracy for the business.
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.
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.
Artificial Intelligence requires significant data, building and deploying AI and machine learning systems requires significant data sets. Creating key machine learning algorithms is dependent on large volumes of data. To expand and deepen the results and findings made by the algorithm, machine learning requires data from a range of sources, in various formats and from a variety of business processes.
At the same time, AI itself can be vital in determining and preparing the data required to drive the further value of AI and analytical systems. Businesses require more data scientists and specialised analysts to integrate the necessary AI and machine learning algorithms.
A new era of enterprise analytics is developing and it involves a combination of automation and contextual information. AI-focused analytical systems can develop vital insights and information that can be passed onto decision-makers without requiring specialist analysts to prepare the data. Business intelligence analysts and other data professionals will still play an important role, but many will not be needed to provide added support to other team members and data users.
Smaller businesses that don’t necessarily have the budget for data scientists will be able to measure their data with better accuracy and clearer insights.
The potential to efficiently automate data tasks is dependant on the industry and overall circumstances. Often, there is a need for adequately trained human support for AI and machine learning plans, especially if the output is critical to the business.
While automated AI data science tools can be simple and effective, they may leave businesses with unanswered questions. If you don’t have a background in data science or machine learning, you may not be capable of determining the results or implementing the suggested changes, which can be challenging and time-consuming.
There is the potential to automate certain parts of a data scientist role, but the skills of a data engineer will continue to be a vital asset to an organisation. Data engineering is required to produce smart and intelligent information that can enhance predictive accuracy and support detailed business analysis.
There may be ways to automate various pieces of data science roles, but the skills category that will still be essential is that of a data engineer. There are many tasks required to source, manage and store data in which data scientists don’t necessarily want to get involved. “To succeed with AI, companies should have an automation environment with reliable historian data,” a McKinsey report explains.
Then, companies “will need to adapt their big data into a form that is amenable to AI, often with far fewer variables and with intelligent, first principles-based feature engineering,” the study’s authors, led by Jay Agarwal, state. Data engineering is needed to produce “smart data” to improve predictive accuracy and aid in root-cause analysis. This, along with equipping staff with the right skills, can provide services that can help increase revenues up to 15 per cent, they relate.
Data engineering is vital. A data scientist can’t discover or utilise information until there is a good set of data to work with. Data scientists and specialised data analysts will continue to be in demand and will remain important in supporting businesses to design and test algorithms and data that can determine trends, automate processes and engage with customers. The challenge, however, is the volume of data flowing into businesses and the rising demands for new algorithms and capabilities with data. AI is unravelling a new path to a more effective and accessible AI.
Financial services businesses within the UK are becoming more reliant on scraping alternative data sources, with over 60% using alternative data to improve their decision-making process. The new report ‘The Growing Importance of Alternative Data in the Finance Industry’ by Oxylabs highlights the significant rise in web scraping for alternative data over the last year or so.
Over 200 senior data decision-makers in the UK finance industry were interviewed on their existing approach to data management. The findings indicated that web scraping and financial transitions were the most popular sources of alternative data for financial services organisations. This includes non-traditional data sources that may not have been assessed before, such as social media posts, website traffic and other data sources. Conventional sources like official public data and third-party data are still considered valuable but have been overtaken by the significant rise in alternative data.
Julius Cerniauskas, the CEO at Oxylabs, explains that the rise in online alternative data sources has created a sharp increase in demand for web scraping services from financial organisations looking to tackle the challenges from the pandemic.
Cerniauskas states that they have experienced a surge in inquiries from businesses in the financial services industry over the last year, so he explains that they are motivated to learn how these organisations were approaching data collection and analysis.
Alternative data can be implemented to gain a better understanding of business performance, market trends and future investment plans. Financial services businesses can transform alternative real-time data into clear, actionable insights that are far more likely to report significant improvements in decision-making.
Business leaders in the finance industry are continuing to explore new ways of improving investment decisions and reducing risk to their business, so it’s understandable to see that the global alternative data industry is growing and predicted to continue increasing over the next few years.
Looking at the research, it’s clear that financial services businesses are increasingly looking to utilise alternative data to gain more value and discover new insights into performance, industry trends and potential investment opportunities. Data-focused organisations will be in a stronger position to convert this valuable information into actionable insights and deliver strategic decisions in a post-pandemic economy.
Open banking is the transfer of financial data and a trend that inevitably is likely to increase. While open banking empowers fintech and larger technology businesses, a report by McKinsey suggests several significant benefits for established banks and financial organisations that may have not been previously recognised.
Industry experts highlight how our world is changing and how important information is to businesses. Customers are not willing to accept a particular service or price if they are aware of better options elsewhere. Several reports from McKinsey suggest that embracing open banking is necessary and has benefits for financial institutions as much as it had for fintech and other businesses.
The findings indicate a value to the adoption of open financial data, an increase in GDP of between 1% and 1.5% within the U.S, the U.K. and the EU.
While it’s not exactly clear how open financial data will progress, the trend towards data sharing between financial institutions, fintech and other big businesses is only going to increase. This will have a significant impact on the traditional banking industry shortly.
In the report ‘Financial Services Unchained’, McKinsey explains that if open finance continues to accelerate it could transform the global financial services system and change the concept of banking altogether. The report goes onto say that the ability for customers to gain a deeper understanding of their finances could result in margin compression, as charges and pricing becomes more transparent. McKinsey explains that banks may have to compete with margin sharing, as payouts to other digital platforms could play a bigger role in customer acquisition.
McKinsey also highlights that open financial data places big technology businesses in a stronger position to become financial services leaders. We are increasingly seeing more big tech businesses entering financial services, using open data as part of their offerings. It’s worth remembering that multiple businesses are capable of using the same data and as a result, big technology businesses will have banking partners and will continue to face several banking competitors.
Increased competition will ultimately lead to the need to understand and respond to new changes, restructure offerings, adapt business models and establish partnerships with fintech or technology businesses to drive continued success and relevance.
The benefits and value of open data
While it may sound like conventional financial businesses may face a challenging future, the report ‘Financial Data Unbound’ by McKinsey details several benefits of open financial data and specifically relate to financial institutions.
In most cases, financial data sharing is quite limited to areas within financial services, but there are several benefits to customers and small businesses from open finance.
Increased Access to Financial Services: Data sharing allows customers to purchase and use financial services that previously they may not have had access to. For example, open financial data can support the credit assessment of borrowers by measuring utility, phone bills and other factors.
Enhanced User Convenience: Data sharing can save substantial time for customers in their engagement with financial services and, more importantly, for product purchases and exit. For example, open access to data on mortgage products enables customers to apply for loans without engaging a mortgage advisor.
Improved Product Options: Open financial data can provide an enhanced range of options available for customers and create further savings. For example, open data systems make it simpler to switch to different accounts, supporting small business customers to gain the best results.
Benefits of Open Data to Financial Institutions
Fintechs and other third-party services have displayed clear benefits by having the ability to access customer banking data that was previously unavailable in conventional banks. The benefits to other financial organisations aren’t necessarily as clear, but they do exist.
McKinsey explains that the open data systems are progressing in various ways that don’t necessarily translate into a clear win-lose situation for banks and fintech. Some banks will be able to leverage open banking and take a share of this emerging market. The McKinsey report several benefits from open banking for financial institutions:
Enhanced operational efficiency: open financial data could significantly reduce costs by replacing physical documents with verified digital data, making it simpler to adopt automated technologies. This will improve customer experience by enabling quicker and more transparent interactions.
Better Fraud Protection: Improved fraud protection can mean considerable cost reductions for financial businesses and an overall improved customer experience. Sharing fraud-related data creates more evidence and insight to support detecting any suspicious activity.
Improved Workforce Allocation: Financial organisations can use open data to allocate and support their workforce, assigning particular members to high-value activities.
Improve the Data Intermediation Process: Open banking systems create direct access to data via APIs for intermediation, reducing overall friction. Data sharing decreases or eliminates the costs financial organisations experience in data sourcing with third party providers and other aggregators.