The CFA Institute, a global association of investment professionals, has introduced a guide for AI and Big Data services in investments, published by the CFA Institute Research Foundation. The guide details how asset managers use AI and big data technologies to streamline the investment process and enhance investments and business performance.

With contributions from data scientists and investment leaders at market leaders, the CFA Institute Research Foundation AI handbook provides a detailed insight into the investment industry’s adoption of data science to offer investment plans to deliver more resilient portfolios, make more informed trading decisions, streamline client plans, generating client-focused services and create additional business intelligence.

Margaret Franklin, the CEO of the CFA Institute, explains that their business considers the combination of AI and human intelligence a winning formula for success in finance in the future. As AI and big data solutions become more pronounced in financial markets, industry leaders must be well-prepared to effectively measure and incorporate these services. Franklin hopes the AI handbook will support the industry in adopting AI and big data solutions meaningfully to benefit their customers.

AI handbook details

The AI handbook is presented from the industry perspective, including real-world examples and tested solutions. Larry Cao, senior director of research at the CFA Institute, explains that industry requirements have expanded from asking for details on how AI and big data work to requesting an action plan supporting their business strategy as AI and ML measures become part of the mainstream. The AI guide is the latest in a series of research from the CFA Institute, focusing on supporting practitioners and policymakers with the necessary services to evaluate and implement AI and big data to the highest standards.

No single operating model for data science integration can work for all finance and asset management businesses. Technology must adapt to work for culture, structure, core values, budgets and strategic priorities. The guide will support companies in commencing, refining or planning the next stage of their data science vision.

The latest Women in Finance report highlights how the finance industry is making positive changes toward increasing female representation in senior leadership roles in finance.

The report suggests that the average representation of women in senior roles increased to 35% in 20222 and that nearly three-quarters of signatories increased the number of women in senior management positions. Furthermore, the report suggests businesses are progressing toward their goals, with half setting a target of reaching 40%.

The HM Treasury introduced the Women in Finance Charter in 2016 and has published a review of the progress annually in partnership with the think tank New Financial. Certifiers of the Charter must declare their progress to the Treasury against their independent targets for women in senior management roles.

Overall this year’s report was very positive, with the main headlines including:

• Average female representation increased to 35%, indicating an improved picture for Charter signatories, as this number remained at 33% in 2020 and 2021.
• 77% of signatories have either increased (71%) or maintained (6%) their proportion of women in senior management.
• Signatories’ targets are rising, with half (50%) setting a target of at least 40%.
• Of the 73 signatories with a 2022 deadline, 44 hit their targets, and the remaining 29 missed, down from 31 in 2021. Of the 29 missing, 22 were close – within five percentage points or five appointments of hitting their targets.
• For the first time since the Charter’s creation, the top quarter of firms (52) have achieved at least 40% female representation in senior management. 

Source: Women in Finance Charter Report gov. uk

In response to the report, Treasury Lords Minister Baroness Penn stated that the results were very positive and that the signatories have shown commitment to delivering on this agenda by utilising data, setting targets and working to develop and inspire the next generation of leaders. Baroness Penn believes the report should indicate progress and remind us to stay focused. Penn wants to ensure the Charter remains a tool for maintaining competition, innovation and productivity. 

Amanda Blanc, CEO at Aviva and Government Women in Finance Champion, explains that the results are encouraging but believes we must continue progressing to ensure lasting changes. It’s positive that leaders are accountable for diversity in their business and that data is used effectively to support this issue.

Blanc highlights that a quarter of businesses now have 40% of women in senior management roles. While this is promising, we must continue to do more to ensure we improve the rate of change to achieve permanent acceptance of women in finance. Yasmine Chinwala, partner at New Finance and the lead author of the report, believes the progress is evidence that the principles of the Charter work. They encourage businesses to focus on the challenge of female representation like other strategic areas, with a target, progress and accountability. 

The data suggests that more businesses are discovering the connection between diversity targets and pay is making a difference, with over 60% reporting that the link to pay has been effective. Creating this link to pay means diversity is increasingly recognised as a business issue rather than an independent or voluntary issue managed by D&I teams.

Many businesses today struggle to maintain pace with the demand for harnessing data for decision-making. A mix of legacy systems, lack of digital skills, underinvestment and mounting unstructured data are some of the main reasons which have left many organisations feeling quite limited in their ability to use data effectively.

Data challenges impact various teams, but the CFO and its finance team typically face additional challenges with the scrutiny around management and regulatory reporting. Furthermore, the finance function often plays a vital role in data with expectations to provide seamless data service for the rest of the business. 

The value of data fabric in finance

According to Gartner, data fabric is a data management design that allows augmented data integration and sharing across diverse data sources. Data fabric have become more common over the last few years with the rise of data sources, formats and silos. Gartner highlighted data fabric as a strategic priority tech trend in 2022 and predicts that by 2024, data fabric deployments will significantly improve data utilisation and reduce human-driven data management activities in half.

Data fabrics offer a centralised, single layer of interaction that bring data, regardless of location, in a process that doesn’t require duplication. The data fabric can manage the lifecycle of that data, applying active data to manage privacy policies and compliance via role-based access controls. 

The role of the CFO in the data fabric

For CFOs managing complex data and finance landscapes, using a data fabric provides easier access to data, increased performance and the ability to operate more efficiently and at a lower cost. 

Data fabrics empower finance and businesses to deliver data models and use data without the relevant coding skills. Traditionally, an application has a predefined data model, which means finance and IT teams must bring in data points from other systems and match them to predetermined models. This can be tedious as people find it challenging to fit existing data into rigid data models. Using data fabric enables teams to flexibly create a data model within finance through a process referred to as data cataloguing. This enables data models to be generated by finance experts rather than technical users. 

Added flexibility with data fabric

A data fabric methodology enables finance to be more flexible in a database application. Finance can apply the most relevant data storage tool that fits the purpose. Using a data fabric approach allows selections that ensure we access the best capabilities and performance. 

Reduced costs with finance

One benefit of data fabric is reducing the cost of finance functions by eliminating redundant storage systems. Considering the current economic challenges and the rise of cloud computing, this is a critical area for IT and finance leaders looking to deliver an efficient infrastructure that fulfils the requirements of the business. The decrease in data ‘lifting and sharing’ has reduced the number of integrations and points of failure, reducing the need to request IT support to tackle potential issues. 

Furthermore, CFOs can decrease the cost of finance by eliminating siloed finance teams validating, managing and reconciling multiple datasets for their purpose. A data fabric enables these activities to be centralised, resulting in a more cost-efficient finance department.

Gartner recently suggested that data fabrics have the potential to reduce data management activities by up to 70% and accelerate the time to value, which has significant implications for finance teams. From reducing the need to deliver point-to-point integrations between systems to reduce repetitive tasks, finance can reduce the time to value. 

Data fabrics enable extensions on top of core applications. Using a data fabric makes it easier to integrate other applications that use the same data set, assuring end users that their data is accurate. Data fabric is a strategic technology approach that offers considerable benefits to CFOs and their teams. From improving flexibility and performance to reducing the cost of finance, this is a vital technology that will provide business value.

With the next industrial revolution progressing, a considerable amount of new data is being created, stored and analysed daily. This information massively impacts our economy, workforce, culture and society. Our experiences, whether it be individually or collectively, are significantly influenced by data. 

We collectively create data, but as it stands, women account for only 26% of data and AI positions in the global workforce, with the gender gap continuing to expand at the senior level. This is a concerning statistic considering we are well aware of the impacts of data bias in recruitment, finance and other industries. 

Women in data have never been so critical in our data-focused world. Fortunately, several female leaders have contributed massively to the industry and have created the path for the next generation. For International Women’s Day, we should highlight women’s impact on the data industry.

Reducing the gender gap

While the industry does need to improve its image to STEM graduates, there are an increasing number of international projects supported by tech leaders like Google, Microsoft and Salesforce with backing from the World Economic Forum, aiming to improve gender equality in the industry. Successful female leaders like Fei-Fei Li, the founder of Stanford AI lab, have been doing great work improving diversity in data for several years. More women are joining their ranks and becoming role models and mentors, inspiring the next generation of young women looking to pursue a career in data and AI.

Reducing the gender gap goes beyond adapting recruitment processes and implementing gender and diversity targets. Industry leaders must ensure their company culture enables women to feel capable of voicing their opinions and providing the insights that often provide companies with a competitive advantage. Studies show that teams capable of rethinking their strategies based on the contribution of female employees are far more likely to deliver successful concepts. With the more female leader in the industry, we can generate opportunities for female contributors to succeed in ways other businesses won’t be able to ignore.

Promoting diversity in data

Women are advocating diversity and inclusion in data, tackling the current gender biases in industry. Thanks to an increasing number of women, businesses are implementing the necessary steps to eliminate data bias and provide alternatives when creating insights from big data. Pre-determined algorithms impact every part of our lives, so women must be involved to avoid widening the existing gender gap. Furthermore, women are improving business performance, with studies indicating those companies in the top 25% for gender diversity are 15% more likely to achieve their financial goals. Some of the most successful tech startups consist of twice as many women in senior positions than less successful tech companies.

Supporting data and innovation

Women in data are incorporating their skills and talent to deliver innovative solutions capable of tackling challenges and generating new ideas for a business that will shape the future of data and analytics. Businesses must focus on improving gender diversity within their data teams if they plan to be part of a growth market controlling more than £20 trillion of global consumer spending. Gender-diverse data teams can deliver a system recognising what female end-users want, allowing businesses to provide a far more effective service.

Data opportunities for women

A recent study by the World Economic Forum discovered that over 90% of employers intend to implement user and big data analytics, with data scientists and analysts considered one of the top ten emerging jobs. Many businesses have just started their data journeys and are now recognising the value of gender diversity. While there is progress with the number of women working in data, there remains a significant gender gap. Businesses and individuals must continue working on creating more opportunities for women in data. By doing this, we can deliver a more diverse and inclusive industry that supports everyone. 

Shifting finance to the cloud can create a range of benefits for businesses, but there are also potential challenges to overcome. CFOs interested in moving the finance aspect to the cloud should consider the benefits the move can bring, as well as the potential challenges. Cloud migration of software can reduce maintenance costs and enable further migration in the future. Migrating finance to SaaS can create greater cost savings in the long term and increase automation ability. SaaS, can, however, come with some challenges, such as increased security problems. 

The core benefits of moving finance to the cloud

Improved analytics – Cloud technology typically consists of more sophisticated analytics compared to on-premises software, and these analytical tools can help the finance team improve overall operations. Many companies that have shifted from legacy technologies to the cloud can offer a range of reporting and analytical tools, as well as the ability to customise reports and explore data with other analytical tools.

Enhanced Automation – Cloud technologies enable more automation of processes, saving employees significant time. Many finance businesses, for example, can automate purchase orders and send shipment updates to customers automatically. Automated services can improve overall customer service, compared to relying on people handling various manual tasks.

Reduced operational costs

Businesses are likely to experience reduced operational costs after moving finance to the cloud because cloud software requires less employee contribution. Integrated cloud services typically require less IT management. Employees can use cloud technologies to deliver specialised reports, reducing the pressure on IT teams. Furthermore, businesses with a well-structured cloud environment often save money on platform maintenance expenses. 

Improved decision-making

A cloud finance system can give finance teams more detailed insights into sales performance. Businesses equipped with modern tools can explore various segments which provide insights into sales and understand what is working or what requires attention. More granular data on sales can support businesses in making important purchasing and management decisions.

The challenges of moving finance to the cloud

CFOs and IT leaders must consider the challenges when migrating finance to the cloud.

Employee skills and training 

CFOs should remember that their employees will require additional training on new cloud systems. Finance and IT teams should collaborate to create a plan for upskilling their employees using existing systems affected by the transition to the cloud. CFOs and others associated with the cloud must consider the time and investment associated with new software training and create an appropriate plan in response. 

Employee caution and resistance While legacy services may not be as efficient, some finance professionals will be reluctant to adopt new technologies that impact their workflow. Businesses that have made the transition, often report a certain level of reluctance to technology changes. In some cases, the resistance to adopting cloud technologies has resulted in a complete restructuring of teams. Often in this situation, the result is a reduced, streamlined team capable of utilising the benefits of these new services.

Determining actual savings from the move

CFOs should explore the specific cost savings from moving to the cloud. Businesses often focus on believed cloud cost savings, but costs can escalate if a company fails to manage cloud operations effectively with efficient data management and security procedures. 

CFOs should collaborate with IT to determine the potential savings from moving to the cloud.

Establishing the business case for cloud

The CFO must partner with other senior leaders to determine the business case for moving finance to the cloud. Finance leaders and tech executives should collaborate to determine the most appropriate cloud service. While the finance team should lead the case for moving finance to the cloud, they will benefit by understanding the IT aspect of transitioning from existing systems. IT and Finance can work together to determine the opportunities for automation and develop metrics for understanding financial operations progress. 

Finance and IT working together may help gain support from other company leaders because each side will have the expertise that the other team lacks.