Oracle has expanded its relationship with the UK Government by enhancing the Government Centre of Excellence and enabling better access to Oracle Cloud. Oracle has updated its links with the Government by updating the existing Memorandum of Understanding (MOU) between Crown Commercial Service (CCS) and Oracle, as well as focusing on building a stronger working relationship between Oracle and the UK public sector.
The Oracle Centre of Excellence will provide further support and technical capabilities enabling the UK Government to make more use of Oracle Cloud. The updated MOU will ensure governments and the public service sector will have continued use of Oracle Cloud. Critical services will have complete access to the full range of cloud applications, infrastructure services and autonomous technologies.
Oracle Cloud will support customers like the UK Government in delivering higher efficiency, automation and productivity, all important factors in supporting a successful economic recovery. The services will provide public sector organisations with further support in shifting workloads to Oracle Cloud Infrastructure or expanding the use of the Oracle Cloud Applications Suite.
Philip Orumwense, commercial director and chief technology officer of Crown Commercial Service explains that the enhanced MOU will continue to create savings and further benefits for public sector customers using Oracle’s cloud-based technologies. Orumwense highlights that the services will create more value while supporting public sector customers’ journey to the cloud.
Gareth Rhys Williams, the Chief Commercial Officer explains that the UK is committed to the Build Back Better growth plan, a part of which involves ensuring we make the most effective use of modern cloud technologies. Extending the relationship with Oracle will enable the UK to continue generating commercial value, enhance services delivery and support the wider agenda of the Government.
Richard Petley, MD and Senior Vice President of Technology and Cloud at Oracle explain that the announcement confirms the commitment and long-standing relationships between their business and the UK Government. Petley highlights that the collaboration enables the potential of the cloud to support the UK is leading the way in adopting digital technologies.
Oracle provides the only multi-region cloud for use by public sector customers in the UK and can be used by multiple groups such as the Home Office, the NHS and the Ministry of Defence. The revised MOU builds on these relationships and will enable public sector group to use cloud technologies to deliver the most effective public services and greater value to the customer.
People are beginning to adapt to AI at a steadily rising rate. It’s clear that modern technology is evolving rapidly and has had some impact on nearly everyone’s lives.
AI has become profoundly popular in multiple industries for a range of reasons. Improving efficiency, managing information, identifying trends in data are a few of the reasons why AI has grown so significantly in recent years.
The finance industry is a particularly important area that needs to be capable of adapting to meet the needs of their customers. The conventional ways of managing customers don’t necessarily work as well today.
In the case of the finance industry, AI and Machine Learning have various applications. Chatbots, robotic process automation are good examples of AI applications in finance. Global studies have indicated that applying AI could save the finance industry over $440 billion by 2023. Many industry leaders are questioning how exactly AI can transform the finance industry and support the global economy.
AI in finance is being utilised for maintaining important business records, in the case of finance, this could be information such as credit scores. Before customers are offered a credit card, a finance company will check multiple records, loans etc and use this data to adjust the interest rate applied to the card offers.
This process is complex and involves multiple record checks but AI is capable of doing this work quickly by utilising data and then recommending the right product and interest rate for each customer. Human-based analysis may include errors that can result in potential costs to finance the business. AI memory is developed on Machine Learning, eliminating the margin of error.
Many finance businesses have launched chatbots on their websites. A chatbot managed and integrated by an AI development business is capable of interacting directly with customers and answering specific questions. This saves time and more importantly money for the business.
Detecting and Managing Fraud
The primary goal for most businesses is reducing risk, and this is particularly true in the world of finance. There has been a rising number of security breaches and scams in the finance industry and so customers are more cautious about their money. Many financial institutions have implemented AI services to detect cases of potential fraud. AI tools are capable of detecting fraud through analysis of one transaction activity. They can detect fraud by monitoring unusual transactions and location changes. With the support of AI, it is becoming more difficult for hackers and fraudsters to complete these activities.
Finance Advisory Services
Machines can apply bionic advisory tools which provide an efficient and accurate service, but industry experts believe a combination of these tools with the human mind generates the highest results. While these new technology tools can generate efficient results, they do require human intervention to generate the most success.
Understanding future trends in finance are challenging and so many investment businesses use AI to generate a clearer understanding of future patterns. Machines are particularly useful in managing large volumes of data in a short period. They also can assess financial changes and detect certain flaws in a system and offer solutions.
AI is continuing to make steady progress in the finance industry and judging by the pace of change, it will have a significant impact on the employee structure in certain roles in finance. Ultimately AI can greatly reduce the potential challenges in finance and lessen the potential of security breaches. Customers can be given better services, enhanced support and opportunities for smarter trading.
The role of a CFO has transformed in recent years, going well beyond its conventional function to more of a pivotal role in engaging, communicating and influencing overall value for a business.
Finance professionals today need to be capable of telling their own story, representing themselves as vital decision-makers on specific issues ranging from ESG to how to best leverage Big Data. The role of the finance professional has significantly changed, thanks partly to the automation of many standard tasks and the focus on how the finance role can influence overall business strategy. Finance is far more than just looking at numbers and has a profound impact on key decisions. Gaining support from the business is critical and so is capable of delivering effective stories defining the problem and solutions for improvements are an important element.
Finance teams are often being approached from other sides of the business, such as corporate sustainability to support collaborative teams capable of meeting the ESG demands. In today’s world, we are finally recognising how precious nature is and that our commodities are finite. Focusing on development must be partnered with understanding and measuring what these actions have on protecting our wider and future interest. Finance professionals are well-positioned to manage and provide teams with the information needed on important issues such as ESG.
In today’s data-driven world, many businesses struggle to manage their data and how to use it to make strategic decisions. Increasingly, finance professionals are being asked to collaborate with data scientists and others focusing on extracting insights from big data. There is an emerging trend of finance professionals collaborating with other teams and harnessing their skills in various ways. Finance people can play a pivotal part in the Information Age. They have experience with data and bring with this their advisory knowledge and strategic position to manage these responsibilities.
We are well into the era of big data and in every business and every finance team, people have the opportunity to work with data. Finance professionals have the power to inform, guide and lead their business. Many CFOs will have the responsibility for possibly the majority of data transformations in a business.
Forward-thinking financial businesses are applying data, analytics and AI to create new products and services and to enable the delivery of more intuitive and personalised service. Future success requires attracting skilled talent, enhancing existing processes and meeting the increasing demands of customers.
The finance industry is continuously focused on digital transformation and utilising data, analytics and artificial intelligence to improve their services. Banks are applying AI to enhance their current offering, build new products and improve the overall customer service. Data and analytics are proving vital in supporting the progression of new business models and improving decision making.
This significant shift comes with its challenges, such as accessing data, the quality of information, the available skilled talent and the delivery of necessary resources to generate the required results. Most financial teams also lack the required digital experience to create and build a digital-focused organisation. Nevertheless, the decision-making influence of data and analytics provide financial businesses with the competitive edge needed to provide the added value to their customers.
According to studies from McKinsey, Financial businesses that apply data and advanced analytics to engage with customers and drive new business are capable of generating value in several ways:
Enhanced Customer Acquisition: By focusing on delivering personalised information at every step of the customer acquisition journey, engagement becomes simplified and the overall customer experience is improved.
Higher Customer Lifetime Value – Offering new products and services to customers is done through intelligent communication and recommendations based on real-time analytics and data.
Reduced Operational Costs – Automating and simplifying data processes and decision making plans, overall efficiencies are improved and costs decline.
Reduced Risk – Applying advanced analytics enables selective decisions on potential customers and allows detailed analysis of customer behaviours to detect potential cases of risk and fraud.
Financial businesses are increasingly looking for analytical solutions to improve their position against other competitors. According to a report by the Cambridge Centre for Alternative Finance and the World Economic Forum, several global financial services firms have implemented or are working towards adding AI solutions within a range of business functions. Data from the World Economic Forum suggests that approximately 85% of all financial businesses have implemented AI, in some shape or form.
Beyond the security and risk detection side, an increasing number of financial services are applying analytics to create new services and an innovative customer experience. Advanced analytics can be applied across the entire customer journey, from initial engagement through to evaluation and ongoing relationships. As a business uses AI to further deepen its understanding of each customer journey, the organisation can deliver highly personalised offerings directly to the customer in real-time.
Applying data to generate insights that can be applied across the business isn’t enough. Financial businesses that engage continue to increase, experiences are enhanced and loyalty is strengthened. In other words, the ROI on data and AI is not fulfilled until these factors are achieved.
A major part of the recent success at Oracle is related to its SaaS model and ability to evolve its technology and offerings to new customers in the cloud. Its recent updates to the advertising and customer experience applications represent another example of innovation and meeting the demands of its customers.
Oracle advertising and CX are application that is capable of delivering a comprehensive view of every customer and their interactions. Risk management leader Aon is a good example of this in action. Aon began using several CRM tools but quickly realised that it required a single system representing the business to its customers. Back in 2017, Aon started the transition to combine all of its users into a single system and chose Oracle as the preferred platform for its customer experience. The instant benefit of the new system was that members from any location could open an account and view all other team members worldwide.
Teams could collaborate and deliver their information as one voice to the customer, instead of many as before. The other benefit was the value of data collected, which provided information on who was working with a customer, what purchases were made etc. opening up several new opportunities and targeted dialogue with customers. With data being collected and stored in one place, the entire reporting process became easier and clearer.
One of the main challenges associated with a subscription model is understanding why customers may not be renewing. Customer churn, the volume of customers cancelling can be related to many factors. Oracle applies artificial intelligence (AI) and historical trends to determine the main drivers influencing customer churn. The system also generates reports to understand ‘at-risk customers and keep loyal customers informed about their accounts.
Oracle continues to improve its advertising and customer experience applications with additional updates. Oracle appreciates the importance of collecting relevant data within the customer journey and utilising artificial intelligence to enhance the overall business process. No employee in a business must approach a customer without having a detailed understanding, context and supporting recommendations. Knowing whether a customer is a loyal repeat user or has experienced service issues is vital and boils down to collecting and measuring the right data sets. Capturing the right data enables the opportunity to provide the necessary support and guidance at the right time to each customer. The result is ensuring that every customer interaction is positive, whether it be for marketing, selling or servicing.
The necessity for clear plans on how to reach net-zero targets and creating a level of resilience are some of the biggest challenges for financial businesses addressing climate risk.
According to a survey by Willis Towers Watson of leading financial businesses, the availability of data represents one of the biggest challenges businesses expect to experience over the next five years to tackle climate risk.
The survey suggested that 80% of respondents reported data as their biggest concern in regards to an effective transition to a Net Zero economy. Delivered as part of the Willis Towers Watson’s Climate Risk and Financial Stewardship Summit, the survey included banks, insurers, wealth and asset managers to gather insights on the progress made to manage the impact of climate risk on their business.
The study also showed that few businesses expect the level of risk related to climate change to decline, with most anticipating the existing level of risk facing businesses to escalate in the coming years. With current trends indicating that we are struggling to maintain temperature levels from exceeding the 1.5-degree target of pre-industrial levels, respondents stated that creating an effective net-zero strategy was the biggest challenge, followed by a lack of data and resources.
Aside from the climate-focused challenges facing the financial sector, respondents highlighted that transition, reputation and social responsibility were key measures that organisations were prioritising to reduce the gap and achieve net-zero targets.
Rowan Douglas, Head of Willis Towers Watson’s Climate and Resilience Hub stated that climate risks for the future are unprecedented. While the financial industry is in a strong position to take a leading role, climate-focused risk needs to be integrated into daily management but also influence the entire economic transition towards a low-carbon and resilient future.
Reports from the Carbon Disclosure Project (CDP) indicate that approximately half of the world’s 500 biggest businesses are yet to conduct any analysis of how their portfolio is impacting the climate. This is even though the portfolio emissions of global financial organisations are over 700 times bigger than direct emissions.
We are experiencing a transformation in what Net Zero finance means for the financial industry and its importance in an economic transition towards a climate-resilient future. The added pressure from bold new climate targets and further inspections from banks, regulators, investors and the wider public are continuing to rise. To succeed, financial institutions need to adapt, acquire data to support their new plans, and ensure their portfolios are aligned with a net-zero carbon world.
The importance of cybersecurity doesn’t just apply to the IT industry. It is a vital part of every business, particularly within the finance sector. Banks and other financial organisations hold and manage millions of transactions daily, with the majority of these payments being done by digital platforms. This rise in digital payment options has come with a rise in targeted cyberattacks.
Cybersecurity has been a critical factor in the financial industry and has become fundamental in establishing a level of trust and credibility with customers. The fundamental reason placing significance on cybersecurity for the finance industry is protecting customer resources. As more customers convert to cashless finance, banking activities are typically done via online platforms. In the case of a security breach, it damages the customer but has an additional impact on the business retrieving information and the implications of listing customer trust.
Despite further government efforts to prevent cyber-attacks, the vision of a world free of these security breaches is unlikely. According to BitDefender, ransomware attacks increased by over 700% worldwide in the first half of 2020. What is quite clear is that the pandemic has shown that businesses need to remain very conscious of their security. Applying a zero-trust approach towards security is essential for financial services that may experience the emerging threats from Covid-19.
Data is so valuable and represents the key to financial services. Applying this level of ‘distrust’ within security requires considerable detail about what your cyber-security is protecting and applying security controls close to your data. Those responsible and managing security should understand where all the data is stored, how it can be extracted and where it moves within the business.
Practical tips financial services can use to stay protected
Understanding what you have and where it goes is an important first step to implementing a zero-trust security plan. Beyond this knowledge is being capable of acting based on an accurate idea of your data.
Businesses should look beyond conventional approaches towards cybersecurity that aim at blocking systems. Instead, businesses must integrate a cyber-resilient approach that is automated and integrated into their working environment. Focusing on protection, detecting, responding and recovering cyber resilience must enable permanent business performance via the most efficient response and data recovery measures.
Three key areas that contribute to effective cyber-security in financial services
Encryption has existed for some time but remains an important tool for sensitive information that is stored in multiple locations or moving around regularly.
Location is an area that relies predominantly on your business understanding the location of your data and how it moves around. To keep data safe, several local and remote copies of critical files must be developed. This should be combined with systems capable of understanding the standard behaviour of data, so if a change in activity occurs, the response time can be immediate. Once security managers grasp this, they can determine the most appropriate method to classify data location and allow access correctly.
Access is generally focused on a transition to the mindset with data. For example the financial services industry as like many need to move away from giving employees access to all data just because they work at that particular business. Instead, data access should be prioritised as a privilege only granted to those when necessary. This is where the concept of zero-trust comes into play and security managers need to create a process of accepting data access based on several measures or personalising access based on the responsibility of each employee.
Security can become overwhelming especially with the rise of new data generated these days. It’s easy for many organisations to be playing catch up and not necessarily apply enough resources to this area. Financial services don’t have the strongest historical reputation in terms of data breaches but that doesn’t mean that a strong cyber-security model cannot be achieved.
Remaining vigilant, consistent data management and implementing an action plan based on insights and a zero-trust approach are needed for effective security in finance.
A new study from NTT suggests that over 80% of financial institutions believe AI is a vital part of differentiating their business, future success and generating new business. The study, however, indicates that only 16% of financial businesses use AI and data.
Senior financial leaders overwhelmingly agreed that the adoption of AI was a very important competitive driver of success over the coming years. While AI generates opportunities for creativity and further innovation, existing challenges are influencing the adoption of this technology. Implementing technology and requirements with organisational skills are considered particular challenges when considering AI services.
Since the pandemic, customer searches for digital finance solutions and applications has risen considerably. Today more than ever, financial institutions need to find a way to eliminate these barriers within AI to support customers and be capable of providing the support they need.
Customers display clear insights that they require banks to work as strategic partner on their financial decisions. AI offers a pathway to providing the services that customers are demanding. The data clearly shows that financial institutions need to focus on AI to meet the rapidly evolving needs of consumers, or potentially risk losing customers to their competitors.
The main challenges for financial institutions to attract and retain customers involves using AI to offer a customer support channel to each customer, building further trust with customers, emerging competition from within the fintech industry, limited in-person customer engagement and a relatively slow rate of launching new products.
The majority of financial institutions view personalised services as an ideal opportunity to attract new customers. However, data shows that only 16% of financial businesses are using data to provide financial guidance to their customers.
The key drivers for financial businesses investing in personalised services are improving customer acquisition and retention, generating new revenue channels and improving customer connections. Financial institutions cite challenges with implementing AI because of the necessary changes needed to their business. This includes adjustments to their technology, skill changes, management support and creating a new business startup culture in an already established business.
The next stage in delivering the digital bank of the future is enabling a more comprehensive use of AI and other digital technologies to connect and engage each customer. Financial institutions worldwide need to focus on AI, big data analytics and processing power, as well as implement the necessary changes and strategic partnerships required to meet the expectations of their customers.
The pandemic has increased digital adoption across all business industries. The finance function must embrace new technology and develop the necessary new skills to maintain its position.
Mark Cracknell, the head of research at digital firm Generation CFO highlights a glaring disparity between how people operate in the workplace and their personal lives. Cracknell explains that in our personal lives we are relatively digitally advanced but when we are in the workplace we regress to manual activities.
This situation is changing and the next generation of workers are questioning why operations aren’t more digital and automated. The pandemic has also accelerated the digitalisation of the workplace and the necessity for more timely data. Cracknell believes that people will have to go down this route, to be more cost-efficient and technology can provide the answer.
Cracknell refers to the NHS Shared Business Services as a good example. On a Generation CFO webinar, the head of finance and accounting said the team wouldn’t have been able to survive over the last year or so had they not established a strong digital position as they entered the pandemic. The organisation used to have over 100 people working on manual tasks and distributing invoices, but adopting e-commerce enabled them to reduce this number to 11.
The digital skills finance team is relatively broad and not everyone working in finance will be good at the same thing. Team leaders will need to be capable of identifying various skills and harness this potential to get the best results. One of the initial steps needed in regards to upskilling in finance is understanding exactly what technology can do.
The skills required within the finance function can be divided into two categories. One side is more technical and focused on understanding data, how to use and read data and generate the right conclusions from it. This includes knowledge of the capabilities and limitations of automation and AI. The skills that generate the most value are the more human-focused skills, including storytelling, influencing and presentation. The key is being capable of understanding the data and creating a supporting story and sharing this information with leaders in a way that will influence future decisions.
David Anderson, partner at Deloitte MCS collaborated with the ICAEW on Finance in a Digital World, a training service to support understanding and awareness of the potential of digital technology. Anderson highlights the focus on technical skills as one particular challenge the industry faces. Anderson explains that as we progress towards a more digital and flexible future, areas such as problem-solving, creativity, questioning the norm all become more important and should not be considered technical skills.
Understanding the dynamics of a team is vital when deciding how to upskill finance with a more digital approach. It’s also influenced by talent acquisition, by focusing on attributes and behaviours, rather than just technical ability.
Cracknell and Anderson describe an approach that incorporates a combination of technical skill sets concerning data management, AI, machine learning and the development of more commercially focused human skills. Cracknell suggests a combination of digital-focused education and ensuring people gain hands-on job experience.
Cross-generation mentorship, where younger staff teach more experienced staff digital skill sets in return for business and organisational skills can be beneficial. Anderson recommends supporting curiosity and encouraging everybody in the business to acquire a certain level of understanding around these industries. The ICAEW Data Analytics Certificate Programme supports the finance team with learning to harness and understand data and how it influences a business.
While it’s not considered like this, data could be interpreted as one of the most important commodities on our planet. Every day we produce data, businesses collect it, extract useful information, convert it into actionable insights, and then develop new products and services.
Data sharing refers to an agreement that involves waiving privacy for commercial purposes. Customers benefit by having higher access to relevant products which financial service institutions benefit from enhanced marketing and development opportunities.
In a recent article by Deloitte called ‘The next generation of data sharing in financial services, the FSI benefits of data sharing are split into 3 key categories:
- Inbound data-sharing and converting this into more focused decision making.
- Outbound data-sharing enables businesses to harness capabilities that may be missing from their organisation.
- Collaborative data sharing allowing businesses to develop richer, larger and more detailed datasets than possible with siloed data.
Despite the clear mutual benefits of data sharing, there are still several challenges and issues to overcome. For customers, there is caution with sharing sensitive information. Statista discovered that over 44% of US fintech app customers had experienced some level of reluctance in terms of information on accounts, loan or investments. Another survey conducted on behalf of IBM discovered that only 20% of customers had complete trust in businesses to maintain their data. With major data security breaches rising, it comes as no surprise that customers are a little hesitant with sharing their information.
What are the key benefits of data sharing?
For the institutions, it means better decision-making and the ability to broaden their capabilities and generate greater volumes of data. For the regulators, it enables further innovation and effective system oversight. Customers have access to higher quality and more relevant and efficient products.
What are the drawbacks of sharing data?
For institutions, there is the potential of breaching privacy regulations and impacting relationships with customers. Similarly, regulators could experience possible cases of breaching customer privacy and customer’s data may be mishandled or misused.
Data sharing does come with risks for FSI; developing a scenario of openness could eliminate competition bypassing too much information to rival businesses. Evolving privacy regulation could be breached by changes in technology.
The value of Open Finance
Open Finance is focused on empowering customers, giving them the ability and control to reuse their financial data in new and innovative ways. It does this by enabling third-party providers to securely access data and put it to work for the customer. This can be done by:
-Consolidating accounts into a unified view
-Enabling electronic data transmission that eliminates the necessity for physical documents when applying for financial products
-Using data as a method of identity verification
This is all included in open banking, allowing for a more direct consumer-banking relationship. Customers are increasingly looking for financial data aggregation services because it makes personal financial management simpler and more accessible. Banks and fintech both want to represent the primary platform for financial services and are currently competing to retain and attract new customers.
Implemented in the right manner, the benefits of Open Finance for both customers and businesses make it an attractive option. There is, however, a constant security concern. Data sharing, at any level, should remain a top concern, with each section of data requiring the appropriate level of protection and ensuring customers have an understanding of how and why some data is used. Informed consent involves understanding the implications of sharing before approval. It’s clear that aside from general clarity with data sharing policies, customers also need examples that show why APIs are beneficial and what exactly Open Finance can do for them.
A recent partnership between TrueLayer and UK digital bank Monzo showed this in action. With customers using Open Finance as a payment option for online gambling, Monzo required a solution to protect at-risk customers by blocking certain transactions to selected gaming sites. TrueLayer started working with Monzo, implementing a specific API capable of notifying the bank whenever a customer with gambling restrictions on their account attempted to pay via Open Finance. TS Anil, the CEO of Monzo praised the partnership, stating that it was simple to develop and capable of protecting thousands of people. Such examples in the finance industry will be critical in convincing customers that data sharing can be responsible and support safeguarding.
Data sharing via Open Finance is a route towards enhanced convenience, better products and considerably cheaper operations for FSIs. Ensuring customers understand the benefits will be the priority and experts highlight that managing physical financial documents will become a thing of the past.