Carmine Rimi, Product Manager AI and Kubernetes, Canonical – the company behind Ubuntu
Artificial Intelligence (AI) has witnessed extraordinary growth in business circles over the past few years. So much so that it feels an omnipresent buzzword in corporate technology conversations the world over. The advent of cloud computing and open source initiatives have supported the rapid expansion of these technologies, which are experiencing huge investment from both multinational businesses and smaller enterprises.
Deloitte’s Digital Disruption Index highlights that 85% of senior executives plan to invest in AI by 2020, while Stanford University’s AI Index reports a six fold rise in the annual investments from venture capitalists into AI start-ups since 2000, with significant quickening of that investment after 2010. Moreover, Gartner predicts that the business value resulting from AI initiatives will hit $3.9 trillion by 2022, rising from $1.2 trillion in 2018. These impressive figures serve to underline the huge potential AI boasts.
The trend towards the adoption of AI shows no signs of abating. In a software dominated world, AI acts as a trigger for business growth, innovation and the launching of new, advanced services for consumers. However, the deployment of AI technology is not a straightforward process, and no industry is immune from this complication. There are many considerations prior to a business being able to enjoy the advantages AI can deliver.
Business have had to discover that rolling out AI technology can be problematic. From concerns around integration with current systems, to a lack of understanding around how AI works, it’s clear that there are broad and complex challenges. A recent report from Databricks, for example, stated that 96% of organisations are experiencing data-related problems such as inconsistent datasets, while 80% reported a lack of collaboration between data engineers and data scientists. Then we come to the question of compute power. AI solutions tend to leverage large reserves of processing power, which will rise as data volumes rocket and the algorithms driving these systems grow increasingly more complex. This presents some large concerns around scalability.
It’s important to note that, from a practical point of view, AI technology is very much in its infancy but is developing rapidly. While the technology has been spoken about for some time, it is only during the last few years that deployments have started to take place and increase.
Challenges to AI deployment can even emerge before the roll-out begins. One of the major barriers for AI is IT teams and business leaders understanding how it can be used for everyday business problems; and also, how it can fit to the specific requirements of the company. As opposed to deploying AI for the sake of it, companies should look at where the technology can make the biggest mark, and what specific processes would benefit from being automated. This is easier said than done. AI requires people with knowledge who can seize the challenge of turning the theory into profitable outcomes. AI encompasses a range of processes and technologies, such as machine learning, data transformation, model creation, natural language processing and deep learning. To derive the most value from these it is essential to understand the differences between these innovations. So, what does it take to deal with these issues to realise the potential of AI?
Making the most of AI
Capitalising on the power of AI comes down to a few key factors. Primarily, it’s crucial that companies understand the importance of rolling out back-end infrastructure and systems which can support the compute-intensive tasks involved in AI and machine learning. Operating systems then have to be adjusted to these sophisticated workloads, which allows businesses to work with huge datasets, deploy applications at scale and manage the complexity that comes with that. Getting AI systems operational takes a lot of time, effort, expertise and resources – which are not always at the disposal of an organisation. AI platforms are only as good as the people who programme them. The industry skills shortage can impact businesses, so it’s important to partner with experts who are able to guide them and address any internal gaps. Enterprises need to be considered in the way they introduce AI, creating a long-term strategy and investing in the right people with the right set of skills and experience.
Harnessing the power of AI may be easier said than done, but no one doubts it presents a phenomenal opportunity. A laser-like focus on how AI can be leveraged to solve business challenges will help. AI has been growing in intelligence for some time – now businesses need to follow that lead and realise the true potential of this remarkable technology.
HOW CHARITIES CAN MEET TOMORROW’S DIGITAL CHALLENGES?
By Steve Georgiou, Business Consultant at Xpedition
Charities are under constant scrutiny for how they handle their finances. Budgets are often squeezed and as a result, it can be hard to justify spending on mediums such as new technology, which aren’t always seen as “necessities.”
And yet, there’s a new generation of workers waiting in the wings who have grown up using technology in all aspects of life. There are also 57% of charity employees who believe the sectors’ development is being hindered by lack of embracing new technology. For those that are willing, a digital strategy has never been more important for a charity’s future outlook.
The Next Generation
Many organisations are not prioritising the technological expectations of today’s younger generation. -. Everything outside of the workplace for the upcoming generation is already technology-driven, including the skills they’re learning right now. It’s already disrupting industries and career plans, and by the time this generation steps into employment, the way we live and work will have become even more advanced.
Competition in the Third Sector has always been on the up. Donation methods have changed, securing funds has never been more competitive, reporting is now a lot more stringent, and the next generation of employees have defined efficient methods of ensuring the organisation they are employed by is not left behind.
For charities that are using legacy financial systems that are often old, outdated and costly to maintain, if they do not take the steps now to digitally transform, they’ll fall further behind. Good governance dictates Charities should be investing in modern technology to support the organisation in both its medium- and long-term digital strategy. Ultimately, Charities want to engage stakeholders and employees, simplify processes, streamline efficiency and guide change – but they cannot do this without investing in modern technology to enable change in this fast-moving digital world we live in.
A Digital Future
In times gone by, financial systems were predominantly used to support the back-office finance function. This has all changed. With advances in technology, such as the latest all-in-one financial management solutions, there are now tangible benefits that add value to the whole organisation.
These tools can strengthen decision making, reduce administration time and provide real-time, accurate reporting, all of which are valuable assets for tomorrow’s demands.
There is a real case to be made for a fully digital third sector using financial technology one which thrives and gives not-for-profits huge benefits:
Data Management and Analysis
The contemporary digital landscape is all about big and beautiful data. Job roles are evolving to cater for the data boom, organisations are now hiring increasing numbers of Data Analysts and Business Analysts. And one of the most significant benefits that the third sector can expect to see by taking on digital methods is greater data transparency.
The world’s most valuable resource is no longer oil, but data. Data is being transformed into a core asset, one which is being used to tackle charity-wide challenges. Daily admin duties such as data analysis and entry are being taken over more and more by financial management solutions. This not only removes the need for online time-heavy tedious tasks, but also reduces the number of different sources people have to use to find and analyse data.
Whether it is finance, fundraising, HR or anything else, the efforts of the organisation should be in the analysis of the data to make better informed decisions in the best interests of the charity.
Use Cloud to Reduce TCO
The resistance to change and the associated investment have been barriers to digital transformation for charities. Every organisation wants to achieve greater efficiency and free-up further funding for their frontline
Activities, such as maintaining hardware and the disruption of upgrading are all a thing of the past.
From maintenance to mobility, cloud computing can help you to significantly reduce the Total Cost of Ownership (TCO). With the cloud, there is no need for onsite hardware or expensive upgrades – you are simply sent a URL for storage. This offers you the flexibility to scale your data storage capacity depending on your needs at the time, avoiding the need for expensive hardware. This on-demand, “pay as you grow” approach avoids hedging your bets on unnecessary data storage. The cloud also has greater mobility, allowing for remote workers to access communications from anywhere, with no further technology needed. Backup and restore can be initiated from any location, using multiple devices, and does not need maintenance – reducing the need for a dedicated IT person.
Consider Digital, before your Charity becomes marginalised.
With a new generation of workers waiting in the wings, and financial management technology that has the power to provide value for all aspects of the organisation, a digital strategy has never been more important for a charity’s financial efforts. They will not settle for a business that is stuck a decade behind due to not embracing change.
COUNTING THE COST OF SILENT CYBER
– Akber Datoo, Founding Partner, D2 Legal Technology
Damaged reputation. Financial loss. Punitive capital adequacy provision. Silent cyber is one of the biggest issues facing the insurance industry. Yet despite the Prudential Regulatory Authority’s (PRA) demands for robust action plans, few firms have put in place the document digitisation required to truly understand the level of risk. Further, it is somewhat ironic that an industry that is predicated on pricing risk, is failing to assess and understand this risk that exists today in its back catalogue. From determining the current silent cyber position to identifying policy wording changes and analysing the legacy book, Akber Datoo, Founding Partner, D2 Legal Technology, highlights the need to digitise policy documents.
Non Affirmative Loss
“Silent Cyber” is the term given to cyber related losses that may/or may not fall under a traditional property and liability policies that were not designed for that purpose.
The concerns of silent cyber have recently come to the fore and the shock waves created by the Mondelez / Zurich Insurance case have reverberated around the market. Whilst publicity may have temporarily abated over the past few months, very few insurance companies have begun to truly address the risk posed by silent cyber. In an industry predicated on strong reputation, the decision by Zurich to reject a claim from a client whose business had been devastated by the NotPetya cyber-attack in 2017 made headlines around the world – not least for citing exclusion for ‘hostile or warlike action in time of peace or war’ by a ’government or sovereign power’.
Yet as the cost of such attacks are being counted, the impact of silent cyber on the industry as a whole is becoming painfully apparent. PCS Global Cyber has recently attributed 90% of the insurance industry’s losses relating to the NotPetya cyber-attack to non-affirmative (silent) cyber, and the rest to affirmative losses.
Certainly, the PRA believes the UK insurance industry can do more to ensure the effective management of affirmative and non-affirmative cyber risk exposures. It has ordered firms to develop an action plan, with clear milestones and dates by which action will be taken.
Despite the cost to the industry, there remains a concerning lack of consistency in terms of risk awareness and planning as well as risk appetite and understanding. The PRA’s own survey in 2018 revealed significant divergence in firms’ views of the potential exposure to silent cyber. Within Marine, Aviation and Transport (MAT), Property and Miscellaneous lines, exposure was rated at anywhere between zero and the full limits.
With PCS Global Cyber believing the cost to the industry of NotPetya associated claims has now exceeded $3 billion, there is ever greater focus on insurance companies’ cyber stress tests. Fears that gross losses could run into the multiples of annual cyber premiums are very real. However, to date such exercises are based on minimal fact: firms lack robust or reliable claims data relating to silent cyber. As a result, models are immature and there is little faith in the resultant capital adequacy calculations. Just how much capital should the regulator demand firms to set aside against possible exposures when the silent cyber risk is so poorly understood?
In addition to the model and assessment demanded by the PRA, firms need to look closely at existing policy documentation to gain better insight into risk. What is the current position? Does wording need to be amended to address silent cyber risk? How can the legacy book be analysed and key data and wording from the contracts extracted to assess the potential silent cyber exposure going forward?
In many ways, the insurance industry is better placed than many for the challenges ahead. Document digitisation has been on the agenda for some time and the industry has already created clause libraries to make it easier for firms to gain access to vetted policy wordings and regularly used clauses. However, the low take-up of these libraries is disappointing. Not only do firms have a somewhat confusing choice – between the Lloyd’s Wording Repository, the IUA (International Underwriting Association) Clauses Document Library and the Xchanging Model Wordings Library, but the checklist structure is not providing the required solution.
Insurance companies and brokers need to better understand how to use these clause libraries within current business models, preferably in tandem with a document generation tool to improve data management. The goal is to create data driven contracts, where documents are drafted based on known outlooks. But to get to that point, firms need to actively embrace document digitisation to gain a better handle over the current risk position and create a foundation for rapidly changing wording to avoid any ambiguity regarding silent cyber. Moreover, we need the link wordings in clause libraries to classified business outcomes, and then derive business intelligence from policy portfolios.
No firm wants to risk the reputational damage associated with refusing a high profile claim – nor endure the huge losses associated with attacks such as NotPetya. With the rise in cyber attacks, this is an issue that has to be addressed immediately: firms need to act now and embrace the opportunity of digitisation strategies within policy documentation to mitigate the potentially devastating silent cyber risk.
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