By Dave Jones,VP of Product Marketing at Content Services Platforms supplier Nuxeo
How can traditional financial institutions stay relevant as big-tech companies flood the market with a new wave of financial customer service innovations? Nuxeo’s Dave Jones proposes four digital strategies for survival.
As open banking continues to disrupt the financial services industry, financial technology innovators – from small fintech startups to the internet giants – are increasingly making their presence felt. Which means that traditional financial institutions can no longer rest on their laurels if they want to stay relevant to existing and prospective customers. Gartner asserts that, within a little over a decade, 80 per cent of established players will go out of business or suffer other ill effects as more attractive alternatives enter the market.
Customers are hungry for change, too. Frustrating service experiences are stoking their appetite for something new, and a provider’s digital prowess is often the primary appeal.
So why haven’t traditional banks upped their game? Digital transformation is hardly new to the FinServ agenda, yet to date, the established players have largely failed to deliver anything significantly different and exciting.
At a very practical level, major institutions are not set up to be agile. Even today, over three-quarters (76 per cent) of organisations simply can’t find the information they need to deliver digital service innovation, according to recent research by Nuxeo. Nearly the same proportion (75 per cent) want to extract the required data from “locked” legacy systems; and 79 per cent can’t connect different data sources to support more dynamic services.
By contrast, alternative financial service providers, particularly the big-tech brands, are less encumbered by traditional information systems – for instance enterprise content management (ECM) solutions, which have failed to evolve with modern priorities.
4 actionable digital strategies
As 2019 gets going, there are four practical steps banks might take to safeguard their future:
- Accept but move on from legacy constraints
Rather than think in terms of costly rip-and-replace programmes, or complex systems integration projects, there is a way to move forward while still exploiting legacy investments.
One very practical option is to deploy a cloud-optimised content services platform alongside existing core business and IT systems. It means departmental or function-specific systems can stay as they are for now, but the organisation can tap into their contents in support of additional and new use cases. These could include faster credit approvals, a more consistent experience across different customer touchpoints, or new product development.
One of the immediate problems this approach addresses is the complexity of managing different types of data and content (video content, audio files, images, etc). ECM grew out of document management, yet most businesses today are not managed according to document-centric processes.
The flexibility needed to be more customer-centric relies on being able to efficiently and easily unlock information contained within documents, and combine it with other data to build a more complete picture, allowing fast decisions and next actions to happen – aided by intelligent automation, where possible. This in turn could help reduce application approval times, for example.
The fact that content services platforms have been designed from the outset to be run on a cloud-based infrastructure means they are inherently flexible, scalable and futureproof too. They can potentially support any future customer service proposition banks may roll out.
- Achieve a clear line of sight across content silos
Even if information is stored in diverse systems, being able to see and access it all via one central hub will make it easier to manage everything from security, data protection compliance and customer permissions management, to new service innovation. The more complete the insight, the easier it will be for responsible teams to identify new product opportunities and/or maintain compliance.
- Innovate incrementally and at a faster pace
Once banks are free to do more with information they already have, they can start to press ahead with specific service improvements for customers. That could be something as simple as giving customers real-time insight into their overall financial status, across multiple financial products and reflecting up-to-the-minute payment activity.
- Delivering benefits today, while preparing for the future
After being limited for so long by locked-down data and finite system capacity, it’s important that banks build scalability and future-proofing into their strategies for information management. Avoid being too prescriptive about IT systems at this stage, and instead keep your options open by leveraging a platform that has the adaptability and scalability to support future growth..
The author is VP of Product Marketing at Content Services Platforms supplier Nuxeo [www.nuxeo.com/?utm_source=PR&utm_medium=UK]
A detailed ebook exploring practical ways forward in financial services, 5 Digital Strategies to Overcome the BigTech Threat in Financial Services, is available to download on Nuxeo’s web site
WHAT EVOLUTIONARY AI MEANS FOR FINANCIAL SERVICES
by Babak Hodjat, VP of Evolutionary AI at Cognizant
Many banks and other financial services institutions (FIs) are beginning to recognise the benefits of AI-driven solutions as a way to get ahead in the market and challenge the competition. Amongst many other benefits, the technology enables organisations to offer hyper-personalised customer experience, dramatically improve internal decision making, and drive operational efficiency. However, many businesses are struggling to move beyond the experimental phase and reach actual AI deployment. It is those organisations that are at risk of being left behind.
The financial world has already been transformed by AI, and this transformation is continuous. A new breed of AI, known as ‘evolutionary AI’ has begun to further accelerate innovation. It is capable of automatically designing itself with little need for explicit programming by humans – innovatively creating complex AI models, and optimising decisions considering multiple scenarios.
This technology is revolutionary for industries across the world, but in particular it is set to transform the financial services sector. Enabling businesses to spot novel strategies that would never have been identified by human data scientists, and, in turn, allowing companies to take full advantage of today’s massive data sets – evolutionary AI will soon be a vital tool in all FIs’ arsenals.
The nuts and bolts of evolutionary AI
Emerging technologies that enable AI algorithms to design themselves are allowing organisations to transcend human limitations. Evolutionary AI operates iteratively. Firstly, it randomly generates a set of potential solutions to form an initial population and assigns a score to each solution based on how well it performs relative to other solutions. In the second round, it retains the solutions that performed best, perhaps only 5% of the total, and recombines their components, sometimes “mutating” them to create a new population. This new population is then tested, and the process begins again. Over multiple generations, the appropriate components of the more successful solutions become increasingly prevalent in the population, and eventually a solution is discovered that yields the best outcomes.
Advantages and use cases
Compared to human design, evolutionary AI can be deployed far more quickly, avoids biases and preconceptions, and typically performs better. Furthermore, the chosen model will evolve and improve over time based on new data.
Evolutionary AI can be applied in a wide variety of areas at FIs. Some examples include designing quantitative trading strategies to maximise returns while minimising risk and loan underwriting. Rather than relying on human analysis, evolutionary AI solutions can quickly analyse all the combinations of relevant variables to create models that more accurately assess the risk of default by a potential borrower.
A recipe for success
In order to reap the benefits of the technology, FIs should focus on the following:
- Responsible AI – Behave in ways that make customers and employees comfortable, i.e. not making decisions that are unethical or exhibit bias. Companies need to monitor them to ensure they continue to act appropriately, as they learn and evolve.
- Viewing AI through a business lens – Having AI projects managed by cross-functional teams with business executives in the lead is a good place to start. Companies also need to look across their organisations to identify opportunities to generate concrete business value from AI — not only in reduced costs but also in boosting revenues by delivering enhanced customer experiences and through improved decision-making.
- Enhance data management – AI applications depend on access to timely and accurate data, which is a challenge for many FIs that have fragmented data architectures with multiple legacy systems. Companies need to identify which types of data are required for each AI project and ensure they can be captured in an appropriate format.
- Approach with speed and caution – AI projects need to be rolled out quickly, while at the same time be rigorously measured, so failures are terminated promptly while successes are moved into production.
The sophistication of AI technology is set to significantly improve over the coming years as it continues to design and test itself. As a result, it will become more critical to the productivity of FIs, and soon businesses will recognise it as a vital tool for consulting on important business decisions. It will not be long before humans and AI are working alongside each other, with robots handling routine tasks, enabling employees to focus on more complex and sensitive activities. Delivering more value together than either could on their own.
6 EXAMPLES OF ARTIFICIAL INTELLIGENCE IN USE TODAY
We’re probably not aware of the moment when artificial intelligence sneaked into our lives and became a part of our everyday existence.
Was it the first movie recommendation we got from Netflix? Or the item we’ve purchased using Amazon’s suggestions?
AI is now all around us, and it’s holding tremendous potential, with new application possibilities being discovered every day.
We’ve gathered six very practical examples of AI, to show just how widespread this technology is today, and how prevalent it is yet to become.
The use of AI in healthcare is already bringing many benefits – at the beginning of the year, we’ve witnessed AI outperforming six radiologists in reading mammograms and identifying breast cancer more accurately and quickly. A computer algorithm can now analyze images in just a few seconds, significantly improving the speed of diagnosis.
The first AI-designed drug molecule, by Excienta, is currently being tested on humans. While it usually takes three to four years for traditional research to reach this stage, it just took 12 months for the algorithm to make it possible.
As for the current COVID-19 crisis, the Chinese technology giant Alibaba has recently developed an algorithm that can detect coronavirus in seconds, with 96% accuracy. The algorithm that analyzes CT images of patients’ chests is used by more than 100 healthcare facilities to distinguish the disease from other viral pneumonia cases.
2. Virtual Personal Assistants
Alexa, Siri, Cortana, and Google Assistant are just some of the most notable examples of artificial intelligence we’re all familiar with.
We interact with our PAs regularly – ask them for directions, information about the weather and the news. They allow us to finish various tasks easily, without having to use our hands – we can stream podcasts, play music, make to-do lists, set alarms, schedule our meetings, or order pizza.
These voice assistants use machine learning technology and natural language processing so that they can get smarter and more capable of understanding voice queries. In other words, with the help of AI and its subsets, voice assistants learn from your previous searches and preferences and use all the information they collect to offer you better search results and service.
3. Customer Service
Even if you’re still not interacting with your devices using your voice assistant, you’ve surely communicated with AI at least once, most probably in the form of a chatbot.
There is hardly any good online store that doesn’t offer at least some kind of AI-powered customer support.
The most common are conversational chatbots that are now able to answer 80% of most common customers’ queries in an accurate and timely manner, without any need for additional human intervention.
With data AI chatbots gather on the customers, they are now able to facilitate human-like interaction and personalize it more than their human counterparts.
Conversational AI algorithms can now give offers and recommendations that are more likely to fit customers’ needs and interests, boosting both their satisfaction and retailers’ revenue.
The banking and finance sector has recognized the possible advantages of AI early on and is now successfully implementing the technology for various purposes.
The finance industry relies heavily on large amounts of data and accurate real-time information. With the use of AI, it’s now much easier to detect frauds, money-laundering, or any other suspicious behavior. Some of the financial advisors’ tasks can now be automated too, as AI-powered advisors can quickly scan the market data, and predict the best portfolio or stock.
One of the best examples of how useful AI in the banking industry can be, is Erica, an AI employee of the National Bank of America. This digital financial assistant has already served over 7 million customers and handled over 50 million queries. Apart from managing many other different tasks, Erica helps customers with their transactions and budgeting, tracks their spending habits, monitors duplicate charges, and gives useful advice.
5. Smart Vehicles and Delivery
Cars and drones are also shifting towards the use of AI. Even though artificial intelligence is widely used in car manufacturing, its use in the automotive industry is most commonly related to the use of self-driving vehicles, that are leveraging machine learning and vision to find their way through the traffic safely.
Autox is, for example, currently testing their autonomous grocery delivery within San Jose. Their vehicles use AI software, real-time cameras, and sensors to navigate within a geofenced zone, with plans for gradual expansion.
Amazon and Walmart are already investing large amounts of money into drone delivery programs. Amazon’s goal for its Prime Air service is to create fully electric drones that can deliver packages lighter than 5 pounds, to their customers located within 15 miles, in less than 30 minutes.
6. Smart Homes
One of the finest examples is Nest, the thermostat algorithm, which uses an intelligent machine learning process to learn about your behavior and the temperatures you like. It then anticipates and adjusts your home or your office to your temperature needs, at the same time saving significant energy resources.
Google acquired Nest back in 2014 for $3.2 billion and now aims to create a smart and helpful home. The tech giant is trying to connect devices such as thermostats, cameras, alarm systems, doorbells, and locks under the same roof, offering an easy to use smart home solution.
However, for this to work seamlessly, technological advancement in the field of IoT and 5G needs to be utilized. Near-zero latency is what allows for smart homes to be remotely controlled.
As you can see, AI is impacting and improving every aspect of our lives and our society. It will revolutionize the way we do different things, from driving our cars to receiving medical treatment. Although this technology is still in its infancy, it has already managed to disrupt the above-mentioned areas and offer us a sneak peek into the future.
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