from “nice to have” to a necessity for success
The overall concept of digital transformation is to use technology to replace manual processes with automated digital processes and to replace old legacy systems with modern, agile technologies.
What was historically considered “a good idea for the future” or a nice addition or update to an outdated system has now become mission critical.
Digital transformation has become the benchmark for financial market survival, making it even more critical for success and innovation. As next-gen technology continues to transform, financial services companies and their management teams are preparing for the next phase of digital transformation.
And most recognize the need to embrace this digital acceleration, but are still too early in their journey to undergo the technology innovation, technology productivity and platform modernization that will not only set them up for success in the market, but will also set them apart from their competitors. .
Although it may seem simple, the challenge these organizations face is significant. Obvious resource barriers exist, such as time, money and people, while digitalization has also taken hold in the regulatory landscape, rapidly becoming the only way to meet stringent regulatory guidelines in global markets.
Faced with new or ever-changing regulations, financial services firms must radically change the way they handle these new demands. Moreover, even beyond the increasingly demanding regulatory environment, the overwhelming amount of data available is becoming increasingly time-consuming and expensive to collect, sort and analyze – and less and less manageable for humans alone.
At a tipping point, these companies must rely on next-generation technology that offers more efficient data management. Fortunately, as regulations and data have evolved, so have the capabilities of current technology, with the advent of AI, blockchain, and digital assets that automate processes and workflows.
Terminology and technology: what does it all mean?
We all hear so much tech jargon that sometimes we feel like it’s lost all meaning. However, understanding the nuances of terms such as hyper-automation, artificial intelligence (AI), machine learning (ML), intelligent document processing (IDP), and natural language processing (NLP) makes a significant difference for decision makers, who are ready to embrace the innovation and the benefits that flow from it.
While AI is the ability of a computer system to perform tasks that typically require human context and intelligence, ML and NLP are more like subsets of AI. They can be divided into different types of technologies – some of which require ML to function while others require NLP. On the other hand, they can be divided by level of intelligence within an AI machine.
An automatic and predictive approach to AI, ML allows the machine to learn (for lack of a better word) from historical data. This can be applied in many different ways – think of how chatbots use voice recognition or how you unlock your phone with facial recognition – but it can also be used for more precise medical diagnoses or to extract data of a document.
Additionally, NLP applies ML to human language, interpreting it for the technology to be used. By using NLP and AI, new technologies can be even more precise, extracting key terms and details from loan documents while reducing the time and increasing the accuracy of manual information processing – a great way to combat the aforementioned regulatory and compliance standards.
Most people will agree, the complexity of this often seems like a great reason to avoid digital transformation all together. Fear is often the biggest hurdle in organizations moving forward with digital transformation, because let’s face it, no one wants to embark on a project they don’t understand.
Fortunately, adopting new technology doesn’t have to be inhibited by a lack of understanding. Whether your business employs a talented IT team to manage and translate your new technology or deploys a no-code solution that is easy to navigate and requires basic understanding, there are a myriad of next-gen solutions available to meet various needs and levels of understanding. . .
Digital transformation 2.0: the next phase of innovation
Long gone are the days when it was enough to talk about digital transformation strategies and future plans – action must be taken. Whether you’re ready or not, the competitive landscape demands true innovation, which means now is the time to implement and execute these strategies. The task can seem monumental, especially in a space as highly regulated as financial services, where a single misstep can cost dearly.
Ironically, the need for this transformation often comes from the pace of change of regulators, which continues to accelerate, enacting stricter rules and restrictions, sometimes even put in place due to the functionality of new technologies that offer more faster, more accurate and more transparent. information.
While the regulatory need is great, new technologies offer far greater benefits than just regulatory compliance, such as more efficient and streamlined data management that provides actionable insights for better and smarter business decisions – added value that is not possible without the use of AI-integrated technologies.
How to make the most of your data: your highest good
It’s no secret that data is important, but did you know that between 80-90% of business data sits unused, untapped and unavailable, according to McKinsey? And without technology, your data would continue to be unstructured and unanalyzed, due to the time and manual effort required to manually organize and analyze information. Think about the competitive advantage of not only having access to this data, but unlocking the hidden value and insights of this data.
In summary, the biggest digital transformation challenge businesses face is having an influx of data, with no real roadmap for what to do with it. But by changing the way you manage your data, there’s a critical opportunity to cut costs, drive efficiencies, and save time by reducing manual work, while reducing market risk.
As the pandemic has spurred market volatility, data transparency and oversight has become a priority for many financial services firms looking to get the most out of their data while staying compliant with ever-changing regulations.
Using artificial intelligence tools to automate both processes and analysis enables institutions and financial services firms to increase risk awareness, accelerate reaction times and make decisions smarter, all underpinned by intuitive and accurate data, which can also offer a deep dive into critical business information. , relevant market trends and unique customer behaviors.
With more and more fintechs and “techfins” (like Google and Amazon entering the financial services space) entering the market, established institutions are increasingly in need of a competitive edge. It’s easy to lose focus and think that these companies only pose a threat because of their expertise in technology – but that’s not the real threat. This is the data that their technology can access. Without investing in new technologies, innovations, and ultimately digital transformation, these companies will continue to encroach on the market, potentially posing an even greater threat.
And sadly, research continues to show that among banks – even those who say they are halfway through their digital transformation journey – only 14% have actually deployed machine learning tools to date. This means that many of these institutions are unprepared for future innovation – and their digital transformation will likely be overwhelmed before they even cross the finish line.
At least it proves that investing in technology isn’t really just a cost to be justified. Instead, it must be an integral part of your long-term growth strategy – a strategy that is not only innovative to meet current standards, but also forward-thinking to meet future needs, expectations and perhaps more. importantly, to regulations. Because organizations that successfully leverage their valuable data sources will be armed for success.
With the pressing need to advance digital transformation, the solution is obvious: the next phase of digital transformation is now.