Refinitiv Labs is shaping the future of finance through innovative AI-enabled solutions to real-world industry problems. Find out how our data science techniques have been used to transform wealth management and the search for alpha.
- Deploying an AI-enabled strategy will be the main differentiator for companies as they look for real-world solutions to challenges around risk and alpha generation.
- An example of how Refinitiv Labs is shaping the future of finance comes with our project to help markets understand the views and sentiments emerging out of China.
- The data science teams at Refinitiv Labs are spread across the world’s financial and technology hubs, including New York, San Francisco, Singapore, and London.
Data is everywhere. This sounds like stating the obvious, which only serves to further emphasize its ubiquity.
Consider the mountains of information that Refinitiv manages: more than 60,000 terabytes of data, including over 90 million data points on financial statements, nearly 12 million economic data time series, and eight million financial price updates processed every second.
To make more of this data, we have at our disposal technology-driven tools such as artificial intelligence (AI), machine learning, natural language processing and blockchain, as well as the means to store it all remotely, on the cloud.
So, what is it possible to do with all this firepower?
For Refinitiv Labs, the answer to that question is: Solve real-world problems and play a role in helping to shape the future of finance.
Shaping the future of finance
At Refinitiv Labs, the process of using technology to harness data — 80 percent of which remains unstructured — and create tools that enable companies to run their businesses more intelligently, has been 10 years in the making.
Over the years, Refinitiv Labs has continued to use its considerable in-house expertise and exhaustive resources of both data and technology tools to ideate and create innovative solutions.
Powered by AI, machine learning, natural language processing, deep learning and robotic process automation, these solutions can tackle challenges holding back business operations and, ultimately, help create new opportunities, while providing a smoother, more effective customer experience.
From ideation to completion, cross-functional teams comprised of engineers, researchers and design experts go through a rigorous six-step process.
These teams also possess a firm grasp of the issues affecting financial markets at a local, regional and global level, spread as they are across the world’s premier financial and technology hubs, such as New York, San Francisco, Singapore and London, which ensures smart, highly tailored solutions.
To help zero-in on a specific proof of concept, the emphasis is on two kinds of products: Risk avoidance and mitigation, and generating alpha. And ideas are typically sparked by closely observing a business problem, assessing the available data and technology, and figuring out how to use them to fix the problem.
Driving our approach is the knowledge that successfully deploying an AI-enabled strategy will be the main differentiator for companies in the future.
And helping us throughout the process is the open-source ecosystem and a network of partners, including big tech, start-ups, universities and trade associations.
Watch: Refinitiv at Singapore Fintech Festival 2018 — Powering the global financial community
Refinitiv Labs in action
Project Marco Polo is a standout example of Refinitiv Labs’ ability to identify real-world problems and create a solution to address them.
It is well known that global financial market participants are keen to understand views and sentiments emerging out of China, one of the world’s fastest-growing markets and its second-largest economy.
However, most of this information is in Chinese, making it hard for investors to decipher and tag the companies mentioned in the news for future reference.
Refinitiv Labs identified an opportunity to provide its clients a crucial edge by helping them to know when the companies they track are mentioned in the Chinese-language press.
The result is Marco Polo, which can tag company names written in simplified Chinese with the help of an algorithm that addresses the linguistic complexities of the script — such as the lack of spacing between entities — to enable notifications.
The tool also allows users of Eikon to view news produced by Reuters and other third-party sources in simplified and traditional Chinese.
This is just one example of a solution conceived and brought to life by Refinitiv Labs.
It provides a glimpse into the vast promise of what informed data scientists, aided by the right technology and data, can achieve in pursuit of the goal of adding value to the financial services industry.
Other solutions vary from tackling challenges in asset management by detecting signals from unstructured text — be it research, transcripts, filings or news — to using graph analytics and centrality measures to help fight financial crime.
Data, technology and people
There are a number of challenges in turning an idea into an industry-transforming product. They can be categorized into three broad categories: data, technology, and people.
With data, the problem at Refinitiv Labs is not availability — given the quality and extent of information we have access to. The challenge, instead, is to discover and combine ‘all’ the data that’s potentially aligned with and capable of addressing the problem at hand.
Similarly, identifying and harnessing the technology required to crunch data and run the necessary models are significant problems to tackle.
One way to address this is by leveraging the open source tech in phases of early discovery, which not only expedites workflows but also accelerates the team’s creative process, allowing the focus to be on problem solving versus technology build.
Then there is the human component. It is incredibly hard to find, motivate and retain talent that is not only data- and tech-savvy but which also thrives in an environment of constant change, speed and uncertainty.
Compounding the problem further — as most organizations will agree — is that it’s even harder to find talent who are both experts in their technical domains and, at the same time, can recognize and tackle business problems.
Watch: Refinitiv Labs, Singapore: Applied Innovation — Introduction
Data and the future of finance
As the old adage goes: Recognizing the problem is half the battle.
Indeed, Refinitiv Labs has over the years proven adept at addressing internal challenges in the same way that we approach proof of concepts — by constantly refining our approach to stay at the forefront of financial innovation.
And, as the future of finance becomes increasingly data and technology driven, Refinitiv Labs remains committed to creating solutions capable of successfully making the journey from drawing board to real world and, in the process, helping transform global finance.
In other words, we will continue to use data to showcase the art of the possible.
- AI & Machine Learning
- Artificial Intelligence
- Case Study
- Data Engineering
- Digitalization of Investment Banking
- Digitalization of Wealth Management
- Elektron Data Platform
- Future of Investing & Trading
- Generating Insights From Data
- Managing & Integrating Data
- Wealth Management