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Top Companies Reveal Their AI & Big Data Strategies at European Summit

March 15, 2021 (4 min read)

Executives from major companies came together late last year to discuss how AI and big data are transforming their businesses at the AI & Big Data Expo Europe. More than 150 people took part in the two-day virtual summit, which featured speakers sharing how central AI and big data have become to the strategies and operations of major organizations across virtually all sectors. They included:

  • Alexei Cherenkov, Senior Data Scientist at Philips.
  • Jeroen Van Genuchten, Global Product Owner of Robotic Process Automation at ING.
  • Lara Suzuki, Data/AI Technology Practice Lead at Google.
  • Gillian Tomlinson, Director of Data and Analytics at Three.

AI for financial services

Not surprisingly, a large proportion of the speakers represented financial services organizations, including ABN AMRO, FBN Bank and ING. The sector has been at the forefront of AI and big data adoption to inform investment strategies, accelerate credit and loan decisions, and conduct third-party due diligence. Financial services organizations can complement internal data with third-party data such as news and broadcast interview transcripts to surface buy/sell signals or key regulatory lists, such as PEPs, sanctions, and watchlists, to anticipate and better manage risk exposure.

Robotic Process Automation (RPA) is one of the fastest-emerging areas of opportunity for banks for accelerating repetitive tasks, such as RPA for third-party due diligence. Jeroen Van Genuchten, Global Product Owner of Robotic Process Automation at ING, said that the financial services company has “put Robotic Process Automation at scale into the organization”. ING uses RPA in a number of ways:

  • Provide immediate responses to customers when they make a simple request like registering a change of address, or a more complex transaction like a mortgage application.
  • Support ING employees by providing a “digital assistant” to handles many of the more manual and repetitive tasks.
  • Understand unstructured or semi-structured paper-based data that come into the bank, such as salary slips or bank statements.

He said the bank has already seen several benefits from its use of RPA, including:

  • Improved employee morale because robots “take away the more repetitive and mundane tasks”.
  • Improved customer experience because RPA means customer queries can be answered more quickly.
  • Reduced risk of errors in areas such as third party screening and due diligence.

Mr. Van Genuchten said RPA was invaluable in giving the bank speed and flexibility to respond to the COVID-19 crisis earlier this year. In a short space of time, ING was inundated with requests from customers to take payment holidays because of the financial strain caused by the pandemic. RPA allowed the bank to handle these requests quickly. “Within a few days we were able to put robots into the business to create the scripts for these payment holidays,” he said. “RPA allows us to be very fast, we can ramp up a team or a process in a very short period.”

AI for research

Research and academia are another area where AI and big data are having a particularly significant impact. Universities, research institutions, governments, companies, and public-private R&D partnerships have taken steps to upgrade their use of data science to boost research and innovation in recent months. Some of these new projects aim to use data science to provide insights into possible causes of and solutions to the COVID-19 pandemic.

The potential of AI for research is enormous. For example, data analysis of large datasets of text-based news articles can be used by academic researchers to analyze political discourse and identify trends. Product development can analyze patents data to understand the competitive landscape and track emerging innovation trends.

But AI is affecting all industries, not just finance and academia. Romaric Redon, AI Fast Track leader at Airbus, explained how AI is “already transforming all Airbus”. For example, AI has been successfully deployed to predict when Airbus’ various vehicles will need maintenance. This is not only good for safety, but it allows the company to be more efficient in when it carries out work on its planes.

AI & big data offer a competitive advantage

Another message from the Expo was that simply buying into the need for data science and AI in your business is not enough to guarantee success. Too many companies fail to maximize their use of the technology. A presentation by Harvinder Atwal, Chief Data Officer at Moneysupermarket Group, reported that:

  • Only 7.3% of organizations say the state of their data and analytics is “excellent”.
  • Only 22% of companies report seeing a “significant return” from their expenditure on data science.

There are a number of reasons why that might be. High volumes of raw data from multiple sources and in numerous formats require secure and efficient processes to convert them into useful insights. Senior management needs to embed a culture of listening to and understanding data science across the company. Companies that harness data and technology in the right way can discover new insights, drive efficiencies, and manage risk more effectively. So, it is not too late to find a competitive edge by adopting AI and big data. What are you waiting for?