The ability to write text summarizations is an important application for AI. Natural language processing can help explain complex information and provide key insights for those who are not data experts.
It can also create more engaging and readable content for humans. It is often difficult to tell if a piece of content was created by a human or a robot.
How does Commerzbank use AI
When Tomak first joined Commerzbank in 2017 to establish the bank’s Big Data and Advanced Analytics function, he learned early on that getting top-down support was key. He interviewed each member of the Management Board, seeking their commitment and understanding of the need for a new data-driven approach to the banking industry. He also used OKRs – Objectives and Key Results – from his time at Google, which helped him set achievable, short-term milestones for his team.
To that end, the German bank has partnered with Restresco, a Berlin start-up specialising in content automation. The company became famous for its robot that writes football news articles, but is now being adapted to create research reports for Commerzbank.
The move comes as many banks look to cut their research costs following new European investor protections known as MiFID II. The regulation requires that investors pay for research separately rather than having it bundled into trading commissions. This has led to a decline in research income for some banks, with UBS and Barclays currently focusing on alternative data sources for their analysis.
In addition to reducing costs, AI can also help improve the quality of analyst reports by making them more accurate. However, this depends on the availability of robust data sets that represent multitudes of customer activities. Without this, AI models would be limited in the information they could synthesize, and their outputs may be constrained or irrelevant to only small groups of consumers.
Is AI reliable for writing reports
Despite the many benefits of AI writing tools, there are some ethical concerns surrounding their use. For example, these systems may not be accurate enough to detect plagiarism or can produce content that is jarringly inappropriate or does not contain context. As such, educators must strike a balance between discouraging students from using these tools and maintaining academic integrity.
In addition, AI-generated text can often sound clunky and unnatural, which could be problematic for some users. This is especially true for longer pieces of writing such as articles. However, AI writing tools can help to improve the quality of these documents by incorporating SEO keywords and creating content that is appealing to readers.
In addition, AI can also be used to generate detailed bug reports that can help software developers find and fix bugs in their products. This can be done by analyzing data and identifying patterns that indicate when a bug is likely to occur. This can lead to faster resolution of issues and more efficient development processes. This technology is already being used in a variety of industries, including healthcare and financial services. For example, AI can analyze patient history to predict when a patient is likely to develop a disease or identify potential fraud.
What are the benefits of AI in analyst reports
Traditionally, research has been a manual process. Even when teams are dedicated to collecting, analyzing, and disseminating information, there is always a risk of overlooking critical information or missing important data points due to natural human limitations. AI can help mitigate this risk by aggregating multiple content sources, sorting for relevancy, and using NLP to quickly find insights in the noise. This allows analysts to get a more holistic view of what’s happening and predict market shifts before competitors who are not using AI.
In addition, AI can help analyze large sets of data and create insights that would be difficult to discover manually. This enables analysts to find valuable insights that can improve business performance and enhance decision-making. Furthermore, AI can help streamline the analysis process by enabling analysts to create collaborative and customisable dashboards that are easy to understand and keep track of.
While many people may assume that AI is still several years away from being able to write research reports, Commerzbank has already started experimenting with the technology. According to the Financial Times, the company has partnered with Restreco, an AI-powered content-automation company, to create research reports on earnings reports. The bank believes that the software is currently capable of doing about 75% of what a human equity research analyst would when writing an immediate report on quarterly earnings.
Is Commerzbank’s AI efficient in writing reports
Commerzbank has partnered with Restreco, a content-automation company, to work on creating a way to write research reports using AI. While this technology is not yet ready to be used to write reports that are sent to customers, it could eventually replace some of the bank’s financial analysts. The partnership is expected to yield results in the near future.
One of Commerzbank’s goals is to offer full digital access to its banking services for private and business clients. To achieve this goal, the bank is developing a new mobile app and online platform that will give users the ability to control their finances from anywhere, at any time.
The new system will perform confirmation, affirmation and payment message generation, settlement netting and processing, matching and reconciliation, exception management and full reporting for trading in interest rate, commodity, credit and equity derivatives. It will also help banks transform back office processes by enabling critical processes to be controlled holistically and adjusted when necessary.
In addition, the new system will allow Commerzbank to improve its risk controls and customer service. The bank hopes to have the new system up and running in 2019. The company has also partnered with fintech Conpend to automate selected compliance relevant pre-checks for its trade finance transaction processing by 2020.
How accurate are AI-written analyst reports
There are a number of companies that advertise AI writing, but how accurate are they? To find out, the team at Turnitin tested a number of AI writing tools by creating academic papers and comparing them to human articles. They found that the AI text detection model they developed was able to distinguish AI-generated papers from human ones with 100% accuracy, and it outperformed existing AI text detectors available on the market.
The team also identified certain traits that AI writers have, such as a tendency to use phrases like “but,” “however,” and “although” as well as words that indicate an inability to write concisely. This information can be used to identify suspicious academic papers written by AI.
Does Commerzbank trust AI for reports
When Tomak was first hired at Commerzbank to establish the Big Data and Advanced Analytics function, he made sure that the bank’s management board was fully committed to the project. He learned from his time in Silicon Valley that top-down buy-in is essential for success, and he set clear OKRs (Objectives and Key Results) to help guide the team in the right direction.
The bank’s dive into artificial intelligence-powered analyst reports comes as major lenders strive to set themselves apart from their competitors in the wake of MiFID II, the European investor protections rules that went into effect this year. Among other things, it forces financial firms to separate research costs from trading commissions and to disclose these charges to investors.
Michael Spitz, head of the Frankfurt-based bank’s R&D unit Main incubator, told the Financial Times that AI is already well enough advanced to carry out about 75% of what a human equity analyst would do when writing a report on quarterly earnings. However, he says that more abstract analyses will need human input for the foreseeable future. He is also confident that the technology will be able to take on more data-intensive tasks, such as analyzing the financial impact of a merger or acquisition.