The rapidly evolving field of Robotic Process Automation (RPA) has made significant strides in automating repetitive processes, yet its effectiveness diminishes in scenarios requiring spontaneous or unpredictable tasks demanded by users. This paper introduces a novel approach, FlowMind, leveraging the capabilities of Large Language Models (LLMs) such as Generative Pretrained Transformer (GPT), to address this limitation and create an automatic workflow generation system. In FlowMind, we propose a generic prompt recipe for a lecture that helps ground LLM reasoning with reliable Application Programming Interfaces (APIs). With this, FlowMind not only mitigates the common issue of hallucinations in LLMs, but also eliminates direct interaction between LLMs and proprietary data or code, thus ensuring the integrity and confidentiality of information - a cornerstone in financial services. FlowMind further simplifies user interaction by presenting high-level descriptions of auto-generated workflows, enabling users to inspect and provide feedback effectively. We also introduce NCEN-QA, a new dataset in finance for benchmarking question-answering tasks from N-CEN reports on funds. We used NCEN-QA to evaluate the performance of workflows generated by FlowMind against baseline and ablation variants of FlowMind. We demonstrate the success of FlowMind, the importance of each component in the proposed lecture recipe, and the effectiveness of user interaction and feedback in FlowMind.

Tata Consultancy Services' Capital Markets Focussed Workflow, Innovative Process Enhancers, and Solutions Backed by the Latest Technologies, Cited as Key Strengths Tata Consultancy Services (TCS), a leading global IT services, consulting and business solutions organization, has been recognized as a Leader in the Everest Group PEAK Matrix for Capital Markets Operations. In an assessment of 24 global service providers offering capital markets operations services, TCS was placed highest for Vision and Capability, as well as Market Impact. Additionally, it was named a Star Performer for having top quartile year-on-year improvement in its scores. TCS' strong position in the overall capital markets segment is attributed to consistent growth in its portfolio with multiple new wins. According to the report, the company has continuously worked on creating solutions backed with the latest technology to help its customers solve operational problems more efficiently.

President and CEO Rehan Jalil looked at how organizations conducted their privacy compliance practices and saw areas that could use improvement. He saw solutions that only handled part of an entity's compliance efforts and a lot of work privacy professionals had to conduct manually. It is why Jalil and his company launched Privaci.ai, a platform designed to automate compliance tasks through the use of artificial intelligence and bots. Privaci was created to tackle data subject access requests, collect consent, assess third-party vendors and assist organizations as they conduct privacy impact assessments. To help bolster these efforts, Privaci recently announced it has obtained $31 million in Series A funding, which Jalil said will be used to continue to service its customers, as well as provide support to its team of 130 employees.

If you define AI as something that can emulate human decision-making, there's a chance you'll be disappointed when you find out how limited AI solutions for cyber security really are. Speaking to Information Age ahead of his keynote speech at Custodian's Talking Tech, April 25 2019, Etienne Greeff, CTO and founder of SecureData, admitted that he often rolls his eyes when he hears about AI solutions for cyber security. He argued: "In cyber security and in application security, there's actually no known application of AI. There's no autonomous agent that automatically defines threats; that does not happen yet, and it's not very close to happening." It appears some enterprises are challenging the hype too.

Artificial intelligence is rapidly becoming the core foundation of the Cloud-Platform-as-a-Service model being offered by'mega vendors' to their customers. This trend is emerging in the cloud space, and as a result, it is going to become increasingly easy for organisations to adopt forms of artificial intelligence. Businesses are going to need to start leveraging AI to cope with the ever-expanding volume of data generated by trends, such as the Internet of Things. And organisations need to have a note of caution around how they adopt AI. "If you put garbage [data] in, you'll get garbage [data] out," explains Greg Hanson, CTO & VP at Informatica. "What we actually need is not just artificial intelligence in the analytics layer -- in terms of generating graphical views of data and making decisions in real time around data -- we need to make sure that we've got artificial intelligence in the backend to ensure we've got well-curated data going into our analytics engines."

At Gigaom.com/quiz, there is a ten question test that scores how likely any given job is to be replaced by automation, be it by a computer or a robot. I'm going to spend ten AI Minutes going through the questions one at a time, and why they're on the test. Question #4: How long is the training for the job? You might score this as 0, which is less likely to be automated, if the training is months or years; that might be a dental hygienist, or an auto mechanic, or a locksmith. On the other hand, you might score this a ten, which is more likely to be automated, for something like a job that requires just a very minimal amount of training, like a custodian.

Recently Lofty Labs was engaged by a law firm. Now, that's not the type of business we generally target as clients for a data analysis consultancy. It turned out they had a data problem, though. When two large companies sue each other, a lot of historical communication records get exchanged between the two sides through the facilitation of the court in a process known within the field as "discovery". This is the process you probably think of from the movies, where lawyers can be seen carting dollies full archival boxes overflowing with paper documents.

Institutional clients are swimming in massive amounts of data that mere mortals can't handle effectively. That is why custody banks are increasingly turning to artificial intelligence and robotics to help their clients wade through it. Such clients want their custody banks to offer better data aggregation and analytics and more automation, according to a recent report by BNP Paribas and the research firm Tabb Group. The authors surveyed a group of sell-side senior executives at midsize banks and brokerages in the United States regarding their technology priorities and their expectations of custodians. "Clients can analyze data and react much more quickly with robotics than the current systems they are running," said Bruno Campenon, a BNP Paribas Securities Services executive who oversees the financial intermediary and corporate client lines.