Arria NLG, a leading provider of natural language generation (NLG) technologies, has appointed Managing Director and Innovation Strategist, Mark Goodey, to cement Arria Investment Analyst as the Banking, Financial Services, and Insurance (BFSI) industry leader. Arria Investment Analyst uses natural language technologies to bring 100 percent accuracy to investment analysis and to create data-driven investment commentary. "I am excited to lead this initiative," said Goodey. "Arria's Investment Analyst uses natural language technology to analyze investment portfolio performance. It's a technology uniquely placed to support asset managers, asset owners, and the financial services industry, so what used to take hours or days can now be accomplished in seconds."

Across industries that have been gold mines for AI investments are automated threat intelligence, automated customer services agent and fraud detection. As per Jessica Goepfert, program director, Customer Insights and Analysis at IDC "Near-term opportunities for cognitive systems are in industries such as banking, securities and investments, and manufacturing….In these segments, we find a wealth of unstructured data, a desire to harness insights from this information, and an openness to innovative technologies". Fintech has witnessed a staggering growth in investments world over, with the growth of over 10% to a whopping $23.2 billion- US and China leading the market. This boost is powered by growing capabilities of AI and machine learning. As AI has already achieved much in retail, healthcare, trading etc. – it is safe to say that AI will achieve great things in Finance.

That's a tough one – for me it's a moment when the end user goes'wow!' and there have been a number of projects where this has happened. The one that first comes to mind is an application we built for one of our clients in the insurance industry, where the Arria NLG system provides summaries of insurance policy sales from millions of sales records as well as root cause analysis. This would have taken an experienced analyst half a day to produce. Another that comes to mind, is an application that we built for an online advertising company to be used by campaign managers. Our system provided not only analysis of weekly performance but also recommendations on how to improve campaign performance.

Artificial intelligence guru Robert Dale explains the benefits and shortcomings of natural language generation technology and advocates for disclosure of use of the software. Natural language generation, a field in artificial intelligence which automatically turns facts and statistics into coherent English and other languages, offers important advantages for finance and accounting, according to Robert Dale, a longtime expert in the technology. He is also co-author, with Arria's chief scientist Ehud Reiter, of the textbook, Building Natural Language Generation Systems, first published in 2000 and then again in 2006. We can build pretty sophisticated systems that can produce pretty sophisticated narratives, but we still cannot do that with quite the nuance of a human author.

It has been well documented that technology has played a major role in the Olympics this year in Rio. Athletes are using technology to train smarter, wearing specialized equipment to compete stronger and are recovering faster and more effectively all due to advances in technology and new innovations. Barbara Kendall has seen this transformation in a way in which few can relate. She competed in the 1992, 1996 and 2000 Olympics in Barcelona, Atlanta and Sydney and won gold, silver and bronze medals through her 25-year Sailboarding career. When her athletic career ended, she got into the technology world and is now a member of board of directors for an artificial intelligence (AI) company Arria NLG.

Arria NLG PLC (LON:NLG), the language generation technology specialist, has confirmed it plans to raise further cash, probably via a listing on the New Zealand and Australian Stock Exchanges. In the half-yearly results statement it said it would also raise capital in the short-term "as needed". Last week it brought in 262,000 via the issue of loan notes and warrants. "The directors are confident of securing sufficient, additional funding within the next financial year, for its near term requirements," Arria said in the notes to its accounts. The results, meanwhile, showed the company had around 2.1mln in cash as at the end of March.

The driving motivations behind the installation of AI in business processes appear to be the greater speed, accuracy and volume capability of computers when compared to their existing human counterparts. Many businesses are already using robotic process automation systems to crunch numbers and sift data on a daily basis. For example, Kensho is an intelligent computer system widely used by stock traders and investors to automatically analyse portfolio performance and predict market changes. The software is described as'the world's first computational knowledge engine for the financial industry'. It claims to address Wall Street's greatest challenge – automating and improving on previously human-intensive knowledge work to keep up with the split-second changeability of stock. Kensho's founder, Daniel Nadler, told the New York Times Magazine: ''People always tell me, 'I used to spend two out of five days a week doing this sort of thing,' or'I used to have a guy whose job it was to do nothing other than this one thing'.''

Artificial intelligence (AI) has been implemented in multiple industries, from stock trading to hospitals, and Google has singled it out as the next big thing. As Uschi Schreiber, Chair of the Global Accounts Committee at EY, wrote earlier this year: "Leaders in every industry are responding to shifts that would have seemed unimaginable even a few years ago. "Artificial intelligence (AI) and robotics are fundamentally reinventing the workforce." The finance sector, given its heavy reliance on mass amounts of numbers and data, is a prime candidate for the automation offered by intelligent learning systems. But while this might mean great things for efficiency and digital transformation, many have raised concerns about robots taking the place of human employees. The driving motivations behind the installation of AI in business processes appear to be the greater speed, accuracy and volume capability of computers when compared to their existing human counterparts. Many businesses are already using robotic process automation systems to crunch numbers and sift data on a daily basis. For example, Kensho is an intelligent computer system widely used by stock traders and investors to automatically analyse portfolio performance and predict market changes. The software is described as'the world's first computational knowledge engine for the financial industry'. It claims to address Wall Street's greatest challenge – automating and improving on previously human-intensive knowledge work to keep up with the split-second changeability of stock. Kensho's founder, Daniel Nadler, told the New York Times Magazine: ''People always tell me, 'I used to spend two out of five days a week doing this sort of thing,' or'I used to have a guy whose job it was to do nothing other than this one thing'.'' Even the breaking down and translating of numerical data into colloquial terms no longer requires the input of a human operator, thanks to systems that learn with use to mimic personable patterns. UK-based Arria has developed natural language generation software (NLG) that is being used across a wide range of industries to humanise and simplify the analysis of data heavy reports. Arria's Chief Technology Officer Robert Dale, said: "By emulating human behaviour in software, you get technology that can carry out tasks that are more than just straightforward number crunching, with the machine exhibiting real intelligence.

In what ways could NLG be used in healthcare? What will NLG mean for patients? NLG can be used to empower patients, so that they understand their medical conditions and can make better choices about their healthcare. NLG can also help patients do a better job of looking after themselves: this includes lifestyle changes, self-management of chronic conditions, and complying with treatment regimes. For example, many diabetics have sensors which measure blood sugar levels, but they struggle to use this information to manage their diabetes because often they don't understand it, and can overreact and indeed panic when they see their blood sugar change.

From the story of Talos of Crete to Mary Shelley's Frankenstein, the concept of artificially-simulated intelligence has long fascinated humankind. This urge to replicate intelligence through synthetic measures is what is even today driving us on to greater innovations. Our online searches are now taking into account the previous'experiences' to curate more tailored results, our cars are becoming self-driven as a result of AI-based tech and robotic domestic helpers have crossed the menial tasks of cleaning homes off the list of their human masters. In short, each and every aspect of our lives is being increasingly taken over by AI, and these examples are barely scraping the tip of the iceberg. To gain a more detailed insight into how ingrained artificial intelligence, heuristic algorithm and machine learning is becoming to everyday functioning, one only needs to take a look at the global startup ecosystem. While traditional technology majors such as IBM, Google, Microsoft and Amazon do figure in prominently when it comes to AI, there are several start-ups and tech-based ventures which are focusing on the technology as a key differentiator for their services and using it to revolutionise the way that businesses are conducted.