AI Articles and Analysis in Finance

Though in its nascency, the Indian banking sector is beginning to adopt artificial intelligence (AI). While large commercial and investment banks globally are incorporating AI and blockchain for both back-office and customer-facing purposes, in India, widespread adoption of these technologies has not yet come to fruition. 

Lending is a massive business in the United States which directly and indirectly touches almost all parts of the economy. With tens of millions of Americans holding loans worth trillions of dollars, any technology that can make even a small improvement in a company’s returns on the loans they hold, or that can improve their share of the market, would be worth a significant amount of money.

The insurance industry is a competitive sector representing an estimated $507 billion or 2.7 percent of the US Gross Domestic Product. As customers become increasingly selective about tailoring their insurance purchases to their unique needs, leading insurers are exploring how machine learning (ML) can improve business operations and customer satisfaction.

Artificial intelligence is likely to affect the entire landscape of insurance as we know it. Change is here, more is coming. Today, the insurance market is dominated by massive national brands and legacy product lines that haven’t substantially evolved in decades. This kind of stagnation has historically suggested that it is an industry ripe to be disrupted.

Real estate is a cost for nearly every business, whether leasing, owning or managing.

Process automation from AI offers a tremendous opportunity to lower costs associated with commercial real estate, especially those associated property management.

While tech giants tend to hog the limelight on the cutting-edge of technology, AI in banking and other facets of the financial sector is showing signs of interest and adoption even among the banking incumbents.

Episode summary: Although machine learning in finance is far from new, it is merely at the cusp of a much wider set of applications (in all segments of finance, from insurance to bookkeeping and beyond). Already machine learning has overhauled so many aspects of the financial landscape, from accounting to trading, and it is destined to have more and more impact as it develops further. Guest Alexander Fleiss and his team at Rebellion Research are developing and using AI which uses quantitative analysis to pick investments. Fleiss discusses the current status of machine learning in the world of finance as well as lesser-known niche applications that don’t make headlines - but do make a big impact on how businesses are run. He then goes on to explore the effects of future innovative applications of AI in the financial domain.

More data, less problems?
How AI is transforming the financial marketplace and operations from the inside out.
AI got a head-start in the information-rich financial industry over two decades ago, though the applications of today—robo-advisors and algorithmic traders, for example—are far more autonomous and omnipresent, accelerated in large by the increasing availability of data and advanced analytics technologies. The "prestige" associated with the use of AI and ML technologies in finance is reflected in initiatives like The AI Financial Summit, an invite-only conference that gathers C-level execs from across the financial industry sector and puts them in a room with AI experts and service providers. But a company doesn't necessarily need to be invited to a closed conference in order to apply or learn from emerging technologies in the industry.