An artificial intelligence-driven compliance technology company founded by a former fund manager and corporate broker has raised £2.5 million in a recent funding round. FeedStock's latest funding round was led by Praetura Ventures, with Force Over Mass and existing investor Illuminate Financial Management also participating in the round. The company provides AI and natural language processing technologies to help both the buy- and sell-side institutions meet various compliance requirements, as well as commercial goals. Founded in 2015, FeedStock was established by former analyst and fund manager at GAM, Lucas Wurfbain, alongside Charlie Henderson, who previously worked as a research analyst and corporate broker. "With our background in highly regulated businesses, we are seeing enormous appetite for our proprietary technology; not only from businesses required to comply with MiFID II, but also for enterprises that are looking to leverage AI as a core component of their business for efficiency gains and revenue generation," Henderson commented on the recent investment.

Effectively managing and storing trade data will ensure that technology used to comply with current regulations remains usable for future requirements, says the chief product and engineering officer, Calypso. "[Having] data in a consistent format, where applications dealing with different product types, different parts of the trade life cycle and workflow are all contributing to that data source, and reading from that same data source, makes the job of reporting on that data so much easier," says Calypso's Richard Bentley. "Without that, for every single regulation that comes along, you are going to have to go to every application involved in the workflow that is impacted, modify those applications to extract the right data from each, pull it all together in a consistent format, try to transform and enrich it - and do that continually." In the 2019 bobsguide Rankings – announced in late November – Calypso ranked top for both regulatory compliance and integration with other systems. The firm came second in the degree of straight-through processing category.

Effectively managing and storing trade data will ensure that technology used to comply with current regulations remains usable for future requirements, says the chief product and engineering officer, Calypso. "[Having] data in a consistent format, where applications dealing with different product types, different parts of the trade life cycle and workflow are all contributing to that data source, and reading from that same data source, makes the job of reporting on that data so much easier," says Calypso's Richard Bentley. "Without that, for every single regulation that comes along, you are going to have to go to every application involved in the workflow that is impacted, modify those applications to extract the right data from each, pull it all together in a consistent format, try to transform and enrich it - and do that continually." In the 2019 bobsguide Rankings – announced in late November – Calypso ranked top for both regulatory compliance and integration with other systems. The firm came second in the degree of straight-through processing category.

MiFID II, alternatively known as Markets in Financial Instruments Directive, is regulation set in place to strengthen investor protection. At Decision Point AI we are focused on enabling transparency around the relationships of assets, asset owners and intermediaries for clients and corporate customers. The Markets in Financial Instruments Directive is the EU legislation that regulates firms who provide services to clients linked to "financial instruments" (shares, bonds, units in collective investment schemes and derivatives), and the venues where those instruments are traded. MiFID II is clearly a conflicting priority in a business context that uniformly hides "the what", from "the who" as part of their competitive advantage. This then creates awful complexity around "at what point" and "about what" financial institutions are transparent.

Investment banking is seeing its historical profit centers eroded by technology and regulations. Core processes are being automated or commoditized. From IPOs, to M&A, to research and trading, investment banks are getting smaller, leaner, and scrambling to keep up with innovations. In 2006, investment banks were at the top of the finance world. With torrential growth and return on investment (ROI) driven largely by the trading of complex financial instruments, Lehman Brothers, Bear Stearns, Goldman Sachs and others achieved record profits and awarded unprecedented bonuses. Over the next two years, everything fell apart. Download the free report to learn how core processes of this financial service are being automated or commoditized. After the collapse of Lehman and Bear Stearns and the global financial crisis that ensued, the business models of the world's biggest investment banks needed to change. In the US, legislation emerged to forbid investment banks from prop trading, or trading with their own capital, and forcing them to keep more capital on hand. This regulation reduced trading profits and created a need to cut costs, spurring investment banks to spin off unprofitable divisions or eliminate them entirely. While the rules against prop trading have more recently been loosened, the restriction has still changed how investment banks operate. Moreover, as more and more companies raise large equity rounds they're also choosing to delay public offerings. And even when major tech companies do decide to go public, some, like Spotify and Slack, are doing so mostly without the help of banks. As a result, banks are facing dropping IPO profits: they generated just $7.3B in revenue in 2017 from equity capital markets, which includes IPOs, down an inflation-adjusted 43% since 2000's peak, according to the Wall Street Journal. At the same time, financial upstarts have built technologies that could eventually cut into the relationship-driven work that investment banks are used to doing. Instead of working with a bank to make an acquisition, you can use Axial -- the so-called "Tinder of M&A," for its algorithm-based approach to matching companies with potential buyers. In 2015, 26% of $1B mergers and acquisitions took place without the help of external financial advisors, up 13% from the year before, according to Dealogic.

With banks under massive pressure to slash costs associated with the production of research on stocks and bonds in Europe, it's artificial intelligence (AI) to the rescue, with Germany's $525-billion Commerzbank leading the way with a new content-automation partnership. For Germany's second-largest bank, it's a major expenditure on research, with a partner, Retresco, that hopes to help it churn out AI-generated research reports and replace the human element in analyst notes. The AI product hasn't been fine-tuned yet, but investors will be interested to learn that it's already advanced enough to provide around 75 percent of what a human equity analyst would give an investor when writing an immediate report on quarterly earnings. Presumably, AI is more objective, too--and that's where the idea of investor protection comes into play. But equity reports reviewing quarterly earnings, says Michael Spitz, Commerzbank's head of research, have common reporting standards, so the parameters are easy to plug in to AI, the Financial Times reported.

When I concluded my final project report for the Warwick Business School Executive MBA last year, one of the summary points was that financial services regulators would soon need to start looking at'technology as law' and would need to write laws and policies to govern this change. Regulations would become endogenous rather than reactive as they are today. While this may look like something for the future, both regulators and member banks could find efficiencies in the near term by leveraging the advancements in technologies of both artificial intelligence and blockchain. In this blog, we will explore how much money is spent by large financial institutions in keeping up with the ever changing regulatory landscape, how smaller enterprises are carrying risks of penalties due to their inability to catch-up with the regulations and how regulators continue to have the dilemma on what's the right level of regulations. Using examples of GDPR and MIFID II, we will see what are the current challenges faced by these enterprises and how we can apply a combination of AI and blockchain to seek efficiencies and start moving towards'pro-active' regulation and maybe one day to endogenous regulations!

Mizuho Financial Group Inc. will start artificial-intelligence trading to bolster its Japanese equity business, according to people with knowledge of the plan. Japan's third-biggest lender will begin offering an algorithm-based AI trading service to some large institutional clients in Japan and elsewhere in Asia, the people said, asking not to be identified because the plan is private. The product attempts to predict how stock prices in Japan will change over an hour and find the best time to trade, they said. Global banks are seeking to improve the quality of their trading execution and equity research before the European Union's revision of the Markets in Financial Instruments Directive, or MiFID II, comes into force in January. Under the new rules, brokerages will be required to separate research fees from trading commissions to ensure investors pay fair prices for the services, a move that may spur competition.