Due diligence, defined as the detailed examination of a company and its financial records, carried out before becoming involved in a business arrangement, is a constant feature of wealth management. Technology firms say they're making it easier, cheaper, and faster.

There’s a big technological trend going on: a shift in how wealth management professionals and private investors perform due diligence. Whether it is testing a potentially promising start-up, or making sure a business hasn’t broken compliance laws, technology can help slash how much legwork is required. 

Family offices, ultra-wealthy individuals and others, as regularly reported and commented upon, are keen to invest directly in business to capture returns. With global interest rates close to vanishing point, the hunt for yield drives much of the hunger for direct investing. But such investment costs time and money, particularly because of the due diligence checks that investors might otherwise have farmed out to fund managers and other intermediaries. 

Firms are stepping into this “due diligence gap”, harnessing artificial intelligence technology to sift through reams of data to ensure that investors are protected as thoroughly as possible from any problems. And this also highlights the different ways in which AI is reshaping the wealth management landscape.

At the start of this year mnAI, an AI-powered intelligence platform, launched in the UK. The firm compresses the time companies and individuals need to identify and understand relevant businesses from months to minutes. mnAI uses more than 250 search vectors, stripping away the need for its subscribers to devote hundreds of hours of manual research, it said.

More recently, the business’s chief executive and founder, John Cushing, explained why such an offering matters to the wealth management community. 

“An industry trend over the last few years is how the largest investment houses have come down the food chain to acquire more interesting and faster-growing businesses,” he told this news service in a call. Another force at work is that family offices and other UHNW investors want to cut out a layer of management fees and go direct, but to do that they need the calls.

The digital tools offered by mnAI have prompted a big flow of inquiries, Cushing said. “We have first-mover advantage,” he said.  

“Lots of firms [investors] are still using Google and a spreadsheet [in performing investment due diligence],” he continued.  

AI can provide valuable data to investors in the early rounds of financing requests – however, it does not eliminate the need for human interaction and some manual checks and awareness, Cushing said. 

The platform uses more than 55 million financial records of UK companies from the last 10-year period. It mixes Bayesian mathematics and Random Forest Modelling to power predictive algorithms that allow users to determine future-based EBITDA and DCF valuations. (According to one definition, a random forest is a data construct applied to machine learning that develops large numbers of random decision trees analysing sets of variables. This type of algorithm helps to enhance the ways in which technologies analyse complex data.) The platform autonomously tracks 37.1 million director, shareholder, officer and PSC [persons with significant control] profiles in real time. These visual charts also track balance sheets, profit and loss, creditors, debtors, debt, shareholders, connections, contacts and introductions.

A reason for going down the AI route, Cushing said, is that traditional ways of tracking down what firms do - Standard Industry Classification – aren’t sufficient or fit for purpose any more. The mnAI offering uses a “natural language keyword search engine”, so that users search for exact keywords or phrases associated with the sector they’re looking into.

The platform can be used in a variety of sectors, such as secondary private equity investments, or start-ups, or older, more mature firms seeking new financing rounds. 

To convey the scalability of the mnAI offering and how many cases can be analysed, a fund that in the past could consider 15 to 20 investment decisions a year can now carry out more than 200, Cushing said. 

In this social media age, when more and more information affecting firms and investments exists online, often in unstructured ways, the need for AI-driven tech to keep track of all this is more and more urgent, he said. Another benefit of such tools is that users can create a visual “map” of promising investments and opportunities – enormously valuable in the long run, he said. 

On the launch of mnAI, Cushing said: “From first-hand experience, I know how painful and time consuming it can be to identify companies for investment and acquisition. With mnAI we have created a technology platform that empowers decision making and provides access to growing and unprecedented volumes of data that enables firms to deliver a richer client experience. We’ve ripped up the rule book, streamlining the entire process for identifying and understanding a target business from months to minutes, helped managers connect with new clients and understand their risk profiles to building investment themes and boosting productivity within wealth managers when performing certain higher value, strategic tasks."  
 

Regulatory compliance
Another side of the due diligence coin is regulatory testing – making sure financial flows and investment opportunities pass a smell test. A firm working in the regulatory AI zone is NICE Actimize, a Hoboken, New Jersey-based provider of financial crime, risk and compliance solutions. An important new area of business is helping firms such as wealth managers keep on top of the Regulation Best Interest regulatory regime designed to protect US investors. This news service spoke to Dave Ackerman, regulatory subject matter expert at the business, about what fund managers should be looking for when it comes to conversations with their broker-dealer partners about Reg BI preparedness. 

Last June, the US Security and Exchange Commission supported the Regulation Best Interest rule, and supported other actions to improve disclosures and clarify advisors’ responsibilities. The rules follow a failed attempt by the Department of Labor to enact a fiduciary rule that would have introduced a “best interest” test of how financial advice is provided. However, senior wealth management industry figures criticised the SEC rule as diverging form the existing fiduciary standard required of registered investment advisors. 

NICE Actimize’s Ackerman is positive about the new rule, however, and thinks it will generate greater demand for the sort of due diligence tests industry practitioners need to make to ensure that they stay compliant.

The new regulatory regime deals with two phases in an investment story: First, before an advisor makes a recommendation to a client, and secondly, when the idea is executed. Showing that necessary tests have been conducted for both phases requires a lot of work – which is where digital tools come in.

Regulation BI also imposes a duty on how people go about the transaction processes involved, he said. The long-term payoff of this new regime is hopefully to improve the quality of the client/advisor relationship. 

“The SEC is pushing Regulation BI as the biggest change to investor protection in 20 years,” he said. 

Already, firms employing Big Data analytics and tools to find patterns and flag up problems are reshaping how advisors carry out due diligence when they onboard a client, and after a client has been taken on. Firms offering wealth managers solutions in this space include smartKYC, for example. 

“The first-time technology is catching up with how regulation is changing us,” Ackerman added.