Regulatory technology or RegTech, along with wealthtech and proptech (property technology), is on the rise. Regulators are using it more and more and venture capitalists are investing in it, even though its take-up among firms seems to have plateaued temporarily.

According to a report from Business Insider Intelligence, Regtech start-ups are shouldering much of the compliance burden at traditional financial institutions, but they are struggling to scale up in volume. This, the publisher claims, is leading to "unexpected inertia in the RegTech industry."

A report by Thomson Reuters seems to bear this surprising assertion out. In its RegTech section it says that only 8% of firms implemented a piece of RegTech software in 2018, compared with 30% the previous year.

The Business Insider Intelligence report, meanwhile, expects financial firms to take up RegTech software more avidly in the next 18 months because: (i) start-ups' business models are improving; (ii) start-ups are forming more and more partnerships among themselves and collaborating in a more organised fashion; (iii) regulators are promoting RegTech more and more; (iv) financial institutions are feeling more favourable towards them; and (v) consultancies are helping to persuade firms to adopt them.

Regulators using RegTech

A regulatory reporting platform for Austrian banks has now emerged. The Austrian central bank – Oesterreichische Nationalbank (OeNB) - has been collaborating with the country's banks to develop a new reporting model. It has based its initiative is based on "a greater harmonization and integration of data, as well as greater integration of the IT systems of the supervisory authority and the supervised entities." It works through a shared 'utility' (a mysterious latinesque word that Nordic regulators are using to describe a one-purpose, centrally important, mutually owned software company) called Austrian Reporting Services GmbH (AuRep), a joint venture of the largest Austrian banking groups. AuRep runs a 'common' (presumably this word means 'shared' rather than 'vulgar') regulatory reporting platform based on Bearingpoint's ABACUS/GMP software which serves as a central interface between the supervised banks and the OeNB.

Another 'interface' concern, the RegTech for Regulators Accelerator (R2A), was set up in 2016 to help financial regulators to understand marketplaces and customers' needs in data-rich environments. It pioneers software on their behalf and works with software innovators to build bespoke systems.

The Philippine banking regulator, the Bangko Sentral ng Pilipinas (BSP) was the first financial authority to collaborate with R2A. BSP asked it to develop an Application Programming Interface (API) and a back-office reporting and visualisation app to:

• allow financial institutions to submit data digitally and automatically to it;
• increase the volume, granularity, and frequency – and improve the quality – of the data that they submit; and
• enable BSP staff to improve data validation and analysis, and generate customised reports for their own use.

Nobody yet knows whether this is nearing completion. Meanwhile, the central bank has also asked R2A to develop a chatbot prototype and processing utility solution (i.e. a dashboard with administrative and reporting capabilities, integration with existing complaints process, etc.) for customers' complaints. The chatbot solution will allow consumers of financial services to send in their complaints through their mobile handsets (either on an app or on SMS). It will also allow the regulator to answer queries, manage the structure and flow of automated conversations based on expertise and historical data and use the data it obtains. The regulator is expecting to save a good deal of man-hours through this manoeuvre.

Firms using RegTech

Binance, one of the world's most recognisable cryptocurrency exchanges, is using Coinfirm, a RegTech company, to help it comply with new guidelines pertaining to the Financial Action Task Force's anti-money-laundering rules. As Binance operates in 180 countries, Coinfirm stands to benefit to a massive degree.

Meanwhile, AQMetrics, the provider of cloud-based software to asset managers and asset service providers, says that it has signed a number of new contracts, hinting that most of them are to do with regulatory reporting. An unnamed accountancy firm of middling size is using it to support its FCA-regulated customers; the rest of its equally unnamed new users appear not to be in wealth management.

Standard Chartered PLC has deployed BearingPoint’s tax reporting solution FiTAX to fulfill CRS, FATCA and QI reporting obligations in 63 countries all over the world.

SteelEye, the compliance technology and data analysis firm, has been hired to help the customer base of CME Group's Trade Repository in Europe to report data to regulators in accordance with EMIR, the European Market Infrastructure Regulation. EMIR calls for all derivatives to be reported to trade repositories (TRs), which collect and keep the records of all derivative contracts.

The SteelEye RegTech service fully automates the reporting process and manages breaks and validations. Since SteelEye is cloud-based, it claims that costs are at a minimum. Matt Smith, the CEO of SteelEye and a frequent contributor to our web-pages, is arguing that (his own products notwithstanding) EMIR reporting has become astronimically expensive and difficult for firms to manage over the last five years.

ClauseMatch has announced that it now operational at Intesa Sanpaolo. This piece of work apparently sprang from a meeting at FinTech Innovation Lab hosted by the bank. A proof-of-concept exercise soon followed.

Venture capitalists investing in RegTech

Marlin Equity Partners has made a 'growth investment' in SmartSearch, a British RegTech company which specialises in anti-money-laundering and ‘know your customer’ compliance through a software-as-a-service platform. Marlin is a private equity investor, with more than $6.7 billion under management, which operates on a global scale.

With the slogan "Up, up and away!" Apiax, a RegTech start-up from Zürich, has completed a US$6.6 million round of Series A funding that was co-led by e.ventures and XAnge and joined by previous investors such as Peter Kurer, DIVentures, Swiss ICT Investor Club (SICTIC), Zürcher Kantonalbank and Tugboat. Apiax was founded to transpose written regulations into binary, machine-readable compliance rules, allowing new digital solutions and products to be “compliant by design”. Major - yet unnamed - financial institutions are now using it.

Nicolas Blanchard of Apiax has proudly proclaimed: "With e.ventures and XAnge, we have found the perfect partners to boost our global expansion plans. One of our next steps is to take our RegTech start-up to Singapore!"

Here and there

CUBE, a RegTech firm whose headquarters are in London, has announced that its regulatory intelligence and regulatory change-management software has filled the number one ranking in the 2019 Market FinTech RegTech Suppliers Report. ACA Compliance Group in London is now marketing ComplianceAlpha 2.0, a ‘next-generation’ risk and compliance management platform.

Awards

ComplyAdvantage, which uses data science and machine learning to tackle the risk of global financial crimes, has won the coveted prize for Best RegTech Solution at Finovate’s Award ceremony in New York City. NICE Actimize, meanwhile, has been awarded “Best Compliance RegTech Global” by Capital Finance International in the US for the second consecutive year. It claims that its newest and most glamorous product, SURVEIL-X, detects virtually all forms of risky behaviour.

A regulatory report

British financial regulators have long been encouraging financial firms to take up machine learning, the development of models for prediction and pattern recognition from data with limited human intervention, especially as a way of countering fraud and money laundering. The Financial Services Authority and the Prudential Regulation Authority have now published a report on progress.

The different stages of the so-called "machine-learning pipeline" are:

• the acquisition and ingestion of data;
• the selection and engineering of features;
• model engineering and performance metrics;
• model validation (i.e. tests to see if the model works as expected); and
• deployment and safeguards.

The regulators sent a questionnaire out to almost 300 firms, including banks, other lenders, credit brokers, e-money institutions, financial market infrastructure firms, investment managers, insurers and principal trading firms, and received 106 responses. The survey has revealed several things.

Machine learning is being used increasingly in the financial service sector, with two-thirds of respondents already using it in some form. The median firm uses live machine learning software in two business areas and this is expected to double in less than three years. In many cases, firms' machine learning has passed the initial phase of development and is being deployed in a mature way. One-third of machine-learning applications are used for a considerable share of activities in a specific business area. Deployment is most advanced in the banking and insurance sectors.

Firms are now using machine learning in a range of business areas and in both front and back offices. They use it most commonly to detect fraud and in anti-money laundering operations. They also use it in customer-facing applications (e.g. customer services and marketing). Some firms also use it in credit risk management, trade pricing and execution, general insurance pricing and underwriting.

Firms could not think of any new risks that machine learning created but thought that it might, in the fulness of time, amplify existing ones. They thought that machine-learning apps might not work as intended if model validation and governance frameworks failed to keep pace with technological developments.

Firms 'validate' machine-learning apps before and after deployment, most usually by means of outcome-focused monitoring and testing against benchmarks.

Firms use a variety of safeguards to manage the risks associated with machine learning, especially alert systems and so-called "human-in-the-loop mechanisms." These can spot circumstances in which a model does not work as intended (as in the case of 'model drift,' which can occur as an app is continuously updated and asked to make decisions that are outside its original set of parameters).

Firms mostly design and develop machine-learning apps in-house. They sometimes rely on software vendors for the underlying platforms and infrastructure, such as cloud computing.

Most users apply their existing model risk management rules to their machine-learning applications. They know, however, that in future they might have to reconfigure them to take account of the increasing sophistication of machine-learning techniques.

In order to provoke further discussion on the subject, the Bank of England (where the PRA resides) and the FCA are going to set up a public-private talking-shop.

The price of not innovating

On a broader note, wealth managers in the UK have told a survey by Nucoro that only 55% of their brethren will survive the next decade if they fail to innovate digitally. Nucoro has also found that only about one-fifth of wealth managers' "client-facing interaction" is done digitally at the moment. When looking at the areas of their operations where they feel that digitisation can "add the greatest value," 29% cited administration, 24% cited communication with clients and 13% cited the onboarding of clients, but only 4% cited regulatory reporting.