#regtechcompanies

Some policies that have been put in place to counter financial crimes have unfortunately had a chilling effect on banks’ willingness to do business in markets perceived to be risky – in part due to the high price of compliance,” says Vijaya Ramachandran, senior fellow at the Centre for Global Development and one of the study’s authors.

But, pointing to the new study, he says “regtech may be the solution to some de-risking woes”.

“What we’re seeing is that even as these policies are having an impact, financial institutions are coming up with solutions in the form of new cutting-edge technologies to help them comply better and faster with AML regulations,” Ramachandran says.

KYC utilities, for example, can reduce the amount of time correspondent banks spend on repetitive due diligence processes. Blockchain can improve the KYC data storage security.

Big data and machine learning can enhance correspondent banks’ ability to assess and manage risk through more sophisticated customer typologies and more accurate transaction monitoring. And biometrics can enable faster and more assured identification of individuals.

Over time, the study concludes, these technologies may alleviate some of the pressures on banks and “make holding correspondent banking accounts with clients in poor countries more likely”.

This enthusiasm about regtech is not new: GTR has previously reported on ways regtech can help the industry optimise compliance – a task that is still largely dominated by manual and mundane processes. A recent study found that banks could save £2.7bn a year by adopting machine learning and big data technology in their AML systems.

However, the argument that new regtech like machine learning and blockchain will bring banks back to de-risked markets is met with scepticism elsewhere in the industry.

“I don’t think technology is going to solve the problem. It’s a people’s, education and timing issue,” says Sean Norris, head of sales at Accuity.

He points to the fact that many of the de-risked countries, mentioning the likes of Afghanistan, Malaysia, Indonesia and Vietnam as examples, “haven’t got processes right for very basic things yet” and are still “far behind” when it comes to prioritising and implementing the Financial Action Task Force (FATF)’s guidelines and best practices for AML.

Norris doesn’t deny the power of technology – after all, Accuity itself is a provider of AML software and is also exploring the use of machine learning to minimise the number of false positives. He also argues that de-risking is in fact driving the acquisition of better technologies by banks in Africa and Asia to upgrade their AML processes.

“When you’ve got a bank in Jakarta that is still relying of self-declaration of a person in a KYC process, how is that going to be acceptable for a western bank? I don’t think technology is going to solve a behavioural problem and different attitudes to AML controls,” he says.

Silicon Valley analytic software firm FICO announced that GVNG, a technology platform for nonprofits, will use the FICO TONBELLER® Siron® suite of anti-money laundering (AML) and know your customer (KYC) solutions. Based in Los Angeles, GVNG will use the FICO "regtech" solutions to carry out risk-based checks on people setting up charities, making donations, receiving payments and volunteering services, and to provide immediate alerts when any suspicious transactions take place.

"When it comes to preventing money laundering and knowing our customers, we wanted to go beyond the letter of the law to truly ensure that we weed out organizations or individuals that could have criminal intent," said Dominic Kalms, president and CEO of GVNG. "For example, we wanted to put safeguards in place to prevent sexual predators from registering as volunteers, and make sure money launderers or terrorist financers are not using our clients' services or receiving funds. With our ambitious goal to sign up 2,000 programs in the next year, we needed a scalable solution we could use in the cloud, without increasing our team's workload. FICO offered the most powerful cloud-based solution, they have a stellar reputation in the marketplace and they could meet our requirement to have it running in just a few months."

RegTech is not new. Whilst the term may be newly minted, many of its business problems and responses have clear lineage back 30 or 40 years. What has changed are: the technologies available and their combinative power, particularly cognitive computing.increased operational complexity calling for smarter solutions.the maturing Fintech investment ecosystem.the concentration of specialist regulatory experience in the world's financial hubs. Regtech solves problems. Issues and requirements thrown up by regulation call for new solutions. More bodies are not the answer. These new solutions are often very specific to a problem so taking many new services, rather than a single monolithic system, is the direction of market travel. Regtech is intelligent. Machines learn patterns to detect anomalous behaviour. Standards are set to enable data definitions to be translated into machine code for different uses, enabling automated and accurate data extraction from source systems for analysis and aggregation. Outside-In is best. It has simply become far more efficient, more flexible and quicker to buy in Regtech solutions than to build them in-house. That in part explains the steady switching of specialists out of Governance Risk and Compliance positions into Regtech start-ups. RegTech transforms data provision and reporting. The explosion in reporting requirements since the Financial Crisis has stimulated effort to improve data provision and reporting processes between industry, regulators and central banks. Regtech solutions tag and track aggregated and reported data back to the level of original data on a granular level. The EU's Anacredit project, for example, identifies, aggregates and compares credit exposures and detects associated risks on a loan-by-loan basis. Regtech is global as well as local.The same thorny issues are faced continuously by businesses and Governments alike, in Developed and Developing Economies: How do we verify the identity of our counterparties? How do we know we can trust them? How do we onboard them, manage them, tax them? How do we identify fraudulent behaviour and how do we act with the customer to stop it? How do we report our numbers to the regulator accurately, on time and at the required level of detail most efficiently? Even if Regtech has to act globally, it has to engage with local regulators and regulations, jurisdiction by jurisdiction; so there are no short cuts.