It’s becoming clear these days that a sizeable chunk of the most disruptive innovations being applied within the financial sphere is coming from RegTech.
As we mentioned in our previous article, demand for RegTech solutions is expected to skyrocket, as firms intensify their search for ways to effectively deal with the increasingly labyrinthine demands from regulators across such areas as compliance, regulatory reporting, and risk management.
In turn, RegTech companies are now offering a diverse range of solutions, each one being geared towards specific regulatory challenges they seek to address and/or resolve.
But just what exactly are those solutions? We take a look at some of the most popular new forms of technology being developed by RegTech companies:
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Cloud Computing
Given that regulatory requirements are being frequently revised, amended and updated, firms are now having to be more flexible and adaptable in the way they respond to such changes. This is where cloud computing is proving particularly useful.
Cloud-based services are allowing standardized shared utilities to be established, ones that can perform various risk and compliance processes including know-your-customer (KYC), stress testing, and reporting. Such utilities, usually managed by third parties, can then be accessed by financial institutions across the industry.
What’s more, cloud-based solutions allow for applications to be updated quickly and without costly release processes, whilst also being able to host large databases for efficiently modelling new regulatory demands.
As such, financial institutions do not need to spend excessively on developing their own individual systems and infrastructure. Rather, the cloud allows firms to pool many compliance functions onto a single platform, thus ultimately helping to boost efficiency, reduce costs, and improve scalability.
FundApps is an example of a RegTech firm offering cloud-based solutions, particularly in the area of compliance monitoring, and includes shareholding disclosure reporting, investment restriction monitoring for funds, and specific reporting and compliance rules.
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Blockchain
The technology underpinning cryptocurrencies, such as Bitcoin, has an increasingly wide range of potential use cases. And RegTech is among the most hotly anticipated. In particular, blockchain’s immutability makes it ideal for recording and sharing information, both between an FI and regulators, and between two or more FIs.
Being a cryptographically secure ledger that records a permanent, immutable log of transactions, moreover, makes blockchain the ideal solution for monitoring financial transactions. And thus, by being able to identify suspicious and/or potentially fraudulent transactions, blockchain will go a long way towards combating the global scourge of money laundering.
Blockchain banking consortium R3 and the UK’s financial watchdog, the Financial Conduct Authority, have recently teamed up along with two major global banks to develop a blockchain-based application specifically designed to improve regulatory reporting of mortgage transactions. Given that the technology enables efficient, secure record-keeping, the FCA should be able to supervise mortgage transaction activity in a much quicker and more efficient manner than is currently the case, whilst also enabling data inconsistencies to be minimized.
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Machine Learning
This increasingly sought-after tech refers to the ability of computer systems to identify complex patterns and relationships within large, unstructured data sets. As more data is fed into the system, algorithms are modified in order to improve the system’s analytical and predictive powers.
With that definition in mind, therefore, machine learning is now being increasingly adopted in risk management, whereby large data sets are subjected to self-learning risk models in order to ascertain the creditworthiness of customers, and determine appropriate market risk parameters for trading counterparties.
Money laundering detection is also benefiting from the application of machine learning. Indeed, RegTech often sees machine learning being leveraged with another popular form of technology…
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Big Data, Data Mining & Analytics
The recent regulatory onslaught for financial firms has meant that they now have to analyze substantially more data in order to sufficiently meet various thresholds. But so far, they have lacked the capacity and infrastructure to do so.
Again, taking the example of money-laundering/KYC, suspicious transactions reports have traditionally only been examined aftera fraudulent transaction has already been committed, meaning that firms are failing to prevent the criminal use of the financial system.
But Big Data and analytics are now being widely adopted to combat complex financial crime by enabling firms to identify suspicious activity, holistically and in real-time. With sufficient data mining infrastructure in place, large datasets related to client activity can be analyzed to spot unusual patterns regarding cash flows, which then allows appropriate action to be taken in a timely manner.
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Biometrics
This mode of technology is concerned with our individual physical and behavioural characteristics as humans. It enables each of our identities to be verified and authenticated on the basis of the individual data that is unique to each of us.
Specific examples include facial recognition, fingerprint and iris scanning, and document ID recognition (such as passports). And companies such as Jumio now offer liveness detection to ensure the user is providing an image of a live person, rather than an old picture.
This has some seriously beneficial implications for improving the security and automation potential pertaining to client identity management. Indeed, the improving resolution and sensor capabilities of our mobile devices means that biometrics is becoming a particularly convenient way to verify identity. And as a result, it can be especially useful in simplifying the KYC process.
