The state of the financial regulations market is constantly changing, thus companies are under constant pressure to keep up with the latest standards. As this regulatory burden grows both in weight and complexity, the cost of meeting new stringent regulations rises exponentially. As a result, a new wave of technology has emerged to help fintech companies and traditional financial businesses fulfill regulatory obligations.

RegTech utilizes technologies to enhance transparency, consistency and standardize regulatory processes in the financial sector. RegTech development companies focus on creating solutions for regulatory monitoring, reporting, and compliance to deliver clear interpretations of ambiguous regulations at higher quality levels and lower cost. So FinTech development companies often partner with RegTechs to ensure their solutions are secure and meet the highest industry standards.

So is RegTech the next big thing in finance? What does it have to offer? And how do companies adopt this technology?

Global demand for regulatory, compliance, and governance software is expected to grow from $80 billion to $118.7 billion by 2020.

Regulators are raising the technical requirements on companies

More and more financial companies are turning to RegTech development vendors to implement data analytics, quantitative risk modeling, real-time reporting, and more into their current processes. One of the major drivers for this is the high cost associated with the existing server-based infrastructure and concerns about the risks associated with gaps in existing technology.

Leading banks such as HSBC, Deutsche Bank, and JPMorgan, spend well over $1 billion annually on regulatory compliance and controls.

Ambiguous regulatory requirements and legacy systems are other important reasons why many financial institutions are now looking externally to partner with software providers. To upgrade the existing technology, RegTech development companies are helping financial business by creating software for automating compliance workflows. Cognitive technologies and enhanced analytics help financial companies understand the explicit and implicit meaning of the regulation and automate numerous processes.

RegTech development

Source: EY

How can RegTech solution development solve the compliance and regulatory reporting challenges?

  • Efficient payment transaction monitoring

One of the key bottlenecks in the monitoring of payments transactions (especially in real-time) is the low quality and great incompatibility of transaction metadata churned out by payments systems. RegTech can simplify the automated interpretation of transactions metadata and help recognize money laundering and terrorist financing.

  • Automated trading in financial markets

RegTech development helps automate a wide range of regulatory tasks including margins calculation, choice of trading venue, choice of the central counterparty, and assessing the impact of a transaction on their institution’s exposures. This results in increased speed and trading efficiency as well as successful compliance.

  • Identifying new regulations and customers

RegTech solutions can help automate the interpretation of regulations including identifying new regulations and allocating different compliance obligations to the responsible units across an organization. Moreover, as required by KYC regulations, client and legal person identification could become more efficient with the help of automated innovative solutions such as fingerprint, iris scanning, blockchain identity, etc.

To find out more about regulations, compliance, and security in the context of software development, read this article.

Technologies trending in RegTech development

  • AI and machine learning for identifying and predicting risks in RegTech

Machine learning, artificial intelligence and other innovations in automated analysis and computer thinking create endless possibilities when applied to compliance. For instance, data mining algorithms based on machine learning can efficiently organize and analyze large data sets, even unstructured or of low quality.

Machine learning can improve the interpretation of low-quality data outputs from payments systems. It has the potential to create more accurate risk models and self-improving methods for data analysis, modeling, and forecasting as needed for stress testing.

According to Baker McKenzie survey, around 49% of senior executives from fintech companies expect their companies to use AI for risk assessment during the next three years. Moreover, 29% said that their companies will apply Artificial Intelligence to learn more about their clients and prevent money laundering. While 26% anticipate AI will help them with regulatory, risk, and compliance issues. In the future, AI-based software is expected to be applied for automatically interpreting new regulations.

One of the notable examples of machine learning in RegTech is AlgoDynamix, which uses adaptive algorithms to detect the disruption in finance. The company’s analytics engine uses primary data sources (e.g., the world’s global financial exchanges) and machine learning to combat trade fraud, helping the customer trace any suspicious or irregular activity during large market or financial instrument shifts. It also makes predictions about potential price movements, sometimes days in advance.

Another example is WorkFusion – an AI-powered RegTech company which provides a suite of automation software to centralize data, digitize documentation and provide a secure portal for transmitting information across various industries including banking and financial services. The company has recently raised a $35M in funding to expand its offering and add new features such as sanctions screening and reducing false positives in the KYC process.

  • Blockchain for automating compliance procedures

RegTech is now starting to provide assurance and compliance solutions on top of the blockchain. This technology can potentially eliminate the need for regulators and insurers to duplicate their own records, it may improve the speed and quality of the regulatory review process.

Blockchain will allow regulators to oversee compliance since all of the actions are tracked on the blockchain. Regulators can now modify or prevent actions if certain predefined conditions are met. Thus managing pre-described limits such as capital and liquidity limits or restrictions becomes easier with this technology.

Moreover, blockchain can reduce the cost of compliance procedures through increased speed and automation. It may act as an execution platform or a mechanism to store transactional information. Regulators would not have to collect, store, reconcile and aggregate themselves since blockchain data is shared by design.

For instance, a US RegTech startup Tradle simplifies and secures KYC requirements using blockchain technology. This company utilises communal networks and improves the accessibility of KYC data for auditors. Its blockchain-based bot framework enables financial institutions to build new customer interactions and customize compliance rules.

Another distinct example is blockchain-based startup Elliptic, which provides RegTech services for the financial sector. The company identifies itself as a global standard for blockchain intelligence. The company collects and constructs private data sets that are only accessible when using a password. It identifies illegal activity on the Bitcoin blockchain and provides proof of identity for Bitcoin users.


All in all, a growing number of banks and financial companies are turning to the new regulatory technology to navigate the shifting regulatory landscape. RegTech development is already helping financial institutions automate mundane compliance tasks and reduce compliance risks.

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