Fidelity Investments has a new business providing financial institutions with technology to create compliant public communications material. Called Saifr, the new business will offer tools powered by Natural Language Processing (NLP) models trained on tens of millions of compliance-reviewed data records. The goal is to foster greater collaboration between a firm's marketing and compliance teams creating, reviewing and approving client communications, said Vall Herard, managing director of Saifr. "Ensuring that marketing materials are compliant with various regulatory rules requires multiple touchpoints inside and outside an organization, including content creation, compliance feedback, revisions, email, and workflow hand-offs," Herard said in a statement. "As a result, the process can be inefficient and create the opportunity for friction and risk."

Innovation in compliance can come in many forms. One such form was described by Vincent M. Walden, Managing Director at Alvarez and Marsal Holdings, LLC (A&M), in his article entitled "Profit & Loss-of-One"(P&L-of-One). In it, Walden detailed how he and his then colleagues at Ernest & Young (EY) worked in conjunction with the General Electric (GE) compliance function to "improve compliance by using forensic data analytics to provide behavioral insights to their compliance program." They did this through the innovative use of "digital twins" which Walden described as "digital replicas of physical assets that organizations can use for multiple purposes such as the maintenance of power generation equipment, jet engines and heavy machinery." In a more expansive definition, the consulting firm Gartner, Inc. described "digital twins" as dynamic software models of physical things or systems.

Given the increasing compliance demands on organisations from the public and regulators alike, companies cannot afford to neglect their compliance obligations. The role of compliance is to prevent, detect, respond to and remediate risk and financial institutions (FIs) must use all of the tools at their disposal to achieve it. Implementing an effective compliance framework requires the whole firm to be on board, from the C-suite down. The compliance function is in a state of flux, however – virtually unrecognisable from a decade ago. The catalyst for much of the change in the financial services industry was the global financial crisis.

The rise of financial technology has drawn the attention of regulators to FinTech firms and how they function. FinTech companies like any other regulated institutions are required to comply with a growing set of regulatory rules. One of the latest examples is the FCA's roll-out of Secure Customer Authentication (SCA) for e-commerce transactions. This will mean that card issuers, payments firms, and online retailers will have to follow more stringent authentication steps for European online payments over €30. However, the real regulatory pain for FinTech's is felt when scaling fast whilst entering new markets. Catering to new obligations from different jurisdictions places further regulatory scrutiny on their operations, ensuring that they are compliant with the various nuances of different regulators' rules.

Up until recently, compliance has mainly relied on people. And as a result of the significant increase in regulatory reporting requirements for financial institutions over the last decade, demand for compliance professionals has surged. Companies have had no choice but to hire more and more compliance staff, in an effort to tackle the growing regulatory burden. However, over the last few years, technology has begun to play a much larger role within compliance. Financial institutions and regulators have realised that by harnessing the power of technology, and more specifically, the power of artificial intelligence (AI) and machine learning (ML), a considerable proportion of the compliance function can actually be automated, reducing the burden on institutions and compliance professionals.

"It is no longer sufficient to do sampling for auditing, you have to boil the ocean," according to Joseph Lodato, global head of compliance technology and surveillance at Guggenheim Partners, in his keynote at the RegTech Summit US. Organizations are now required to trawl through the plethora of emails they send and receive each day to ensure they comply with regulations during an SEC examination. Making technology all the more important, a machine learning solution that flags suspicious emails would be advantageous in such a situation. As the remit for compliance officers continues to expand, they are increasingly looking at technology to augment their capabilities. Artificial intelligence powered by machine learning and big data has the potential to completely revolutionize the compliance world. Machine learning solutions are already widely used in front office activities such as dynamic portfolio rebalancing and high-frequency trading.

Front office jobs at investment banks are increasingly being taken over by intelligent machines. Many current front office employees are worried about being displaced by artificial intelligence, and their fears are not unfounded. Huy Nguyen Trieu, former head of macro structuring at Citigroup, has a positive message for traders who risk being replaced by automation: become a data facilitator. After 13 years in financial engineering at SocGen and RBS, before becoming an Managing Director and head of macro structuring at Citi, he has shifted his focus to acting as a thought leader in the fintech space. Currently a fintech fellow at London's Imperial College and mentor at fintech accelerator, Level 39, Nguyen Trieu is both fintech guru and entrepreneur.

New compliance technology such as AI and intelligent tagging has the power to change compliance. Our webinar which brought together in-house experts and external subject matter specialists has shed light on the latest cutting-edge technologies and how they can help solve the many day-to-day challenges faced by compliance professionals across the globe. In today's rapidly changing regulatory landscape, it is critically important for banks and financial institutions to respond to new regulations with agility, while ensuring that the customer experience does not suffer. These dual demands put pressure on compliance departments. Compliance technology in the form of end-to-end controls capable of mitigating a multitude of financial crime risks can help to alleviate this pressure.

Maintaining regulatory compliance is a daunting task. Up to 200 regulatory changes occur every day, varying from large scale regulation like Dodd Frank, to minute changes to the font and size of footnotes in regulation text. The cost of not being compliant is astronomical – since 2008, more than $50 billion in fines have been paid. Banks and financial institutions are looking for any advantage they can get to streamline operations and reduce compliance costs. IBM Think, the three-and-a-half day event that emphasizes'mankind machine', highlights using IBM's vast background in cognitive computing to, in this instance, help compliance professionals to play by the rules and maintain compliance, avoid sizeable penalties and leverage machine learning and artificial intelligence to make their jobs easier.

"It is no longer sufficient to do sampling for auditing, you have to boil the ocean," according to Joseph Lodato, global head of compliance technology and surveillance at Guggenheim Partners, in his keynote at the RegTech Summit US. Organizations are now required to trawl through the plethora of emails they send and receive each day to ensure they comply with regulations during an SEC examination. Making technology all the more important, a machine learning solution that flags suspicious emails would be advantageous in such a situation. As the remit for compliance officers continues to expand, they are increasingly looking at technology to augment their capabilities. Artificial intelligence powered by machine learning and big data has the potential to completely revolutionize the compliance world. Machine learning solutions are already widely used in front office activities such as dynamic portfolio rebalancing and high-frequency trading.