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4 Trends to Watch in Regulatory AI

These top 4 trends of AI in regulatory compliance for financial services can give banks a competitive advantage in today's data-centric world.

Innovative technologies leveraging Artificial Intelligence (AI) empower the automation of regulatory compliance and business processes; analysts view this type of automation as a top trend for financial institutions in 2019. According to PwC, 20% of business executives surveyed plan to incorporate AI throughout their companies in 2019. According to Forbes, financial institutions that choose not to adopt AI now will lose significant competitive advantage.

The good news? Fintech, Regtech, and Insurtech startups are all enabling AI adoption, even for smaller and midsize institutions.

Trends Compliance Costs Keep Increasing

According to Accenture's 2018 Compliance Risk Study, compliance can no longer depend on adding new resources to increase effectiveness. Globally, 89% of responses from over 150 compliance officers at banks, insurance companies and capital market firms foresee increased compliance spending in the next two years. According to a survey by Duff & Phelps, compliance costs in the financial sector are on pace to double by 2022 – a staggering amount considering the current spend for compliance and regulatory obligations is already $270+ billion per year. Furthermore, banks have had to pay $342 billion in noncompliance fines between 2009 to 2017 – with some big banks fined in excess of $1 billion each.

The trending focus of spending earmarked for managing regulatory compliance is shifting from people to technology. Trust is rising that new technology can help institutions realize high returns (cost savings + improved compliance). The caveat? The bank needs a strategic approach and insightful understanding of how to effectively deploy Regtech solutions to gain the most value and benefits.

Managing & Understanding Regulatory Changes Requires Streamlining

Regulatory scrutiny has increased significantly since the 2008 financial crisis, and a decade later the pressure continues. More than 750 global regulatory bodies are pushing over 2,500 compliance rule books and giving rise to an average of 201 daily regulatory alerts.

Facing frequently changing regulations, financial institutions have a growing challenge to keep pace and properly interpret regulatory requirements and their impact. According to the 2018 Compliance Pulse Report, 64% of respondents feel they do not have enough time to manage all their compliance needs, while 1 in 3 respondents say the most pressing issue in compliance is staying up-to-date on regulatory changes.

Adopting AI technology will significantly benefit institutions, not only to manage regulatory changes but also to leverage their data to stay compliant and gain valuable insights.

Data-Centric Strategy For Compliance

Data is at the core of regulatory compliance. Regulatory lapses in reporting are typically due to weak data and reporting processes. The Basel Committee on Banking Supervision (BCBS) introduced standard 239 ("Principles for effective risk data aggregation and risk reporting") which provides a framework to institutions for data governance and infrastructure, risk data aggregation and risk reporting. As per Lourenco Miranda, Managing Director at Societe Generale "If you can't uniquely and precisely provide data with the granularity the Fed expects, you won't be able to produce the capital forecasts as you should".

Regulators expect banks to provide end-to-end data lineage (the ability to track data from its source to the report). Managing and maintaining this lineage as data goes through multiple systems and software is challenging. Studies show that 31% of institutions identify data quality issues as a key barrier hindering their organizations' progress and effective delivery for compliance. Meanwhile, analysts spend 90% of their time on data collection and organization, and only 10% on data analysis.

Adoption of Big Data and AI technologies can significantly enhance and enable data-centric compliance by providing automation and consolidation of regulatory compliance processes.

Reactive To Proactive Compliance

Intelligent data analysis and reporting present an opportunity to identify trends and better mitigate inherent risks. New regulatory regimes may lead to a more proactive approach to regulations; regulatory processes could become streamlined to such an extent that periodic regulatory reporting will be a thing of the past as regulators can get real-time data access and perform compliance checks on the fly. With technology such as Apache Spark, real-time data analysis and monitoring is readily available to financial institutions. Banks can define necessary fields to monitor their data, and granular real-time analysis of data can significantly expedite reaction time to identify and track fraud.

A proactive approach to compliance will require an end-to-end platform for data collection and mining, with in-built compliance features to automate regulatory processes and allow real-time identification of risk/fraud. Automation and consolidation of reporting and analytical processes facilitate this streamlined approach to regulations.

These trends all point to opportunities. In my next blog we'll explore the Top 3 Use Cases for harnessing the power of Regulatory AI in banking. The possibilities may amaze you.

 

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