The Future of Risk Management Leveraging Artificial Intelligence & Automation is Here

As the cost of labour, the volume of transactions, and the regulatory requirements and enforcement continue to increase, the risk executives are resorting to advanced technologies, such as artificial intelligence and automation, to complement scarce human talent to drive efficiency and efficacy while balancing risks, costs and regulatory constraints.

The average cost of financial crime compliance now is 121% higher than pre-pandemic cost

Ransomware filings have substantially increased from 487 in 2020 to 1,489 in 2021, and the value of ransomware-related BSA filings in 2021 approached $1.2 billion—a 188% increase compared to the previous year

While Beneficial Ownership changes are upcoming - effective Jan 1, 2024, FinCEN will continue to make further changes to protect the interest of individuals, entities and corporations

So, how are the early adopters transforming?

Fraud and Debt Analytics

In this cluster of risk areas, the risk executives are automating AML/CFT processes and detection of fraud, grandparents scams, default and credit risks using Artificial Intelligence and automation. Let's deep-dive into AML/CFT automation use-case.

AML/CFT Compliance

AML/CFT process - identity validation, performing KYC, authenticating access, transaction and monitoring - is a complex rules-based process, and has traditionally been a manual process. The average amount of time spent completing due diligence is enormous:

Foreign Corporations: 67 hours

Foreign SME: 58 hours

Domestic Large Corporate: 45 hours

Domestic Midmarket Corporate: 43 hours

In addition to this, further efforts on required on record keeping and SARs reporting, particularly for large transactions, EFTs and casino disbursements. AML/CFT SMEs typically find several activities - sanctions screening, the positive ID of PEPs, regulatory reporting, KYC onboarding, efficient resolution of alerts and customer digital identify verification - in compliance screening operations the most challenging.

The solution: The early adopters in Risk Management are strategically leveraging Artificial Intelligence and Automation in the following ways:

• KYC: Harnessing the capabilities of an intelligent agent (IA) to perform KYC - validate proof of registration, listing, business presence, and activities performed by the corporation from the company's 10k and 10q filings and websites
• UBO, Sanctions and Screening Checks: Leveraging the capabilities of an IA to check core banking systems and corporations' onboarding documents, and comparing the data to 10k and 10q filings and Almanac's database. Additionally, these early adopters are leveraging AI and automation to perform sanctions checks and PEP screening using WorldCheck, LexisNexis and respective screening databases. Furthermore, they are also using IAs to perform Google searches for adverse news
• Data Consolidation and Preparing SARs Report: Harnessing the capabilities of an IA to consolidate data and prepare SARs reports for the AML/CFT specialists to review and submit
• False Positives: Leveraging the capabilities of an IA to review and eliminate false positives

Risk Modeling

In the area of risk modelling, the early adopters are leveraging AI and automation to enhance the efficiency and efficacy of strategic planning, capital allocation and performance management.

Emerging Risk

According to Jim Lee, Chief of IRS Criminal Investigation, "Advancements in virtual reality combined with an internet that is growing more decentralized will present potentially major challenges for policing financial crimes". The domain of web3 and metaverse is nascent and rapidly evolving. Specific AI and automation use cases will be developed as web3 and metaverse continue to mature.

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