By Rebecca Bradshaw, Director, Rotherham Taylor
Data management and analytics are among the most popular uses of artificial intelligence (AI) in UK businesses – with around half of finance and accounting firms using or planning to adopt AI technologies.
This points to the widespread use of one of the most significant capabilities of AI, namely the ability to not only process data but understand it and assist in decision-making.
The implications of appropriate AI use in financial compliance, then, is clear.
Enhancing onboarding
As a sector, accountancy has always been concerned with enhancing compliance in order to protect its practitioners and clients, and for the general prevention of financial misconduct.
From the outset of a client relationship, we have developed sophisticated manual ways of doing so, including due diligence, anti-money laundering (AML) checks and credit references.
However, we know that manual onboarding is neither the most efficient way of doing things, nor is it the most conducive to a great client relationship.
Using machine learning and pattern recognition for onboarding clients can help to identify irregularities or missing or inconsistent information during compliance checks.
An AI solution can also enhance compliance reporting on an ongoing basis, with data collection and report generation capabilities.
Revolutionising the audit process
As a way of maintaining continued compliance with reporting requirements and regulations, AI has significant advantages over traditional, manual processes.
The shift towards cloud accounting has provided many financial services providers with real-time data on client transactions, accessible from anywhere.
This means that audit providers have the opportunity to transform the process from a reflection to a proactive process which can more effectively and quickly identify discrepancies.
However, this clearly carries a significant labour burden – unless you introduce AI into the equation.
Certain AI programmes have the ability to process large amounts of data and identify patterns, including where data deviates from an expected pattern, which could indicate financial mismanagement or an error.
Identifying these quickly can ensure continued compliance and a reduction of long-term risk.
Predictive analytics
AI doesn’t just identify current or past anomalies – it also has predictive capabilities.
By analysing trends and patterns in historical data, AI can forecast potential areas of risk or non-compliance before they become significant issues.
This predictive insight allows auditors and compliance officers to focus their efforts on areas with a higher risk of error or fraud, thereby optimising the audit process and ensuring resources are used effectively.
Compliance at the centre
AI tools do not replace human auditors but rather enhance their capabilities by increasing data management and processing capacity.
This is integral to ensuring ongoing financial compliance, particularly as firms grow and take on new clients.
By handling routine data analysis, AI frees us up to focus on higher-level strategic assessments and decision-making.
We can then apply our expertise where it adds the most value, interpreting AI-generated insights, and providing strategic advice to enhance business operations and financial compliance.
To find out more or seek tailored financial support, contact the Rotherham Taylor team today.
