Key takeaways from the blog
- Regulatory changes are ever-evolving across different domains and business sectors.
- Multi-generation legacy systems and the volume of regulatory changes pose challenges.
- AI-driven automation solutions help navigate the complex landscape with ease.
Frequent regulatory changes create a challenging environment for businesses to rapidly identify, understand, code, and incorporate them into their processes. Businesses and their professional service providers, ranging from management consulting, security and compliance, accounting services, to legal services, have to continuously look for changes in this space and bring the processes quickly up to speed. Missing out on these changes results in exorbitant penalties for the businesses. According to analysts, in 2024 alone, banks paid penalties of $19 bn to regulatory authorities for compliance breaches. Similarly, healthcare services faced penalties amounting to well over $2 bn in 2024. Specialized professional services, such as those in areas like regulatory compliance, have evolved over the past decade to support different industries in ensuring compliance, minimizing risk, and reporting to regulatory authorities in a timely manner. However, they encounter many pitfalls that hinder their ability to continuously adapt to change and deliver at scale. AI-driven automation enables service providers and their customers to safely navigate and adapt to the evolving regulatory compliance landscape.
Compliance challenges faced by professional service providers
Globally, the regulatory compliance landscape poses unique challenges to small and large businesses. Specialized service providers take on this challenge on behalf of the businesses. Still, they have to navigate a tough terrain while continuously monitoring regulatory changes for their customers, who are spread across a wide range of industries. The major challenges are:
- Dynamically changing regulations: Highly regulated industries, such as financial services and healthcare, continuously go through changes to laws and regulations. Monitoring these changes and amendments across different geographies and industries is a mammoth task. Reading through huge volumes of legal documents, caveats, corollaries, and government circulars for different industries is a highly tedious and error-prone process. Translating legal language into business and technical rules is challenging, with a minor mistake resulting in a customer face-off and reputational damage.
- Huge data variety and volumes: The regulations and their format vary from time to time. Ensuring compliance at the micro and macro levels across all stakeholders, including customers, partners, and employees, is daunting. Conducting periodic updates, such as KYC, and maintaining audit-readiness is another mammoth task to deal with. Additionally, most businesses have data dispersed across different siloed legacy systems. The scenario proves detrimental to maintaining a single view for compliance monitoring in real-time. Slicing and dicing this siloed data and laying it out to complete a jigsaw almost always fails to identify and target procedural gaps.
- Manual processing: Regulatory compliance audits have traditionally been done through manual operations. However, with rising workloads and compliance requirements, the regulatory checks and audits are done only on a sampling basis instead of meticulously checking each and every transaction. These mechanisms create gaps and lacunae through which discrepancies easily fall through, missing important alerts and errors.
- Multi-generational legacy systems integration: Service providers catering to sensitive areas such as regulatory compliance have to build automation solutions by integrating different generations of business applications and enterprise resource planning systems. They have to design different middleware solutions to bring the multi-generational systems on the same plane to talk to each other, and then design the compliance monitoring solutions. The situation gives rise to risk, and the system integrations themselves have to be monitored separately, in case they snap due to a change in the interfaces at any level.
Take regulatory surveillance to the next level with AI-driven automation
Intelligent automation and AI solutions for professional service providers help them to go beyond the pain points associated with reactive, manual regulatory compliance operations.
Some of the important advantages of AI-driven automation solutions in the regulatory compliance space are:
- Real-time interpretation: AI empowers service providers to ingest and analyze thousands of compliance documents and caveats at speed. It helps to contextually identify new rules and changes stated in legal language, identify the areas of impact, and reduce the effort required for manual text research, analysis, and interpretation.
- Conversion of regulations into code: The AI-driven solutions convert the identified regulatory changes into business rules and code. The capability of these solutions to convert the identified regulatory changes into technical code and integrate them into the compliance monitoring solution minimizes compliance risks.
- Unified monitoring: The solutions aggregate data from different enterprise business systems, clean the data, and create a unified view. The resulting high-quality dataset enables the specialized service providers and their customers to conduct seamless monitoring across the enterprise and perform compliance checks.
- Anomaly identification: AI solutions detect anomalies at speed and scale. They help move away from rule-based monitoring and identify anomalous transaction patterns vis-à-vis normal work patterns. These solutions significantly augment human capability to accurately identify true positives that are oblivious to the human eye.
- Reporting at speed: These solutions automate data collection, aggregation, and reporting for compliance purposes. They extract only the required information and validate it to create submission-ready reports, thus significantly reducing manual effort and error, and report at speed to regulatory authorities.
- Audit-readiness: The solutions are adept at conducting real-time audits through automated monitoring across all pre-defined process nodes. When the solutions detect faults, they automatically raise a flag for quick remediation. They always generate an audit trail that can be revisited to prove audit-readiness through a proactive approach.
- Due diligence at speed: AI helps to collect and collate data and documents during important events, such as Know Your Customer and Mergers & Acquisitions, and screens the parties involved by analyzing the submitted information and that in the public domain. It expedites the process, generates data-driven insights for quick decision-making, and improves turnaround time.
- AI-driven integration: AI solutions use intelligent APIs to talk to multi-generation legacy systems. These APIs and connectors are designed to adapt and interact with the different business systems. They simplify the integration and reduce the requirement for rule-based customization.
- Predictive maintenance: AI automation solutions monitor the overall integrated business application ecosystem for stability and performance. The mechanism continuously monitors the integration to ensure proactive maintenance. The solutions reduce process disruptions and maintain continuity of operations and compliance procedures.
AI-driven automation enables businesses to adopt a more proactive approach by building agile and efficient solutions for regulatory compliance. It transforms compliance from being a reactive approach to a more proactive and strategic approach.
Use Case Scenario 1: Compliance monitoring
Intelligent automation and AI enables professional service providers and their customers to automate repetitive and judgment-intensive tasks, such as compliance monitoring, delivering accurate outcomes. Some of the major automation outcomes of the process are:
- Automating the regulatory change identification and management: Professional service providers have to continuously adapt to changing regulations, such as GDPR, AML, SOX, etc. Automation solutions use Natural Language Processing (NLP), Natural Language Understanding (NLU), and Natural Language Generation (NLG) to scan regulatory documents and generate summaries. On identifying a new regulatory change, the AI-driven solution identifies the target systems for process changes and triggers the process workflow for the updates.
The solution then orchestrates the Automation to update configurations and documentation across different business applications, ensuring compliance at speed with the new regulatory requirement. The AI-driven automation solution ensures consistency in the enterprise-wide regulatory change compliance, its rollout, and necessary dissemination.
- Automating risk identification and monitoring: The AI-led automation solutions are adept at identifying and predicting risk. The solutions analyze a vast volume of transactional data and learn about the business-as-usual processes. Any anomaly in terms of transaction size or events, or resemblance to an earlier anomalous precedent, is quickly identified and flagged for remediation.
The solutions track and monitor the processes vis-à-vis key risks, process exceptions, or late submissions against pre-defined limits. As soon as the process reaches any risk threshold, the solution triggers an alert for human intervention before the breach actually materializes. Some solutions are adapted to halt the process in case of an impending violation.
- Automating regulatory reporting: Regulatory reporting involves aggregating data from different systems and applications. The AI-led automation solutions automate the complete reporting process. The solution orchestrates the AI Agents to extract and validate the required data and include the appropriate regulatory tags. The solution is adept at directly filing the reports with the regulatory authorities to avoid late submissions.
The solutions are adapted to GRC (governance-risk-compliance) framework as part of a holistic strategy to align the business objectives with the changing regulatory landscape. The solutions aggregate the compliance metrics across the supervised and unsupervised automation processes to create a real-time view for the leadership and management. The solutions also facilitate automated regulatory reporting.
Intelligent Automation and AI enables professional service providers to confidently navigate the maze of regulatory changes, allowing them to focus more on their core competence of complex analysis to deliver higher value to their customers.
Use Case Scenario 2: Audit Readiness
Sensitive business sectors, such as healthcare and banking, have to be audit-ready at all times. Intelligent Automation and AI makes audit-readiness a reality. With instant data ingestion, real-time data synchronization across business systems, AI-led unified business insights generation, and process transparency, Intelligent Automation offers the complete solution for being audit-ready.
- Automation of data management protocols: Intelligent Automation enables professional service providers to help their customers stay ahead in data management. AI-powered automation solutions extract, classify, and validate unstructured data with high accuracy from different business documents and integrate it with the downstream systems. It ensures that high-quality data is available for audit work.
Similarly, AI-driven task automation connects multi-generational systems to automatically synchronize data in real-time. Complex processes, such as reconciliations across high volumes of data in financial reporting, become easy with these solutions. AI seamlessly execute processes in the background and flag anomalies for human intervention.
- Automated audit trails: The AI-driven automation solutions generate a scrupulous digital trail of the transactions. Each action that is executed, 24x7, in the background leaves a timestamp. As a result, the un-editable trail becomes available for audit scrutiny and operations. AI-led automation sets a good precedent for control operations, which are much required to be audit-ready.
The solutions reduce the burden on human resources for gathering data for audits, thereby supporting audit operations and query resolutions. The systems also take screenshots and report specific user access for high-value transactions. The solutions enable businesses to be audit-ready for internal and external audits.
- Continuous monitoring: Manual audits conduct scrutiny on a sampling basis. AI-led audit operations enable professional service providers to have a keen eye for a detailed 100% audit.
Intelligent bots are configured to perform thorough checks across different process nodes. If a pre-configured rule is broken, the solution raises a flag for immediate human action. AI enables professional service providers to establish a control environment for their customers that serves as a precedent for audit readiness to auditors.
Intelligent automation solutions create an in-house control environment that is instrumental in reducing the requirement for expensive external audits. The solutions support continuous monitoring and eliminate downtime caused by costly disruptions resulting from different internal and external forces.
Use Case Scenario 3: Instant compliance document retrieval
Businesses must be prompt at audit-proof retrieval. The scenarios range from facing internal and external auditors to retrieving safety data sheets from humongous repositories for HAZMAT transportation through different modes.
- Intelligent ingestion: AI-driven automation solutions ingest the document sheets in different layouts and formats, extract the unstructured data, and convert it into a machine-readable and structured format. AI automation will monitor the input sources, including supplier emails, SFTP locations, and web portals for new documents. Automation solutions leverage AI/ML models and convert the documents into context-aware, structured data that is easily searchable.
- Data indexing: The solution indexes the extracted data and is prepared for retrieval augmented generation (RAG), which makes sense of the semantic meaning. Preparing the data enables the user to raise searches in natural language and retrieve contextually aware answers. The solution works even if the actual keyword is absent or the search string has a mistake.
- Natural language-driven searches: Advanced search using RAG allows users to find accurate information using natural language. It also leverages LLMs to generate more accurate and context-aware external information. It allows users to retrieve the latest information from external sources without retraining the model, for example, searching SDS for a new chemical transportation.
Simply put
The changing regulatory landscape presents a complex and challenging environment for businesses and professional service providers. The challenges stem from the continuous and large-scale regulatory updates that have to be complied with. Manual operations are tedious, error-prone, and costly. AI-driven automation solutions enable professional service providers in the regulatory compliance space and their customers to navigate the mesh of complex technical hurdles and volume challenges of converting regulatory changes into code and integrating them with multi-generational legacy systems.
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