Financial crime is a burgeoning crisis with colossal ramifications—significant monetary losses, market volatility and damage to institutional credibility. Money laundering alone drains economies worldwide of an estimated $5.5 trillion every year, a whopping 5% of the global GDP, as per Napier AI research. With the face of fraud constantly evolving and heightened regulatory scrutiny further tightening the noose around financial gatekeepers, it is imperative they modernise their compliance frameworks.
But ironically, new-age technology is both the sword criminals are using to perpetrate financial crime as well as the shield institutions are wielding to combat it. While fraudsters are turning to Artificial Intelligence (AI)-generated deepfakes and synthetic identities to outflank legacy security systems, organisations are increasingly relying on AI and its subsets to fortify their prevention and compliance strategies. Better still, many entities are utilising managed services to do so.
What are managed services in Financial Crime Compliance (FCC)?
They involve partially or totally outsourcing compliance operations like Anti-Money Laundering (AML) and Know Your Customer (KYC) processes to specialised third-party providers. While these services help institutions reduce costs, scale operations, access state-of-the-art technology and meet regulatory requirements, most importantly, they blend AI-driven efficiency with human expertise.
Before further exploring the role of managed services in FCC, let us examine what AI brings to the table and why financial institutions must tap into it.
- Anomaly detection/transaction monitoring: AI algorithms analyse vast volumes of data to identify anomalies and fraud patterns that traditional, static systems may miss. They monitor payment transactions in real time, flagging suspicious activity as it occurs and helping institutions contain threats before any significant harm is done.
- Elimination of false positives: Lacking contextual intelligence, legacy systems generate a high percentage of false positives. Machine Learning (ML) studies and analyses normal operational habits to establish dynamic baselines, thereby minimising false positives and enhancing genuine threat detection. AI-based AML services use advanced neural networks to uncover multi-layered fund movements (shell companies, mule accounts) and separate them from ordinary transfers.
- Improved KYC/customer due diligence: AI tools are transforming the KYC process from a document-heavy workflow to automated verification. They extract data from identification documents, verify authenticity and instantly detect synthetic identities, drastically reducing compliance workloads.
- Automating investigation/reporting: AI accelerates FCC investigations by automating tedious tasks like data gathering, summarisation and report filing, thereby allowing professionals to focus on high-risk cases and strategic decision-making. AI tools can review a case file and speedily generate detailed investigative narratives. They can dissect structured/unstructured data to automatically draft regulation-compliant Suspicious Activity Reports (SARs).
- Predictive risk scoring/threat adaptation: AI models continuously update customer risk profiles on the basis of transaction history, behaviour and external risk factors instead of using periodic manual reviews as a benchmark. Assigning dynamic risk scores enables targeted monitoring. ML algorithms continuously learn from new data and adjust to novel techniques employed by launderers.
Why managed services are the way ahead
Technology alone is not a silver bullet. Combining it with managed services can provide financial institutions the right arsenal to build a comprehensive defence strategy. Managed service providers (MSPs) leverage the best technology to handle multiple functions like data cleansing, transaction monitoring and regulatory reporting, apart from offering solutions like KYC as a Service (KYCaaS)—which includes customer onboarding, identity verification etc. However, MSPs rely on human expertise for critical contextual analysis that software cannot replicate. Their domain specialists handle complex investigations, assess flagged anomalies and ensure regulatory alignment.
Benefits of managed services in FCC include:
- Tech integration + domain expertise: MSPs continuously invest in cutting-edge technology like AI, ML and Robotic Process Automation (RPA), which help improve data quality and minimise false positive alerts. Also, institutions outsourcing FCC to such providers can immediately access highly skilled subject-matter experts in AML, KYC and transaction monitoring.
- Cost/resource optimisation: Outsourcing the day-to-day FCC lifecycle can hugely cut down operational costs and save talent resources, as institutions are no longer required to maintain large-scale in-house compliance teams or spend unnecessarily on infrastructure.
- Scalability/flexibility: MSPs offer flexible subscription models, allowing institutions to change the level of support needed based on seasonal workloads or market surges. Outcome-based pricing means one pays for measurable results and not billable hours.
- Audit readiness: Providers deliver audit-ready solutions—like standardised case notes and immutable digital timestamps on all risk assessments/transaction reviews—aligning with the latest regulatory standards. This reduces the risk of non-compliance fines.
A recent Hawk and Chartis report revealed 9 in 10 financial institutions now sincerely encourage AI use in FCC operations. According to Thomson Reuters, over 60% of large financial institutions’ compliance officers use outsourced services. These figures speak volumes about the path institutions are treading and what the future holds. Institutions that effectively leverage this man-machine collaboration—treating AI as co-pilot and keeping humans in the pilot’s seat—are set to soar.
How Infosys BPM can help
Infosys BPM offers FCC-as-a-Service, combining productivity, automation and optimisation to help organisations fight financial crime. Leveraging advanced analytics and RPA/ML/AI-driven automation, teams can detect fraud in real time, enhance regulatory adaptability and boost efficiency. Clients report up to 40% cost savings, 30% efficiency gains and faster regulatory adaptation, minimising risks while achieving sustainable operational excellence.
