About a-team Marketing Services

A-Team Insight Blogs

FinScan Combines Data Quality Experience with Technological Expertise to Deliver Agile AML Solution

Subscribe to our newsletter

FinScan has combined experience in data quality with technological expertise in screening to provide an Anti-Money Laundering (AML) solution designed to help financial institutions develop more efficient AML programmes that generate fewer false positives and support better detection of true alerts.

The company is part of Pittsburgh-based Innovative Systems, which was founded in 1968 and developed data quality solutions to cleanse, profile, match and link data with precision. In 1995, Innovative Systems applied its data matching technology to address the need for AML compliance screening and created FinScan.

“We have two lines of business, data quality, which provides our customers with accurate data to make better business decisions, and FinScan, an AML application based on our data quality engine,” explains Mayank Sharma, senior product marketing manager at the company. Data preparation capabilities provided by Innovative Systems improve screening accuracy and efficiency by fixing data anomalies and provide a base layer for FinScan AML, which includes modules covering customer screening, entity screening, transaction screening, ultimate beneficial ownership due diligence, and risk scoring of business relationships.

The solution comprises a proprietary data quality engine based on early work by Innovative Systems, a crowd sourced data dictionary that captures phrases and name patterns, and access to over 70 public sanctions and exclusion lists, including OFAC, HM Treasury, EU consolidated and terrorist lists, PEPs and more. Using cognitive and fuzzy data matching algorithms rather than rules-based probabilistic or weighted field scoring approaches common to many AML products, FinScan claims to reduce false positives and provide explainable matching that can be shared with regulators. The inclusion of AI automates the detection of names in different records and provides a simulation tool to suggest what users should see if a data field is missing.

FinScan can be used on premise, cloud hosted or in a hybrid environment with the majority of new users favouring the cloud option. It runs natively in the Microsoft Azure cloud, along with FinScan services such as constant updating of sanctions and PEPs lists. It can also be implemented in other clouds such as AWS or Google Cloud, although at this stage, users must manage the database maintenance and scheduling activities.

Sharma highlights FinScan’s differentiators in the AML market as advisory services provided to customers ahead of solution implementation, the capabilities of the company’s data matching engine, and its data dictionary. He concludes: “We go to market to help firms find hidden risk so that our customers can do business confidently.”

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Unlocking Transparency in Private Markets: Data-Driven Strategies in Asset Management

10 September 2025 10:00am ET | 3:00pm London | 4:00pm CET Duration: 50 Minutes As asset managers continue to increase their allocations in private assets, the demand for greater transparency, risk oversight, and operational efficiency is growing rapidly. Managing private markets data presents its own set of unique challenges due to a lack of transparency,...

BLOG

Challenges of the New Regulatory Landscape: Data Management Summit London Preview

The regulatory landscape for financial institutions has rarely been in greater flux than now, placing new challenges on the technology and data that will be critical to satisfying the requirements of overseers. While digital innovations are offering organisations the opportunity to meet their compliance obligations with greater accuracy and efficiency, they are also encouraging regulators...

EVENT

AI in Capital Markets Summit New York

The AI in Capital Markets Summit will explore current and emerging trends in AI, the potential of Generative AI and LLMs and how AI can be applied for efficiencies and business value across a number of use cases, in the front and back office of financial institutions. The agenda will explore the risks and challenges of adopting AI and the foundational technologies and data management capabilities that underpin successful deployment.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...