2011-05-01
“It would be unimaginable for us to complete this major project without ACL technology. Our audit team has become far more confident and continues to move forward with deeper data analyses.”
João Vieira Filho, Internal Audit Coordinator, Instituto Nacional Do Seguro Social
The INSS is a Brazilian federal government agency that protects 37 million workers and their families through a public social security policy. As the agency began developing an audit analytics program to identify data errors and fraudulent benefit claims, the Internal Audit department applied ACL analytics to demonstrate the need for permanent information exchange partnerships. The INSS team scheduled a series of meetings with other government agencies that used ACL analytics to cross-reference – in real time – agency and INSS data to reveal irregularities. Meeting participants could immediately see the need for technical cooperation and were impressed by the speed, simplicity and power of ACL. With seamless technology and a quick proof of concept, the INSS is rapidly moving toward an effective audit analytics program and an agency that supports Brazil’s working population.
The INSS is an independent agency of the Brazilian federal government that protects workers and their families through a public social security system. Every month, the INSS pays over £16 million in benefits. The organisation has 1,110 subsidiary agencies throughout Brazil and over 38,000 staff. To grant benefits, the INSS manages a database on Brazilian workers (CNIS) that contains 500 million records and information on 10 billion remunerations. Every month, the CNIS receives 7 million pieces of information from companies and organisations that employ 37 million people.
The Brazilian federal government recently implemented a new policy designed to grant social security benefits in 30 minutes or less, and moved the burden of eligibility proof from individual workers to employers and government. This means the INSS must maintain accurate data records and monitor incoming information for fraudulent activity and inconsistencies.
In addition, the INSS needs a way to monitor benefits that have already been granted, in order to pinpoint fraud and identify civil servants who hold more than one government job – a scenario prohibited by Brazilian federal law. The INSS must also monitor payments connected to commitments in the “means and ends” area and information that arrives daily through the multi-platform service network, which includes online portals, call centers, and individual agencies.
These challenges have a direct impact on the agency’s compliance with its institutional mission. With help from the Internal Audit department, the INSS is developing internal control mechanisms and a CNIS monitoring environment that will validate or refute data that enters the system each day. The ultimate goal is to establish permanent, real-time data exchange agreements between cooperating government agencies that will support stronger controls and seamless access to critical information.
The INSS Internal Audit department identified ACL technology as a strategic solution to detect illegal government job and social security benefit accumulations. The project requires technical cooperation agreements, so initial meetings with agency control areas must demonstrate the existence of data irregularities and help overcome government bureaucracies.
With ACL software, the INSS team can conduct real-time demonstrations that take data files from cooperating agencies, convert the format, and cross-reference institutional databases to reveal inconsistencies for further investigation. It’s an innovative and effective way to reinforce the need for technical information exchange agreements and demonstrate the power of automated data analytics.
Participating government agencies have been highly impressed by how quickly ACL technology can cross-reference disparate data sources and immediately identify exceptions. Cross-referencing agency data will allow the INSS and its partners to correct many of the existing data irregularities and to analyse new information for errors and fraud. The Internal Audit team uses ACL on a daily basis and has now extended the solution to enhance the organisation’s business and human resources departments. In the past, data cross-referencing mechanisms were unreliable, slow and didn’t allow full access to large databases.
With ACL, the INSS had expanded its audit horizons and is working to improve automation processes – even as the agency sees significant data volume increases with each new partnership agreement. Audit team members are enthusiastic about using ACL analytics and feel equipped to tackle increasingly complex data analyses.
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