Three years ago, NuAgeBI was founded on the premise that customers were following traditional methods of risk discovery pf financial transactions sourced from balance sheet and income statements.
The problem that NuAgeBI’s founding team identified with this approach was that it required the knowledge of the risk and also a specific material amount to identify risky transactions. In response, NuAgeBI was founded as a financial risk analytics company to address the void in the market.
The available tools on the market are on-premise technology, with the industry headed for SaaS and on-cloud deployment. NuAgeBI breaks this mold as the first company to offer a self-service component beside the existing and limited technology. The startup targets internal audit and controllers of mid-to-large size companies that require technologies providing financial statement risk assessments on an ongoing basis.
HANA Use Case
A multi-national technology company required financial statement risk assessment on an ongoing basis that was cost effective, and addressed the following pain points:
- Business users have a concern that they may have unusual debits/credits they are not aware of
- They have a reactive approach based on previously identified issues rather than current facts
- Business Users were spending too much time following false positives transactions flagged by rule-based KPIs
NuAgeBI’s proprietary solution combined the power of predictive analytics, visual analytics, and rule-based anomaly detection to accomplish:
- Self-service platform removes the complexity of extracting information from disparate sources
- Minimizes false positives and identifies high risk transactions
- Provides the ability to drill down into data and offer actionable insights
The comany’s business users are able to identify strategic problem areas:
- Unusual financial transactions that highlight lack of proper control and oversight
- Historical trend of such transactions and details without involving IT
- Other high risk transactions that indicate revenue recognition issues
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