Accenture Analytics Apps Target ‘Domain Experts’

Among the largest consumers of data analytics is the financial services sector. As vendors tout new analytics platforms for the masses that push tools deeper into organizations and beyond data scientists, even management consultants are getting into the act.

Among them is Accenture Analytics, the big data arm of management consultant and technology services giant Accenture. Its analytics unit rolled out a batch of big data applications this week aimed at placing market insights at the “fingertips” of more corporate users.

Accenture said Thursday (June 11) its analytics applications platform targets financial services firms looking to retain customers, boost sales, simplify the credit scoring process or cutting costs associated with claims fraud.

Consistent with the trend toward driving analytics deeper into organizations, the management consultant said its package of applications could be customized for specific users, from data scientists to company executives. The package is also being promoted as tunable to specific workflows aimed at particular use cases.

Accenture, which launched its apps analytics platform in May, is attempting to differentiate itself from competitors by offering turnkey analytics for specific applications ranging from real-time credit decisions and a wealth management tool kit to applying predictive analytics to cut losses from claims fraud and “customer churn management.”

Accenture said it has so far developed 22 applications for financial services, retail, telecommunications and utilities. Among the predictive analytics tools are apps for forecasting product and resource demand, specific market forecasts for utilities and retail fraud detection.

The platform requires only “soft” programming skills to create applications and accompanying algorithms that are said to leverage and support third-party components as “analytical engines.” Accenture stressed that users do not need to know SQL or a programming language since the platform uses metadata definitions to retrieve data and connect it to an analytics engine.

For non-data scientists, the Accenture platform uses an automated modeling approach geared to business users who are considered “domain experts.” Hence, the platform relies on self-extracting technology that is able to mine data, apply models and algorithms, connect the dots and deliver a summary report on a specific business driver.

The “predictive pillar” of the Accenture platform leverages advanced algorithms for scoring, clustering, profiling and text mining based on decision trees, neural networks and machine learning techniques, the company said. Among the applications for the predictive analytics feature are fraud prevention, risk reduction, predicting asset downtime and customer attrition.

Accenture also has been busy expanding the reach of its analytics unit, announcing in February that it was acquiring the Brazilian analytics service vendor Gapso. The acquisition gives Accenture Analytics a foothold in the Brazilian market where Gapso’s clients include oil and gas companies, mining, agriculture along with steel and other manufacturers.

The deal also gives Accenture another new asset in short supply: experienced data scientists.

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