Turn hours into minutes with rapid prototyping.

It’s critical for fi nancial institutions to know exactly what’s in a contract as well as each version of that contract.

DataSkill’s ACUMI software, powered by IBM Watson, enables these organizations to automatically extract data from a high volume of complex documents. This unattended process is highlighted by rapid prototyping and the ability to identify specific information crucial for moving business forward.

For example, the software makes it possible for a bank’s legal team to locate specific legal terms within minutes, not hours or days. This is key for finding potential compliance violations and missing elements, such as signatures and calculations.

Transform the underwriting process.

In the insurance industry, risk classifications get trickier as proprietors get more creative. For example, what if a barbershop incorporates alcohol sales by adding a bar counter? What is the proper risk classification now? Underwriting challenges like these are increasing and data isn’t always accurate.

ACUMI and Watson have revolutionized the insurance underwriting process. The solution gathers public and private information from websites and social media and interprets it into the underwriting model. From this data, the technology can accurately classify businesses, resulting in higher revenue and a more efficient underwriting process. This is also made possible by rapid prototyping.

Gain the cognitive advantage.

By automating the knowledge worker, financial services institutions can gain a cognitive edge over competitors. Thanks to the solution’s intelligent automation process, our clients recognize results that are more accurate, rapid, consistent and repeatable across the organization.

ACUMI empowers financial services organizations in the following ways:

• Automates “knowledge worker” intelligence with cognitive models
• Mitigates costly regulatory fi nes and penalties
• Extracts data from high volumes of unknown documents with similar data
• Collects and analyzes data for the best possible accuracy rate
• Reduces workload through automatic identification and classification of cases
• Improves risk models and data quality