Artificial Intelligence (AI) is the next big challenge in software development for business and will be a key component of success across public and private sector institutions.
“I skate to where the puck is going to be, not where it has been.” – Wayne Gretzky
The ability for machines to “learn” creates an opportunity to amplify the contributions made by individuals or groups of people. Machine learning is a type of Artificial Intelligence that enables small and mid-size organizations to compete with larger companies despite their smaller workforce and inherent cost structure limitations.
How does it work? Machine learning occurs when a program is taught to interpret data collected through automated and non-automated processes. By performing real-time analysis and constantly updating its decision-making algorithms, the system will continually find ways to make better tactical decisions.
Over time the software identifies its own predictive factors and constantly “self-improves”. Machine learning software cost-effectively helps companies make better decisions while improving customer experience by offering customized customer journeys that can consider a wide range consumer preferences.
Artificial Intelligence Case Study – Elagy
Elagy is an InsurTech startup that is disrupting the insurance industry by integrating real-time analytics and insights into distribution, underwriting, and policy administration processes.
Provides services to companies including: Swiss Re, AIG, Plymouth Rock, Accuquote
Use predictive analytics as a point of differentiation
Founded by former insurance executives and industry consultants
Elagy needed a comprehensive technology platform that integrated its analytics services with insurance companies to help increase sales while improving their combined ratios.
Manage big data sets from multiple disparate data sources, including legacy systems
Integrate with distribution partners, 3rd party data sets, and customer proprietary databases
- HIPAA, PII, PCI and TCPA compliant
Quickly provide fast, scalable resources to large multinational organizations
Jaroop developers created the Elagy Data Analytics and Decision Making Engine that provides data aggregation, data analysis, and machine learning capabilities, enabling Elagy to provide a low cost, high benefit product to its customers.
Autonomous bidding on marketing leads
Automatic lead prioritization
Seamless integration with partner insurance organizations’ existing IT infrastructure, including legacy systems
AI generated, real-time system improvements
Since Elagy is a startup, getting a product to market quickly was vital to their success. Jaroop met with Elagy leadership, interviewed the Elagy staff, and together with the Elagy team, built the initial analytics and decision-making engine.
22% improvement in premium generated per marketing dollar spent
Reliability of 99.997% uptime
76% decrease in labor costs associated with new system
Real-time, dynamic bidding on insurance leads Full-access API capable of collecting all data from multiple legacy systems
Prototype completed within 30 days of start, including integration with third party data and customer proprietary data
Fully independent artificial intelligence with no need for day-to-day administration
- Bug rate of less than 0.3%