Can You Insure Against Disruption?
Decreasing insurance underwriting profitability, higher combined ratios, increased customer churn, new distribution channels, and even stronger competition.
Profound changes are taking place in the insurance industry both in personal and commercial lines of business, so how do you remain relevant with all this disruption? If you are like many insurance companies, you may be facing flat market growth today, falling customer retention rates, and the need to reduce operational costs and improve profitability.
We get it.
At the same time, your company has to offer products that help you stand out from the crowd. Your customers demand a more personalized experience, even customized offerings to meet their distinct needs. Yet data proliferation makes your job harder and harder.
We transform your analytics
Saama's Insurance Analytics combine significant experience in modern data architecture design and construction with advanced insurance analytics applications. We specialize in solving business problems like churn, fraud, underwriting profitability using data science. Our insurance customers achieve a competitive edge after gaining deeper levels of real-time business and operational insights, greater market speed, and customer intimacy.
We transform your analytics
Saama's Insurance Analytics combine significant experience in modern data architecture design and construction with advanced insurance analytics applications. We specialize in solving business problems like churn and fraud, underwriting profitability using data science. Our insurance customers achieve a competitive edge after gaining deeper levels of real-time business and operational insights, greater market speed, and customer intimacy.
Insurance Solution Areas
A $35-Billion Problem
Insurance loss to fraud is significant, and growing. Yet disparate legacy claims systems abound — whether from acquisitions or internal organic growth — and have resulted in data silos that make fraud analytics and claims management difficult. This requires your enterprise to adopt a strategy to rationalize, consolidate, and migrate data to get a single source of truth.
Optimize Claims — Predict, Detect, Investigate Fraud
Saama Fraud Analytics enable better ROI on your fraud detection, prevention, and detection processes. The solution automatically adapts as fraud behavior changes and improves customer satisfaction via fast tracking clean claims.
Build A Strong Relationship With Your Connected Customer
The Insurance industry is plagued with several ‘systems of record’ with inconsistent customer data leading to audit/compliance issues, poor marketing/segmentation, and the inability to address the entire customer lifecycle. Saama’s Customer 360 solution analyzes data by quote, policy, claims, billing, payment systems and from interactions via the website from desktop and mobile devices, IVR, chat, email and even takes into account survey data such as Net Promoter Scores (NPS), Customer Satisfaction, and Brand Tracker.
A single view of your customers will lead to deeper market penetration — boosting revenue growth, and resulting in higher levels of privacy, security, and regulatory compliance.
A Complete Suite of Analytics — From Retroactive to Predictive
Agency and Distribution Management: What if you had real-time performance metrics and a dashboard that provided your agency operations with accurate agent performance stats and reduced commission leakage? The Saama Agency and Distribution Management solution enables this and more, and leads to improved agent satisfaction.
We achieve this by:
- Building a centralized data store for quote, production, loss, audit, and agent data
- Providing a platform for carriers to monitor production of business
- Assisting with an incentive program design
- Managing agent performance with a quantitative framework
Speech and Voice Analytics: Voice data not only contains valuable words and sentences that can lead to better analytics intelligence, but also contains the tone, intensity and intent of the voice. This can add up to 80 percent more in details, providing for deeper sentiment analytics.
Our solution provides the ability to ingest audio data, perform speech recognition, and then translate this into machine-readable data based on language and grammar models to perform analytics on top of it.
Our core capabilities include:
- Ability to identify the metadata of audio file/call
- Ability to conduct phonetic and linguistic analysis
- Machine learning capability to categorize the calls and identify sentiment
- Real time Search & Visualization – trends, alerts, and search capabilities
Read our White Paper on Speech Analytics.
Sentiment Analytics: Understand the sentiment of the customer by the application of natural language processing, text analytics, and computational linguistics to extract subjective information from various types of content. The automatization of sentiment analysis allows processing data that due to their volume, variety, and velocity cannot be treated efficiently by human resources.
Marketing and Campaign Analytics: Use marketing analytics, to identify your ideal customers, find more of them, and develop a smarter and more cost effective approach to marketing. Use an effective strategy to advertise, generate leads and measure the ROI on your campaigns so that you can find the customers that are just right for you.
Insurance IoT (Usage-Based Insurance)
By translating IoT signals into metrics and combining them with book of business data, companies will improve their overall business outcomes related to bottom-line, top-line, and customer engagement. As companies develop Internet of Things (IoT) business plans, they need to also plan for scalable IoT-enabled analytics to provide actionable insights and stay ahead of the competition.
Saama’s Usage-Based Insurance Program establishes the data foundation, analytics, and data services capabilities for a telematics data platform. You can use the UBI data for a better understanding of your book of business, and for developing scoring models and for pricing.
In particular, life insurance companies can reduce risks by leveraging IoT data from wearables (such as Fitbits) in their wellness programs. By combining the insights from the IoT data along with member health record data, insurance companies can reduce the early mortality risk of their customers.
Fluid Analytics℠ for Insurance
Craft Truly Unique Experiences from Contextualized Data
Saama’s Fluid Analytics for Insurance is an industry-specific orchestration environment that integrates and aggregates structured and unstructured data. Consisting of comprehensive insurance data models, categorized by subject area, the solution provides industry-standard KPIs at your fingertips. Saama’s Fluid Analytics for Insurance comes with claims and policy analytics modules already pre-built to suit your needs.
By combining data science and domain expertise, this offers a forward-looking, transformational vision of a digitally enabled insurance enterprise. For the first time, analysts, underwriters, and actuaries will have direct access to the data in native format in a self-service mode.
Driving Business Outcomes When it Matters the Most
- Drive top and bottom line improvements by better understanding your existing book of business
- Improve customer loyalty through prediction of churn leveraging data across multiple systems like policy, claims, billing
- Improve product marketing, pricing, and features by analyzing performance across agent, market, customer
- Improve risk mitigation by early detection of Sales problems and Loss trends to determine the best course of action
A large insurance company with 1000s of agencies nationwide (and 10,000+ agents) faced a number of competitive and pricing challenges: It was unable to integrate structured (survey) and unstructured (notes) data; had difficulty translating findings into actionable customer experience programs; and suffered from customer satisfaction and retention issues.
Saama helped integrate a data management platform sourcing from 15+ legacy systems; automated data ingestion, integration and integrity checks; added a role-based, secure dashboard with new KPIs, and self-service capability for end users. The solution loaded 20 years of data into the insurance model.
Better business outcomes included quicker implementation (3X compared to industry benchmarks) that led to faster time to insight and a holistic view of the customer; the potential to lift Net Promoter Scores (NPS); improve loss-ratios; and enhance customer retention and experience, and more.
Recent posts in Insurance
- Insurance: Time to get smarter with Machine learning
- Insurance takes a 360 turn for its customers
- Saama VP – Insurance, Sanjeev Kumar’s article on ‘How to Get Broader View of Customers’ featured in Insurance Thought Leadership (ITL)
- The world of Travel Insurance Fraud
- Disrupting Insurance with Advanced Analytics