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Posts Tagged: Business Intelligence
Eliminating Waste in Auto Claims

Eliminating Waste in Auto Claims

This is the final entry in a set of three posts – you can see the first on Reducing the cost of manual claims handling here and the second on Fast-tracking disability claims here. Each post is a real-world story that illustrates the importance of handling your claims...

Fast-tracking Disability Claims

Fast-tracking Disability Claims

This is the second in a set of three posts – you can see the first on Reducing the cost of manual claims handling here. The series is designed to use specific real-world stories to illustrate the importance of handling your claims effectively, not just efficiently....

Reducing the cost of Manual Claims Handling

Reducing the cost of Manual Claims Handling

Our CTO, Ryan Trollip, recently gave a webinar on claims automation with our partner Red Hat. Many companies spend heavily automating their claims process, but this spend is largely on handling a claim efficiently not on claims handling effectiveness. Digitizing...

Claims 2030

Claims 2030

COVID-19 accelerated the need for next-generation claims-processing goals. To make these capabilities a reality and create long-term value, insurers should focus on five key areas.

Managing AI Decision-Making Part 3: Human on the Loop

Managing AI Decision-Making Part 3: Human on the Loop

Continuing our series on AI management options (kicked off by the HBR article Managing AI Decision-Making Tools), the next option is Human on the Loop (HOTL). HOTL systems are most common in situations there is a need for 100% straight through or automated processing...

Machine Learning, Trust and Stephen Covey

Machine Learning, Trust and Stephen Covey

Trust is a big deal when it comes to machine learning. “Black box” algorithms, concerns about bias and a sense that data scientists may know everything about the data but nothing about the business all undermine trust in machine learning models. Indeed, building...

Algorithms and Regulations: Tips for Success

Algorithms and Regulations: Tips for Success

Cathy O’Neill wrote an interesting piece on regulating automated decision making recently. I am not going to argue about whether use of algorithms should or should not be regulated because I think it is inevitable that they will be. The question is how companies...

Using Technology to Reduce Operating Costs in Insurance

Using Technology to Reduce Operating Costs in Insurance

In February, we published a blog post on “Using Technology to Add Value in Insurance”. That post, referenced Matt Josefowticz’s article – Technology May be the Answer for Insurers, but What Was the Question?, in which he states that there are only three levers of...

Using Technology to Better Manage Risk in Insurance

Using Technology to Better Manage Risk in Insurance

In February, we published a blog post on “Using Technology to Add Value in Insurance”. In that post, I referenced Matt Josefowticz’s article – Technology May be the Answer for Insurers, but What Was the Question?, in which he states there are only three levers of...

Using Technology to Grow Relationship Value in Insurance

Using Technology to Grow Relationship Value in Insurance

In February, we published a blog post on “Using Technology to Add Value in Insurance.” In that post, I referenced Matt Josefowticz’s recent article – Technology May be the Answer for Insurers, but What Was the Question?, in which he argues that there are only three...

What is an Acceptable Analytic Failure?

What is an Acceptable Analytic Failure?

Many speakers on predictive analytics, machine learning (ML) and AI talk about the need to allow data science teams to fail. Without failure, without a willingness to fail sometimes, it’s very hard to build a successful data science program. This is true and often a barrier for companies that find it hard to accept that not all analytics initiatives succeed.

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