Research

LDTI Should Spell Opportunity

By Naxine Chang, Robert Morison, Mar 24, 2021

Complying with the Long-Duration Targeted Improvements standard presents major challenges to the business processes and information systems of insurance companies. At the same time, it offers them the opportunity to make rapid progress in modernizing those processes and systems to deliver management insight of unprecedented value. To explore the two sides of the LDTI coin, IIA interviewed Naxine Chang, FSA, MAAA, North America Insurance Strategy Head at SAS Institute.

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Inquiry Response: Service Health Model Monitoring and Effectiveness

By IIA Expert, Mar 15, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We want to get proactive about predicting service health and correcting customer issues. We’re struggling with growing pains when it comes to model monitoring and effectiveness. How have you seen this done?

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Fighting Money Laundering with Intelligent Automation

By Christopher Ghenne, Beth Herron, David Stewart, Robert Morison, Feb 08, 2021

The world of money laundering and other financial crimes – and they do span the globe – continues to reshape rapidly. The amount of money laundered is estimated at between 2 and 5 percent of global GDP. The midpoint of that range has over $3 trillion in illicit funds moving annually through the financial services industry. That’s several million dollars a minute. If the money laundering “industry” were a country, it would have the fourth or fifth largest GDP in the world…Today, continuous and sometimes radical improvement has become a business imperative. Institutions must rethink and accelerate their processes, become both more efficient and more nimble, and react faster to the changing schemes of financial crime.

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Value and Opportunity: An Executive Guide to Procurement Integrity

By JEN DUNHAM, Laurent Colombant, Robert Morison, Jan 13, 2021

Procurement Integrity (PI) represents a broader problem and bigger opportunity than most businesses recognize. Comprehensive PI programs continuously validate purchasing transactions, using data and analytics to trace patterns, spot anomalies, and reduce fraud, waste, and abuse. The problems uncovered range from occasional opportunistic fraud to ongoing organized fraud, from duplicate invoices and other improper payments to regular kickbacks, from conflicts of interest to ongoing collusion with suppliers. Continuous monitoring of anomalies in procurement and supplier due diligence processes reveal potential problems, including data issues and process breaches, and help focus the efforts of audit and other investigative staff.

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Inquiry Response: Safeguards For Frequently Retrained Models In Production

By IIA Expert, Jan 04, 2021

Available to Research & Advisory Network Clients Only

Inquiry:

We deploy an automated, predictive service prioritization model every week, training on the past four months data and refreshing the previous week’s data (subtracting the oldest week). Is this frequency justified? Also, what safeguards should we have in place?

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Inquiry Response: Moderating A Discussion On Innovation in Analytics

By IIA Expert, Kathleen Maley, Nov 23, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

I’ve been invited to moderate a discussion with leadership on innovation in analytics. I want to make sure I’m well prepared. What would you be thinking about if you were me?

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Inquiry Response: A/B Testing For Mobile Applications

By IIA Expert, Casey Rosenthal, Oct 12, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

How do other companies perform A/B testing at scale for their mobile apps? We’d like to work on optimizing user experience performance.

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Inquiry Response: Maturing Beyond Outlier-Based Fraud Detection

By IIA Expert, Oct 12, 2020

Available to Research & Advisory Network Clients Only

Inquiry:

We’re exploring ways to mature our fraud detection models. At the moment we rely on outlier-based detection, but we don’t have a ton of label data. How can we advance our outlier testing until we generate enough labels to build ML models? What else might you suggest?

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A Framework For Establishing A Self-Service Program

By Doug Mirsky, Drew Smith, Aug 31, 2020

Available to Research & Advisory Network Clients Only

As with many terms in the analytics space, “self-service” tends to have many meanings, depending on the vendor using the term. Self-service is used to describe both business intelligence and (advanced) analytics, and is frequently co-mingled with a number of other terms, including “data democratization,” “citizen data scientist” and, more recently, “data literacy.”

In general, this collection of terms points in the direction of a conscious strategy to have more employees in an organization, with broader and deeper access to data, use those data sets to make better, more timely data-driven decisions with little or no intervention from a centralized BI or analytics function, or IT professionals.

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Fusion Centers: Evolving Roles, Expanding Capabilities,  Continuing Challenges

By Juan Colon, John Gillon, Gretchen Stewart, Robert Morison, Aug 24, 2020

Fusion centers have evolved far beyond their original role in counter-terrorism to safeguarding and serving the public on many fronts. They continue to evolve rapidly as they opportunistically and, in the COVID-19 pandemic, necessarily make their operations more virtual. The core challenges are also changing, but they still revolve around the three imperatives of integrating data, deploying technology, and building trust. Three experts – Juan Colon, National Director of Opioids and Illegal Drug Solutions, SAS Institute, John Gillon, Industry Expert, Public Security, SAS Institute, and Gretchen Stewart, Public Sector Data Science Director, Intel Corporation – share their experience and perspectives on how fusion centers succeed in their missions today and tomorrow.

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