International Institute for Analytics

Inquiry:

We recently launched a new talent management system and are working to define job descriptions for data analysts, data scientists, and data engineers. We’re struggling with mapping existing roles to new roles and ensuring we’re on the right track with necessary change management that goes with this. Could you help us think through this?

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.

A recurring theme among analytics and data science leaders is the concern of not being able to keep up with all of the rapid change taking place – both individually and as a team. In years past, it was possible to stand up an organization largely made up of analytics generalists who would handle initiatives end to end. In today’s world, it is necessary to utilize a range of specialists focused on either specific methods or specific points in the lifecycle of an analytics and data science initiative. This talk will discuss the trends driving the need to evolve your organization’s talent model, new roles you need to consider implementing, and how they all fit together.

Inquiry:

We supply propensity models to the marketing team to help predict customer behavior for our various brands. Beyond this, what can our analytics team be doing to support them?

Inquiry:

We’re developing a customer data platform and are challenged by the wide variety of ways our customers interact with us. How are other organizations trying to solve this problem?

Response:

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.

Inquiry:

We are relying more and more on digital B2B2C to reach our consumers. As we ramp up e-commerce, how can we apply analytics and what kind of investment should we make? What did you do in your company?

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.

Inquiry:

We’re new to HR analytics. What kind of projects should we look to tackle to show some initial wins?

Inquiry:

How can we measure the lift from coupons used and what’s the best way to deploy the models to do it? We know we have lift coming in from various combinations of promotions, but we need a more granular view. Unfortunately, we don’t have access to web data, although we can track the coupons used in our brick-and-mortar stores. What do you think?