SPSS Analytics Partner | Fraud, Risk & Claims

Fraud, Risk & Claims

Webinar: Turning Your Insurance Digital into Gold through Advanced Analytics

You are sitting on a huge amount of data but are you getting any new information from it? Join us on the 15th of March to see how you can leverage all your existing and new data that is now flowing through your organisation.

The Chief Data Officer playbook

Creating a game plan to sharpen your digital edge - Tailoring the CDO Role

Webinar: Predictive Analytics in Insurance

Watch this recorded webinar where our two outstanding speakers Tony Boobier and Dr. Claire Jordan shared their experience and success stories in delivering analytics solutions in insurance.

Case Study: Insurance Bureau of Canada

Outsmarting fraudsters with fraud analytics – IBC protects honest policyholders by detecting and prosecuting organized insurance fraud.

Infographic: Detecting Fraud using Predictive Analytics

Corporate failures from fraud result in massive losses to shareholders. Poor risk management capabilities lead to poor decision making and high costsm, and organizations throughout many industries struggle to comply with escalating regulations. In this environment, risk, fraud and compliance management must be pervasive throughout your organization’s culture and operating model. Leverage Big Data & Analytics to gain a holistic view of risk, fraud and compliance information across your organization.

Infographic: 3 Ways to Improve Claims Management with Business Analytics

Filing a claim is the single most important part in the relationship between insurers and the insured. It lays the foundation for customer satisfaction, profitability and positive word-of-mouth for attracting new customers. A “one size fits all” approach to decision-making won't be successful - rather adjustments to the circumstances and needs of individual cases are required.

Case Study: Bancolombia

Bancolombia strengthens anti-money-laundering capabilities with Predictive Analytics

Case Study – OTP Bank

Statistical modeling used to identify hidden predictors in loan applications, reduce defaults and increase capital reserves

Case Study – Adira Finance

Predictive analytics used to more effectively manage credit risk and tailor loan offers

Case Study – Santam Insurance

Using IBM SPSS predictive analytics to identify risks and accelerate claims settlement