Overview

Access to credit plays a vital role supporting consumer expenditure, which makes up around 70% of the economic activity in a modern consumer-driven economy. By just about any measurement, the modern consumer finance business can be seen as a success, but that success has come with the consequence of rising levels of consumer indebtedness.

Overview

Digital transformation (DX) is the act of leveraging technology to improve our knowledge, comprehension, decisions and actions. Within the next five years, it is widely expected that large enterprises will see the majority of their revenue driven by products and services that rely on digital technologies. Digital technologies continue to evolve. We have already seen the impact that big data, the cloud, social business and mobility are having on business. Add to that predictive and prescriptive analytics and cognitive capabilities, including machine learning (ML) and artificial intelligence (AI), and the stage is set for massive disruption over the next five years as enterprises apply digital technologies to transform their businesses. However, digital technologies all share the same DNA. This DNA consists of five core constructs: data (including events), decisioning, actions, analytics and improvements (learning). This white paper examines these five constructs but especially focuses on decisioning because of its central role in orchestrating the activities of these constructs.

Overview

IDC surveyed 500 business executives, data scientists, statisticians and senior IT staff on their use of analytics and related capabilities across their enterprises. This InfoBrief delves into how organizations are deploying “decision-centric” capabilities to help power digital transformation (DX) initiatives. In addition to analytics, the results explain the current state of rules and optimization implementations, as well as measuring how businesses that leverage all three core capabilities have a clear decision advantage over their competitors.

Overview

It’s estimated that 30 million people in the US alone have one or more debts in collections, and household debt is on the rise. Significant 90-day delinquencies come from credit cards, mortgages (plus associated lines of credit), student loans, healthcare and auto loans. While the collection industry is drawn by the significant activity of these potential revenue streams, we should recognize conflicting trends from declining collection rates, increasing regulation and growing automation.

Overview

The FICO® Decision Management Suite is a complete cloud or on-premises solution that delivers an integrated suite of tools for creating fully customizable analytically powered applications. This document provides a high-level overview of the Decision Management Suite architecture and the elements of a decision management solution. It also provides an architectural overview of the FICO® Decision Management Platform, which provides a standardized set of analytic and execution services that power the Suite.

Using this document as a guide, the reader will understand the context and boundaries to guide architectural decision-making.

Overview

Within the banking industry, marketing offers have to navigate a fine line between risk, timing and profitability. The massive proliferation of customer data, complexity of decision criteria, and shifting priorities all place a substantial burden on the decision rules system powering these offers, and any lag in performance can reduce, if not nullify, the benefit of using such a system.
 
Download our white paper now to learn how one mid-sized financial services institution deployed a decision rules system based on FICO Blaze Advisor® DRMS technology, in under two months, to:

• Proactively identify prospects for financial services and assess eligibility for inclusion in marketing campaigns.
• For each eligible prospect, select the most relevant product offer and approach through optimal channel of direct marketing.
• Process large volumes of data efficiently (leveraging Hadoop), extend timely enticements, and improve deal-close and performance metrics.

Overview

Many insurance payers realize how valuable identity resolution and link analysis technology can be in supporting detection of organized crime, as well as opportunistic fraudulent providers. But they also know how difficult it is to implement on proprietary platforms. Now, with FICO® Identity Resolution Engine as a component of FICO® Insurance Fraud Manager, healthcare insurers can immediately access the industry’s most innovative entity data matching technology to reduce losses with a more holistic view into criminal activity and networks.

Overview

When structuring a cyber insurance policy, an underwriter must understand two types of risk: the direct risk posed by the prospective policy holder’s own
actions and strategies, and the indirect risk posed by the external dependencies and fourth-party vendors of the policy holder. The latter risk assessment is as
critical as the first because entities are routinely breached through their vendors and service providers. Visibility of external dependencies must be factored into
the risk assessment of the primary policy holder in order to arrive at an accurate picture of risk exposure.

Overview

The FICO® Decision Management Suite provides an easy way for customers to evaluate, customize, deploy and scale state of-the-art analytics and decision management solutions. It allows them to quickly integrate FICO and FICO partner decision management tools and components with their own components, helping organizations of all sizes realize the promise of advanced analytics and decision management via cost-effective, scalable cloud and on-premises solutions. Decision management solutions are software services that expose predictive models, optimization models and decision rules to business processes for the purpose of automating business decisions. This white paper will explore three capabilities in Decision Management Suite and look at an insurance solution based on a real FICO customer.

Overview

The second Payment Services Directive, better known as PSD2, is set to change the payments landscape, and Payment Service Providers (PSPs) will have to change with it. Those that implement PSD2 well are likely to retain existing customers and attract new ones.

In this white paper, we focus on the changes that will affect the fraud operations of PSPs, such as retail banks and card issuers. And we take a look at the role machine learning can play in helping them make the most of their adoption of PSD2 standards.