Open Framework, Information Management Strategy & Collaborative Governance | Data & Social Methodology - MIKE2.0 Methodology
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Being a Leader in Consumer Lending

From MIKE2.0 Methodology

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This article is a stub. It is currently undergoing major changes as it is in the very early stages of development and is only a placeholder. Please help improve MIKE2.0 by adding to this article.

In order to increase revenues and decrease impairments, organisations that aim to be leaders in Consumer Lending want to make fast, reliable, integrated and consistent decisions. For unsecured loans they want these to be automated as much as possible. For secured loans such as home loans, organisations are also looking to automate decisioning, although their first priority is to improve the efficiency of their manual processes and minimise errors related to data re-keying. They are also looking to integrate the business and ensure they are making fact-based decisions on their data.

This means that organisations are aiming to have marketing and fraud more closely integrated with their credit decisioning processes. Beyond doing things better (new capabilities, higher quality) and faster, they also want to do things more cheaply. Therefore, improving operational efficiency is a major goal of most organisations. The key to all of this is better management of information.

Contents

An Overview on the Business Solution

Definition of the Solution Area

Impacted Industries

Why this Solution Requires an Information Development Approach

Typical High Level Business Requirements

Project Delivery using MIKE2.0

Key Components Required from SAFE Architecture

Applicable Activities from the MIKE2.0 Methodology

Best Practices for Implementation

Areas of Complexity

Applicable Software Solutions

One of the leading international providers of payment systems is ACI Worldwide (Nasdaq: ACIW). Their product is ACI Proactive Risk Management 8.0 (PRM) and it provides data mining to work with the bank's customer preferences to help determine whether to authorize transactions.

As the last step in an authorization process, systems like PRM share a score with the bank based on a tolerance score the bank has set for the customer and the bank systems decide whether to authorize the transaction or not. They use a profile of customer transactions, a set of rules around certain transactions (i.e., taking out the daily maximum one minute before midnight) and analytics.

To accomplish this, PRM needs all customer transactions. PRM is plugged into bank systems and learns when it has been wrong and tunes accordingly.  

Companies like PRM can also share fraud patterns across their entire network so banks effectively learn from each other.  

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