Client

The client is one of the largest multi-channel non-bank lenders, providing home, car, business and investment loans throughout Australia and New Zealand.

Brief

The brief was to develop a consolidation multi-entity planning model that allowed the group of companies to forecast out their near-term growth, strategy and treasury modelling.

The model suite needed to support:

• modelling of the front and back books of all business units;
• analysis of the operational growth and development of the front book;
• automated monthly historical-forecast as well as intra-month analysis;
• detailed treasury ruleset modelling to assess the funding options across the group;
• automated warehouse and SPV funding projections; and
• comprehensive three-way analysis across the different presentations of the business.

Solution

Our solution comprised of the following three models to facilitate the scale of the business, it’s data and reporting requirements:

• Data Compression file;
• Core Planning and Analysis model; and
• Reporting Book model.

The model suite was based around the following key modules:

• business channels – analysing the loan book and forecasting income down to net contribution;
• warehouses – to fund new loan generation in the first instance;
• SPVs – to bundle loans together and offer a fixed term deal funding opportunity to investors;
• Consolidated 3-way financials for a multitude of different companies within the parent; and
• A CFO-style one-pager dashboard that allows the user to flex key assumptions and perform what-if analysis in a clear and concise way.

Modano Benefits

From an end user perspective, the Modano software automated the following model development processes:

• monthly roll forward;
• adding an entire business channel;
• adding an SPV funding unit;
• creation of comprehensive board pack analysis including:
  • business channel analysis;
  • budget and prior year comparisons;
  • non-financial metric analysis; and
• intra month daily non-financial metric analysis by business channel, whereby each day, updated data could be extracted from a data warehouse, imported into the model and used to analyse within the month whether targets are being met.