Collateral coverage

Already calculating collateral coverage? Here is how you can segment your portfolio and optimize your profitability

We have all dealt with the concept of collateral coverage, one way or another. For instance, I have to leave my ID card at a gas station if I accidentally forget my wallet at home. Believing that things will turn out OK is terrific, but it would be wise to ensure everybody meets their obligations and, in the end, it is essential that we all get what we wanted in the first place.

However, the only thing banks worldwide actually do is collateral management. Although many are most likely not aware of it, collateral is essential to a bank’s business. So, it is only natural that everyone involved in the process has a few questions about it:

  • Sales manager: “What is the lowest interest rate I can offer to this client? “
  • Risk manager: “How can I improve my portfolio collateral coverage?”
  • CEO: “How come my collateralization ratio is so low?”
  • Client: “What type of securitization should I offer to the bank to get the money? The Stock exchange market is doing so well nowadays; let’s try this. Or maybe an old little house I have in the mountain. I cannot sell it, but it’s worth something according to the real estate market, and maybe the bank has to take it as security.”
  • Regulator:” Those banks are probably cheating when lending the money. How can we find out what is the actual market value of their collaterals? Also, how much money they ought to have “in every moment” to keep their business go on regardless of climate changes, covid-19 expansion, the stock market in New York, etc.?”

 

How do banks calculate collateral coverage?

When you talk to your client as a bank manager, you are more than happy to offer the lowest interest rate for their new loan thanks to a calculated collateral coverage value (hopefully 100%) prompting on your screen. This could help you become a rising star if the criteria of success in your branch is presenting your loans portfolio from a collateral coverage perspective.

But how do you get there? The perfect algorithm for calculating collateral coverage is worthless without a proper collateral management process in place. And, what makes a collateral management process good, is having clear and unified business definitions and rules for empowering it. Moreover, a solid and coherent process ensures you deal with good collateral data, which further leads to data knowledge that allows data science to perform at its best and helps you really end up with solid and actionable information on how to deal with your clients.

 

collateral coverage

Get ready for data preparation

If you work in the banking industry, you must have heard these questions before:

  • How much data (on different matters) should we collect to have a meaningful statistical model and rationale?
  • What is the value of the collateral? Be aware that there is more than one collateral value, depending on what role you are in.
  • What is the “cushion” for potential losses? Meaning something providing support or protection against impact.

 

Here are few suggestions:

1. Proper data management

Listen to all the requests your statisticians and your regulators have. Don’t hesitate to ask your client every question which crosses the risk manager’s mind. All the clients want is money, and before you lend them a loan, they are prepared to give you all the information you need.

2. Collateral value

It is hard to determine the market value of collateral in the case of real estate or movables. Also, it is hard to decide if the guarantor’s rating is sufficient to take his guarantee as securitization or decide on the proper collateral value of securities on stock markets worldwide.

On top of that, the national bank has its saying, called EU directive 575/2013, on the minimum value of regulatory capital. This EU law aims to decrease the likelihood of banks going insolvent.

The Capital Requirement Regulation (CRR) 2013 reflects Basel III rules on capital measurement and capital standards. And now and then, banks have to prove to everybody that their capital is sufficient to cover losses in drastic economic scenarios over the long run. That is also known as a stress test.

To prepare your data properly, your collateral database and your losses database should be modeled to easily divide collateral market value at a given point of time and recover the amount (received an amount from selling specific collateral). We are talking about the Collateral Recovery Ratio (CRR) on a single collateral level and the valuation rate for each collateral type (calculated CRR on collateral type level).

3. Protection

Protection is performed when the valuation rate (calculated from your historical data) is applied to the market values of your whole collateral portfolio. In the end, this is the value you use for covering approved loans. It represents acceptable value by all means, including the risk that you will not be able to sell your instrument within a reasonable time and get a fair price for it.

 

Deciding on collateral coverage type and segmenting your portfolio

You need to decide what type of collateral coverage you want to measure. Is it for provisioning, capital adequacy, or are you simply guessing the future? Once you have decided what exactly is that you are doing, take a deep dive into your collateral database and segment your portfolio. Do it in such a way that each collateral covers just the perfect match of your clients, their loans, and your business rules.

You want pools, and you want to cover those pools with the blankets wide enough and strong enough that you have almost nothing uncovered.

In that respect, Banking DWH model can help you:

  • choose the proper segmentation,
  • sequence your collaterals for optimized collateral coverage
  • order you collateral records
  • apply calculation algorithms
  • prepare calculated data for business inquires

 

Do you want to know more about collateral coverage or data warehouse? Let our expert team help you!

Simplify the way you gather data, have a single point of truth and ensure data quality, consistency, accuracy, complexity and the right timing.

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Collateral coverage

Already calculating collateral coverage? Here is how you can segment your portfolio and optimize your profitability

We have all dealt with the concept of collateral coverage, one way or another. For instance, I have to leave my ID card at a gas station if I accidentally forget my wallet at home. Believing that things will turn out OK is terrific, but it would be wise to ensure everybody meets their obligations and, in the end, it is essential that we all get what we wanted in the first place.

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Collateral coverage

Already calculating collateral coverage? Here is how you can segment your portfolio and optimize your profitability

We have all dealt with the concept of collateral coverage, one way or another. For instance, I have to leave my ID card at a gas station if I accidentally forget my wallet at home. Believing that things will turn out OK is terrific, but it would be wise to ensure everybody meets their obligations and, in the end, it is essential that we all get what we wanted in the first place.

> Read More
Data Democratization starts with Data Governance

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There is no consensus of where the data democratization process begins and where it ends. It is a complex strategy with many proposed steps for data democratization to drive businesses. Each and every organization is unique and should define its own democratization steps according to its own needs, challenges, risks.

> Read More
Data democratization

Data democratization | Why is it Important for Your Business in 2021

In a world lead by data, an enormous amount of data is getting generated every second. We know by now that a data warehouse adds a significant value to an enterprise, helping to improve decision-making processes, but what about access to the raw data? By implementing data democratization, you enable everybody in the organization to take advantage of data-informed decisions.

> Read More
event driven economy

Data Analytics in Event-Driven Economy 

World and business are changing rapidly, and analytics is changing too. I will not talk about technical terms that are very popular now – Data Lakes, unstructured data, real-time analytics, Data Science, artificial intelligence, and other nice things everyone is talking about in the last few years. Instead, I would like to emphasize the change from a process-driven economy to an event-driven economy and what it brings to the analytical landscape.

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