Leveraging Analytics and AI for Smart Growth

When buying new portfolios, evaluating the financial health and risk profile of the potential portfolio is essential. During this process, risk assessment tools are fundamental for companies to make informed decisions.

In the equipment leasing and financing sector, due diligence is crucial for every decision taken. It is even more important when taking bigger risks, like those faced when expanding a company’s portfolio. Whether branching out to new segments of the market, or acquiring portfolios from third parties, key elements that should be considered include, but are not limited to: credit, market, and operational risks.

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‍What is Risk Assessment, and Why Does it Matter?

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Risk assessment is the process of evaluating potential events that can cause harm to a company or investor to identify how likely it is that they occur. In the equipment leasing and financing sector these hazards can put the operation at risk, causing losses, and putting a dent in the company’s bottom line. Identifying these risks is not only a good practice, but a requirement to ensure that a company is ready to deal with them and has all the necessary assets to mitigate their effects.

In this blog post, we will be evaluating the different ways in which Kin Analytics’ expertise and industry-leading risk assessment and management tools can be leveraged to minimize risks when venturing into an expansion.

It is a rule of nature, you either are big and strong, or you become the prey for those who are. However, if only size and strength mattered, us humans would not be at the top of the food chain. What is the real reason behind our success as a species? Intelligence.

Sure, size and strength provide an advantage, but none of that matters if there is no intellect.

The same applies for companies. If a company is not “smart”, it does not matter how big they are or how strong their position in the market is, in the long run they will not thrive.

For a company to be “smart”, they need to leverage knowledge as much as possible, and ensure that all of their decisions are informed ones.

This does not mean that a company should not strive to increase their size nor improve their market share. On the contrary, it means that if a company wants to prosper, they should keep growing, but be clever with their expansion.

But how does a company become smart? Well, they become data-driven and let facts and true insights guide their decisions.

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Becoming Data Driven

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(Don’t worry, we will soon be discussing risk assessment and portfolio, but first we must set the fundamentals).

Becoming a data-driven company is simple in theory, but complex in practice. From the technical aspects to those involving the company’s culture, multiple facets must be worked on and changed. How information is gathered, stored, and used; the resources available to and employed by the team, and how decision makers rely on information with confidence, are some of the aspects that need to be reviewed and improved.

It is possible to do all this work in-house, but given the option, why wouldn’t you choose to rely on a team of experts to assist you in this transformation?

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Data Driven Risk Assessment

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Okay, now you are a data-driven company. Great. You are in a better position than 74% of organizations (Bean, 2022). With this settled, we can move on to what we really want to see.

Long gone are the days of going blind into portfolio negotiations and relying on the transparency of “the other party”. Nowadays, if you are not going into these negotiations with all the information you can, you are choosing to put yourself at a disadvantage.

In this digital era, if you don’t have all the information you need, you are probably already in deep water.

Now, here's what we are here for: assessing the credit risk associated with a new expansion.

When buying an existing portfolio, you have the advantage of reviewing its performance with their current lender. However, you should not be taking their internal risk assessment at face value. Not only is it possible that their risk appetite is at least somewhat different from yours, but it is likely that their way of evaluating and managing risk is unlike your own.

On the other hand, when expanding to a new market segment by yourself, you won’t be able to do this. Don’t worry, you don’t need to venture into it blindly. Proxy data (i.e., data from other lenders provided by credit bureaus) will be your best bet.

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Expanding Through Acquisitions: Buying Existing Portfolios

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Acquiring an existing portfolio provides an incredible opportunity to build on a known track record. However, solely relying on the seller’s own risk assessment can be an expensive mistake.

To truly benefit from acquiring a portfolio, it is essential to go looking for what’s under the surface. Employing your own risk evaluation tools, leveraging advanced analytics, you can dig deeper. This involves assessing much more than just credit risk. Identifying operational challenges and evaluating potential market vulnerabilities are also part of the process that will guide your long-term success.

Let us exemplify this with a short story about “Company A”. 

‍Company A, an equipment leasing company, had been steadily growing over the years. Still, they had been searching for new opportunities to expand their portfolio. However, they did not want to take unnecessary risks.They saw a great opportunity when Company B, a company in the same sector, announced they were selling a segment of their portfolio that aligned with their current portfolio. This offered an immediate growth opportunity, but Company A wanted to ensure this was the best option for them (after all, all that glitters is not gold).

Being a data-driven organization, Company A had a bespoke credit risk assessment tool at their disposal. This tool, which relied on advanced analytics and risk profiling models allowed them to both analyze the portfolio’s general risk (i.e., its risk relative to the industry) and the portfolio’s risk relative to their own risk appetite. With this information in hand, they considered the portfolio to be aligned with their risk strategy.

After being satisfied with the portfolio’s risk, they relied on a team of experts to compare their portfolio management with Company B’s. This allowed them to identify some shortcomings and inefficiencies in Company B’s portfolio management. After gauging how they would affect their operation and costs, they were in a favorable position to negotiate a better price on the portfolio.

By leveraging advanced data analytics, they had valuable insights that allowed them to gain the upper hand in the negotiations, while protecting themselves from potential pitfalls.

They acquired the portfolio, expanding their business without compromising their risk standards.

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Venturing to Uncharted Territories: Expanding Through Proxy Data

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There are situations where expansion leads to involvement in new market segments where you don’t have historical data from your own portfolio. Also, unless you are expanding through acquisition, you won’t have performance data from a seller’s portfolio either.

Luckily, credit bureaus thought of this situation. Proxy data, i.e., data from other lenders provided by credit bureaus, is an invaluable instrument. While not as thorough as having your own internal data, this data provides critical information on the creditworthiness of potential clients from the segment. It includes data that can be analyzed to get your own insights, as well as insights from the bureau’s analyses.

Let’s return to the example of Company A.

Company A has been looking to expand to segments other than those in their current portfolio. Instead of acquiring an existing portfolio from another lender, they decided to add a new segment to their portfolio: construction equipment. Knowing that bureaus sell proxy data, they bought a sample of 10,000 leases from the past 5 years for this segment.

Using this sample, they analyzed the segment trends. They drew insights on the segment’s delinquency (i.e., how often clients from the segment fail to make their payments on time), the average size of their deals (i.e., how much money they request), as well as other key metrics they thought valuable.

Nevertheless, they knew that these superficial evaluations were not enough.

Given that their bespoke credit risk assessment tool could be used to evaluate this sample, they used it to estimate the performance and risk of this new segment. These estimates were assessed and compared to those from their current portfolio.

They found that the average risk in this segment was higher than their current average risk. However, with all the data they had they estimated how this would affect their reserves (i.e., money saved to cover expected financial losses), and determined that they would be able to offset this change while still increasing their profits. 

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Bespoke Credit Risk Assessment Tools: Your Essential Partner for Business Growth

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Throughout this blog we have mentioned bespoke credit risk assessment tools, but, what are they?

Bespoke credit risk assessment tools are solutions tailored to the specific needs and profiles of organizations. Unlike one-size-fits-all solutions, these tools are focused on the specific financial landscape and risk appetite of your organization. Because of this, they are more accurate and relevant for your needs. Using these tailored tools to evaluate creditworthiness allows businesses to make data-driven decisions, minimizing their risk exposure, and promoting a better lending strategy, fostering a sustainable growth.

Additionally, these tools evolve with your business, adapting to changes in your organization’s needs and the market conditions, ensuring that they remain relevant and effective through time.

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Kin Analytics: Empowering Your Expansion Strategy

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Kin Analytics’ bespoke tools and expertise can be leveraged to ensure a competitive edge when expanding. We enable companies to make data-driven decisions, providing them with the ins and outs of the choices they are facing. This provides a two-fold advantage: the real risk becomes apparent to the decision-makers, and with it they are in a better position to negotiate and make a final, informed decision.

Ready to embark on your journey to becoming data-driven, or looking to grow smartly? Contact us today.

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References

Bean, R. (2022). ‘Why Becoming a Data-Driven Organization Is So Hard’. Harvard Business Review. https://hbr.org/2022/02/why-becoming-a-data-driven-organization-is-so-hard