Personalised pricing in a digital world

Digital transformation is a high priority among lenders, especially as the sector moves towards personalised pricing. But there are challenges, particularly around customer experiences, data and AI, and understanding the competition.

Giving customers the experience they want

Today’s customers expect more from their lenders. They want a fast, efficient process and expect to be offered a digital option, even when dealing with complex transactions. COVID-19 has also made customers more comfortable about transacting online, and surveys show they’re becoming increasingly dissatisfied when the process and offerings are not personalised.

However, simply moving a physical process to a digital environment doesn’t work. Imagine trying to replicate an eight-page car loan application online. If organisations don’t adapt, new fintechs will fill the gap. For example, Athena Home Loans can approve an online home loan application in fifteen minutes.

What’s required is an online experience that is simple, easy and intuitive enough for customers to work through. It also needs to have the appropriate tools to educate and coach them when help is needed.

Improve data quality

While once customers were cautious about sharing their personal data with insurers and banks, they are now willing if they believe there is value to them of doing so, such as receiving personalised pricing, products and services. The challenge here is that lenders have a lot of customer data in their legacy systems, but they’re not using it effectively: it’s in silos, unstructured, and not enriched with external data sources, and this makes it difficult to personalise.

To improve data quality, it’s important to pay attention to your data architecture and processes. Data needs to be enriched, and in the right format so you can use it to enhance your personalisation efforts.

Know your competition

There are many new organisations – particularly fintechs – entering the lending space, offering competitive pricing and products that make online price shopping faster and easier. It’s critical to understand the customer-acquisition strategies of these competitors and to use that information to help develop your own pricing strategy.

A major challenge is that the online lending sector is not yet mature. This makes it difficult to go online and search customer profiles to get prices for specific lending products for use in your pricing strategies. However, this is likely to change as banks boost their digital capabilities.

How to provide personalised pricing

When building personalised pricing models, you need the appropriate data architecture so you can make the most efficient use of the AI and machine-learning models that are available. Having enriched data means you gain a better understanding of your customers, which helps you to personalise their price offers.

Once your data is in good shape, you then need to work out the internal costs associated with each particular customer. It’s critical to build your models around these internal costs so you can attribute them to specific customers and then combine this data with customer data to start offering personalised pricing.

The next stage involves understanding your customers’ elasticity. This is important because if you put a technical price into the marketplace, you don't know whether the customer's going to purchase at that technical price, so an understanding of whether the price that you set will be attractive to your customers is critical to drive conversion. Therefore, price testing on a portion of your portfolio is recommended.

As your customers’ elasticity changes every month, it’s important to continue to invest appropriate resources in ensuring you have the best data, the right people and the most efficient processes. Then you can include intelligence on what your competitors are doing to help you to assess your product price points for certain demographics.

Following these procedures will help you get to the point where you convert every customer that you put a price to, or target the customers that you want to have on your books.

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Combining 30+ years’ experience in banking and finance with our deep capability we have helped hundreds of business leaders navigate complex challenges and bring clarity to their decision making. Heavily underpinned by data science and analytics, our advice is end-to-end from data governance to policy, process and implementation to ensure you extract the maximum value from your data assets to meet your evolving customer needs and thrive in a rapidly changing industry.