A Roadmap for Hyper-Personalized Lending

In a previous blog “Are credits not too commoditized?” in February 2020, we already raised the concern that loans in general and mortgages in particular have become too much of a commodity product, for which price is nearly the only differentiator. Many customers are however unaware that the loan with the best price or interest rate may not necessarily be the best option for their specific situation.

Credit factors that influence customers decisions

It is therefore surprising that banks (both incumbents and neobanks) are not offering more options and insights to their customers to differentiate between different lending products. Obviously price is a very important factor, but there are dozens of other factors that contribute towards a final decisionfor example :

  • The loan duration
  • The reimbursement modeie installment, balloon (first pay only interests and only start reimbursing principal after that period), bullet (payment of principal of loan and interests at maturity or interest-only loan), etc.
  • Associated insuranceslike outstanding balance insurance or fire/theft insurance on the underlying asset (house)
  • The interest rate scheme, ie fixed vs. variable (ie adjustable-rate mortgages = ARM) and different possibilities when going for variable interest rate (like frequency of rate revision, min/max caps, ie capped rate mortgages, etc.​)
  • The contractual penalties to renegotiate a loan or to perform an (partial) early reimbursement or overpayment
  • Possibility to overpay / underpay on a monthly basis
  • Possibility to shorten / extend your loan during its lifecycle
  • Possibility to pause reimbursements at certain moments (payment holidays)
  • Possibility to get subsides from government instances
  • The required collaterals of the loanie :

    • Only the home itself or additional guarantees/collaterals requested
    • Mortgage on the collateral and/or mandate to the bank to initiate a mortgage upon need (or combination of both)
    • Potential backing by government agencies
    • The required down payments

  • Possibility and costs associated to remortgagingie reuse an available mortgage
  • Possibility to transfer Your existing home loan to another house

Additionally banks can differentiate their service based on :

  • The loan acceptance criteria, ie for people having difficulties to obtain a loan, the acceptance criteria (like LTV and DTI) can be crucial. In this credit scoring domain, one can see a lot of evolutions in using alternative data sources like Open Banking data
  • The speed at which a loan demand can be initiated. This speed can be increased by maximum pre-filling (from previous demands, digital identity providers, social media, PSD2/Open Banking​), data analytics and AI, and the possibility to upload documents which are automatically OCRed and analyzed
  • The speed at which a loan can be closed with possibilities to request a loan fully online 24/7, with digital signing, digital communication with notaries, automated decision taking, etc. This allows to reduce the average time to apply for a mortgage from a few weeks to a few days, drastically improving the customer experience

Tooling for customers to choose between differentiating options

Many banks offer several of these differentiation options, but it is rare that these are clearly marketed and properly explained to customers. We feel there is a lack of easy simulators and digital guidance (like wizards/questionnaires) to determine the best (read “cheapest” over its entire loan life cycle) loan for the customer’s specific forecast situation today and for the future. Via tooling with an excellent user experience, the above choices will become more important commercial differentiators towards customers, ultimately resulting in hyper-personalized lending.

So far the evolution in this space has been limited, although there are some interesting evolutions of Fintechs trying to introduce new concepts, for example:

  • Spree: a UK based Fintech trying to assist customers in managing mortgage overpayments, ie by overpaying at the right moment and with the right amount customers can save a lot of money
  • Perenna: a UK based Fintech offering innovative long-term fixed-price mortgages with very competitive transfer and early reimbursement options
  • Loan comparators: different Fintechs are offering options to compare loans of different banks, offering also different types of questionnaires/wizards, simulators and automatic onboarding options, for example Holo (UAE start-up), Mojo Mortgages, Helderlenen.be, TopCompare, Spaargids.be , Trussle, Independer.nl​
  • Lender Price: offering a real-time mortgage pricing engine, based on AI and competitor analysis to offer a personalized and competitive pricing in real-time
  • Capilever: a Belgian start-up offering new tooling to make lending simpler, like the FINE product to direct the user to the right lending product via simple and configurable questionnaires, wizards and simulators, or the IRCT tool allowing to compare loans with different durations and interest rate schemes, allowing to simulate different scenarios for benchmark interest and inflation rates

Clearly interesting evolutions are on the way but focus for now seems mainly on the automation and digitalization of the origination and decision-making processes for mortgages. Once this will become more mature, we can expect more focus on offering more flexibility in the servicing of credits and higher personalization of mortgages. Therefore we believe a good preparation of this 2nd step of credit innovation should be started today.

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