How does our recommendation engine work?
Hypofriend's proprietary algorithm will identify the most optimal fixed interest period, repayment pattern and optimal down payment given a user's profile and preferences.
It does so by minimizing the lowest total expected cost given the user's expected stay, the possible cost of leaving earlier and the possible cost of staying longer with respect to possible pre-payment penalties & rising interest rates. The advice is influenced by the customers age, income growth and preferences for investment alternatives or renting the property in case of earlier than expected departure. This engine serves as the basis for understanding how to make better mortgage decisions.
Many clients will be falsely lured into finding a product that only has the lowest interest rate. Unfortunately, getting the best rate on the wrong product can leave customers extremely exposed down the road. Most advisors in Germany do not take future interest rate projections, the clients income outlook nor their future plans into account.
Hypofriend's algorithm was developed by Dr. Christian Mulder after working at the IMF & World Bank where he advised countries on the investment and management of trillions of Euros worth of assets. He led a team developing an innovative system to help optimize their debt management that is now used in over 60 countries. Many of the insights from that work have been employed in the Hypofriend's algorithms. Christian holds a PhD from the London School of Economics and has many academic publications to his name.
To find the right mortgage given your situation, start here.