In collaboration with JUMP Informatique, Loft Finance presented their client valuation model and its use in strategic client operations, as well as in optimising a company’s value. The presentation took place on the in Paris, Tue. 29th November at Rue St. Honoré. A distinguished audience of 20+ asset managers and private bankers attended.
The Client Valuation Model is designed to help private bankers and asset managers measure the potential value of a client over the lifetime of their relationship with the firm. The objective is to help investment managers make judgments about the harder-to-measure tradeoffs between clients’ costliness, risk-tolerance, and attachment to the firm. And the impact of these dimensions on the total value of the relationship.
By providing present valuations incorporating subjective factors, the models gives bankers a roadmap for time and resource allocations based on the assumptions in their framework.
The long term value of an asset management activity is largely determined by the value of its customer relationships. The value of a bank can be extracted from a customer over time. For instance, a young currently loss-making client may actually have a positive net present value (NPV) which a typical customer relationship management tool may not take into account.
The model is designed to provide a consistent, simple, robust, and repeatable structure for comparison and decision-making : a support tool for private bankers in their daily operations.
Amongst other things, the pricing of a client depends their future revenue dimensions : Assets under management , AUM (portfolio/s), cross-selling of products (from other entities in the bank), referral of new clients (net new AUM), and costs (bankers estimate on costliness of client in excess of fees on service). The model imbed other analytics. Such as ‘share of wallet’ that the bank is currently managing (the % of the client’s total assets with the bank) as or the measurement of ‘stickiness’ (the likelihood of the client to stay with the bank).
More importantly, the model demonstrates through sensitivity analyses which factors in the formula have the largest impact on the net present value of the client over the lifetime of their relationship with the bank.
For a demo, please contact us here.