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mentor – Make the Most of Your Data

mentor is an innovative KPI platform evaluating existing trading data in real time and in a structured way. In combination with historical negotiation data, new matchings are created. By using a minimum amount of resources and a target-oriented use of your transaction data, mentor can assist with generating additional business. Simply specify the necessary targets for your business and check the results, for example, new trading suggestions directly via mentor.


Table of contents

mentor Offers Two Smart Modules

+ 5000000

Data as basis for analysis

+ 10000

Different formats of key indicators


KPI calculation

Use cases

Use case 1: How to assess the revenue with a certain client?

“My objective is to increase the proportional customer revenue. For this, I need an appropriate reference value.”

The customer revenue can be determined by calculation of typical Key Performance Indicators (KPI). Moreover, a more detailed analysis of the bank’s proportional revenue in relation to the overall customer revenue is possible. In the end, these are two strong indicators with high significance.

The mentor indicator platform parametrises these indicators and enriches them with additional data such as, for example, asset classes or time intervals. With comprehensive filter options, individual KPIs with even higher informational value can be created. The results are shown via dashboards in a modern web front-end whereby real-time information as well as context-related information, e.g. via customer requests, is updated automatically.


  • High significance via KPIs
  • Real-time calculation
  • Easy comprehension with visual display

Use case 2: What has the client traded in my account book?

“I have a position for a specific bond and would like to know which customer might be interested in this bond.”

The mentor indicator platform offers a database which can be filtered by a variety of data and structures, e.g. by an instrument book, and thus the top customers for the selected instrument/bond are displayed. The interest is displayed in tabular and graphic form so that the customer having the greatest interest in the position can quickly be identified.


  • Navigation through historical negotiation data in the mentor database
  • Easy and fast handling
  • Real-time integration of new negotiation data

Use case 3: Is it possible to compare matchings?

“I have a customer interest for a specific bond and would like to know whether a countertrade is possible.”

In addition to all concluded transactions, mentor also analyses interests and requests which have not been traded yet. Within the database it is always possible to set filters for interests to any specific financial instruments. mentor compares all kinds of positions: banks’ inhouse axes, customer interests or customer positions from historical negotiations. All datasets are reconciled in a structured way based on parametrisable similarities. Any matchings are reported to the interested party in real time. In this way, the trade for the customer’s original interest can be mediated and the countertrade can be concluded at the same time.


  • Similar opposite matchings from own and other interests
  • Consideration of historical negotiation data
  • Real-time notification regarding new matchings

Use case 4: What about the provision of alternatives?

“I have a customer interest which does not match any other interest. Are alternatives proposed too?” 

The mentor matching platform provides the possibility to filter suitable alternatives for an interest on the basis of defined similarities such as sector, issuer or term buckets. Like this, the customer receives different alternatives for the case that the direct matching – whether an own or other matching – is not suitable.


  • Alternatives filter
  • Real-time notification about alternatives
  • Consideration of historical negotiation data
Real-time report in web application
Open architecture
Automated processes

Perfect Connection to valantic’s mentor

mentor functions as advisor for customer interests and delivers real-time notifications regarding potential matchings. The input of customer interests can be carried out in different automated ways, e.g. via valantic’s icProfit. The modern and open architecture delivers an open standard API from the very start so that customer interests and axes can be delivered to mentor via third-party software such as Refinitiv’s Eikon, Excel or Bloomberg.

Illustration of how mentor works, valantic functionality of mentor

Chart for matching and administration of interests as well as transfer to downstream trading systems

Your Benefits at a Glance

Real-time visualisation and evaluation of pre- and post-transaction data
Management and matching of customer interests
More business and increased turnover thanks to better customer offers
Reduced risk for tier2 and tier3 requests
Simple and fast connection to data sources
Open API for data import
Integration into valantic workflows and automated processes
Flexible technical implementation (in your system landscape or in the cloud) and support possibilities
Increase in revenue by up to 15%

Added Value for Everyone


Traders can at first sight recognise which financial instruments are currently in high demand and which not. The trader also receives information about the present customer relationships.


Sales employees have an overview of how the customer relationship develops and how the previous customer strategy works. mentor helps to support more customers with less effort.


Business analysts can use the prepared datasets for analyses and concept proposals. Thus, key performance indicators can be better evaluated and new trading strategies can be developed.

Your Contact

Mathias Schmidt

Mathias Schmidt

Product Owner
valantic Financial Services Automation