In today’s financial landscape, by harnessing the power of data, financial institutions can manage overall fund situation by determining fund transfer pricing and right interest rates. This enables informed decisions that increase profitability and customer satisfaction.

What is FTP?

The term Funds Transfer Pricing is used in banking and financial institutes to analyse their core competencies. It is a systematic method used to estimate how funds add value to a company’s overall profitability. Funds Transfer Pricing helps to accurately calculate the cost of funds required for profitability measurement, budgeting and planning and better pricing strategy.

Data driven FTP models can adapt to changing market conditions by making sure the internal pricing remains competitive. This is crucial for companies to calculate the profitability of various product lines offered and helps in analysing the performance of branch outlets and effectiveness of processes – all of which are directly proportionate to its success and profitability.

The two basic FTP methodologies are:

  • Single-rate FTP in which all assets and liabilities are assigned to a single transfer rate regardless of the nature of the product.
  • Multi-rate FTP divides assets and liabilities into further smaller groups based on various characteristics selected. With the multi-rate method, management has a better view of risks.

Charting is the most important part of all FTP methods. It’s the collection of data from available assets and liabilities. This gives companies a visual view of the link between yield to maturity and time to maturity. It can be changed or customized based on report and methodology requirements.

Data analytics plays a major role in overall fund situation by monitoring and managing it. By analysing transactional data, financial institutions can gain insights into cash flow patterns, liquidity positions and internal funding needs. And predictive analytics helps in predicting future cash flows and to proactively manage funds to avoid shortfalls and regulate surplus allocations. Analytics also allows for real time adjustments to fund allocations based on current market conditions to effectively use the available resources.

With the help of data analytics, financial institutions can track and analyse the deposit and withdrawal trends, recognise patterns and their reasons and predict periods of high liquidity demand. It helps banks to plan and maintain the right liquidity levels and meet their requirements. This prevents unnecessary borrowing costs and reduces the risk of insolvency.

Determining interest rates is a complex task and has to be a balance of needs of financial institutions and the market. Data analytics helps by providing overall insights into market trends, customer behaviour and economic indicators. By analysing large datasets, financial institutions can fix ideal interest rates that attracts customers and still be profitable.

Data analytics with competitor analysis helps financial institutions fix interest rates against competitors so they remain attractive to customers without losing on profit margins. Change in interest rates and its effects on loan demand, growth in deposits, and overall financial situation can be easily predicted with insights generated from predictive models.

Financial institutions can improve their real time decision-making, financial performance, and customer service by investing in advanced data analytics tools and methodologies. As the financial sector continues to grow, the integration of data analytics will become more critical in driving success. Learn more about how organizations like yours are working with CRG Solutions platform to drive their business forward.

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