The struggle that banks face in combating credit risks is multi-dimensional. Foremost among them is determining the right capital allocation and pricing for different sources of their revenue. These include the bank’s loan commitments, revolving lines of credit (which have no maturity), secured vs unsecured lending, and so on. Balancing the risk and profitability of each transaction is also an area of opportunity to optimize. Banks need to be more prudent than ever, and reliant on advanced technologies in order to maintain asset quality, ensure profitability and deliver a competitive market performance.
It goes without saying that good credit management practices are bound to have a resounding impact on the financial health of banks. For decades,, RAROC (Risk Adjusted Return on Capital) and EVA (Economic Value Added) have been globally acknowledged as two of the foremost banking performance evaluators and profitability-measurement frameworks, by way of promoting efficient capital allocation and risk management practices. RAROC, especially, has a key role to play in bolstering the profitability by factoring in the risk quotient of a project or business unit.
In good science, Central Banks across the globe, in line with the guidelines set by the Basel Committee, have been advising that banks adopt a pricing mechanism that computes in RAROC, to temper their risk exposure levels. However, the lack of a standardized methodology for accurate RAROC computation is of concern today and continues to plague credit pricing, especially on the corporate lending side.
As a FinTech specialist and pioneer in financial risk management solutions, BCT Digital, a division of Bahwan CyberTek (BCT) helps banks and financial institutions mitigate risk and safeguard operations through its flagship product suite rt360. Built by bankers-turned-solution-architects, rt360’s powerful risk-based pricing solution combines state-of-the-art technology with deep risk management domain expertise to arrive at a profitable yet compelling credit pricing for banks and their customers.
The tool can aid bankers with information on three mission-critical fronts:
- Pricing: Arriving at the ideal loan pricing and interest mark-up based on the risk-quotient of a loan seeker, weighed against the optimum RAROC threshold set by the bank
- Credit decisions: Determining the feasibility of loan applications by taking into account the loan seeker’s overall credit rating, transactional history with the bank, as well as other key parameters related to loan purpose and facility. Ability to accept or reject the application by gauging the overall risk vs profitability
- Collateral coverage: Analytics to decide on the appropriate collateral or guarantee cover for risk mitigation, once the credit-worthiness of the loan seeker has been established
- Comparability: Getting a 360-degree view of the customer’s engagement with the bank, comparing customer portfolios, profiles, credit worthiness and operational scenarios leading up to lending decisions
A real-world example
Relationship managers routinely connect with commercial loan seekers to discuss loan requirements. The information gathered during the discussion should ideally enable a manager to decide upon the feasibility of a credit deal and arrive at a rational pricing quote.
However, the challenge is the time delay in arriving at an optimal pricing on the fly. This often leads to undesirable pricing trade-offs, with quotes that are at times on the higher end (resulting in the loss of a customer) or lower-than-optimal pricing (leading to revenue leakage on the part of the bank).
The rt360 risk-based pricing solution is a web-based tool that formally computes the optimal pricing or lending rate by leveraging sophisticated algorithms incorporating complex credit risk parameters. Its powerful computation engine and mobile-responsive design make it an ideal tool for bankers on the go. The solution essentially feeds off simple data input, and extensively functions in the background to provide accurate, on-the-spot credit pricing.
Working with the rt360 risk-based pricing solution is a simple, three-step process:
- Data ingestion: Bankers feed inputs like customer/facility data, utilization, pricing, rating and security into a user-friendly web page.
- Computation: rt360’s powerful engine computes risk-weighted assets, capital and risk-adjusted returns.
- Presentation: Usable information, including the RAROC percentage, is displayed along with customizable dashboards and reports — like customer-wise profitability reports, growth reports and more — segregated as per user rights, roles and privileges.
Calculate RAROC || Assess break even pricing || Perform revenue analysis || Manage risks
Holistic credit profile based pricing mechanism: Enables bankers to gain a comprehensive view of the customer’s profitability. For example, the tool takes into account collateral/guarantee for computing losses, resulting in a holistic assessment of risk instead of relying solely on credit rating.
Budgeting mechanism: Assists the business team in yearly/quarterly account planning exercise to systematically determine sales targets for relationship managers.
Access controlled, workflow-based system: Ensures the sanctity of the information entered and mitigate the risk of manual errors
Something for everyone
There are immediate to long-term benefits of adopting the rt360 risk-based pricing solution into your banking system. Relationship managers can optimize the proposed interest rates and fees to arrive at a RAROC percentage that is above the internal threshold set by the bank, yet acceptable to the customer. In addition, risk and product managers can slice and dice varied data inputs pertaining to risk and profitability to achieve granular insights for meaningful decisions and action. Managers can assess customer portfolios, evaluate profitability (segment-wise) and facilitate the risk department staff to conduct sensitivity analysis.
Beyond accurately pricing advances, this customized solution also helps in:
- Providing a personalized customer experience through customer level aggregation of relationships rather than having a narrow view of account/facility level profitability
- Facilitating superior efficiency and reduced cycle time for processing credit applications
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