HomeBusinessInterview: Rubix Data Sciences CEO Mohan Ramaswamy on Modernizing Credit Risk Management
spot_img

Interview: Rubix Data Sciences CEO Mohan Ramaswamy on Modernizing Credit Risk Management

Date:

Trending

In an interview with TechGraph, Mohan Ramaswamy, CEO & Co-Founder of Rubix Data Sciences, spoke about how the company leverages data analytics and machine learning algorithms to bolster credit risk management.

Read the complete interview:

- Advertisement -

TechGraph: How does Rubix’s technology platform help organizations monitor credit risk in real-time?

Mohan Ramaswamy: In today’s VUCA environment, a one-time risk assessment is not adequate; counterparties’ risk needs to be monitored continuously. An entity that was a low credit risk 2 years ago may be a company’s biggest credit risk today. Its most critical supplier from a year ago may be bankrupt. This poses a significant challenge for companies with large distribution networks and supply chains because they need to regularly monitor the risk of their counterparty portfolio cost-effectively.

The IMC-award-winning Rubix Early Warning System (EWS) is a cost-effective and efficient plug-and-play platform that facilitates dynamic risk decisions about B2B counterparties, allowing companies to monitor the evolving risk of their counterparties (customers, distributors, dealers, suppliers, vendors, borrowers, franchisees, and competitors) both at an individual company and portfolio level. It does so by collating key risk indicators near real-time from various data sources, including statutory compliance and financial filings, news, and media, to get a dynamic view of a company’s risk profile.

It covers changes in:

• Payment Indicators (GST, PF Filings)

- Advertisement -

• Statutory Compliance (MCA filings)

• Credit Ratings

- Advertisement -

• News and Media

• Legal Cases Status

• Defaults

The Risk Score of an entity is dynamically updated by Rubix EWS based on the above. All this is presented in a highly intuitive and easy-to-use interface even for first-time users; it provides risk insights in color-coded, easy-to-read dashboards. If counterparties are highlighted in red, it means their Risk Scores have dropped and the company needs to be extremely cautious in its dealings with these partners. For counterparties marked in green, the company is comfortable proceeding with its transaction. However, for those marked in Amber, it needs a closer look before moving forward.

Moreover, the platform is completely flexible; the key risk parameters of counterparties can be set up to be monitored on a daily, weekly, monthly, or quarterly basis. Being fully automated, the Rubix EWS system leaves very little room for misjudgment or error and produces quick, up-to-date reports and Risk Scores.

The Rubix EWS system can function as a stand-alone platform or in conjunction with the Rubix ARMS Platform. Rubix EWS is a must-have tool in the risk management arsenal of Corporates, eCommerce Platforms, Banks, Credit Insurance Companies, NBFCs, Fintechs, and SMEs. Over 400 companies are using the Rubix EWS platform to effectively monitor the credit risk, supplier risk, and compliance, risk of 40,000 counterparties.

TechGraph: How does Rubix help organizations identify potential credit risks and mitigate them?

Mohan Ramaswamy: Credit risks should be assessed at various stages of the transaction cycle to ensure potential risks are identified and managed appropriately. The specific stages where credit risks should be evaluated for counterparties can vary depending on the nature of the transaction and the industry involved. However, here are some key stages to assess credit risks:

Pre-Onboarding Identity Validation: Before entering into a transaction with a counterparty, it is important to conduct an identity check and complete the Know Your Customer (KYC) process. This is a crucial step in credit risk management to ensure counterparty legitimacy and to prevent fraud or misrepresentation.

It involves verifying the identity and legal existence of the business entity by collecting and validating relevant identification documents. These documents include business licenses, tax registrations, articles of incorporation, and other supporting documentation.

This process helps confirm that the counterparty is a legitimate entity and minimizes the risk of engaging with fraudulent or non-existent businesses. Rubix’s advanced Video KYC Solutions, Key Registration Checks, and Promoter ID checks leverage Artificial Intelligence (AI) and Machine Learning (ML) to help our customers validate their counterparties’ identities before onboarding them.

Moreover, as India’s first Validation Agent for the Legal Entity Identifier (LEI), we help applicants get their LEI within 24 hours of applying. The Legal Entity Identifier (LEI) is a 20-character, alphanumeric code that uniquely identifies a legal entity or structure that is a party to a financial transaction in any jurisdiction.

The LEI connects to key reference information that enables a clear and unique identification of legal entities participating in financial transactions. Each LEI contains information about an entity’s ownership structure and thus answers the questions of ‘who is who’ and ‘who owns whom’.

Therefore, it is easier to trust entities with an LEI, cutting down on the risk of fraud. Regulators globally require businesses to have an LEI before entering certain transactions.

Credit Decisioning and Counterparty Risk Assessment: During contract negotiation, it is essential to incorporate appropriate credit risk mitigation measures. This may include setting credit limits and defining payment terms to mitigate credit risk. For this, we leverage the Rubix ARMS platform to assess the risk of our client’s prospective customers, distributors, dealers, franchisees, suppliers, vendors, or service providers.

This could be in the form of:

● Credit risk assessment and credit limit setting for customers/ distributors/dealers

● Supplier Risk assessment for suppliers and vendors.

● Compliance Risk assessment of all counterparties from statutory, legal, PEP, AML, anti-bribery (FCPA, UK Bribery Act), and sanctions perspectives.

We thus help banks, NBFCs, corporates, and Fintechs by providing independent credit risk assessment at the loan or trade credit decision stage. Our credit risk assessment also enables credit insurance companies to underwrite businesses in India and around the world.

Continuous Monitoring: Once the transaction is executed, ongoing monitoring of the counterparty’s creditworthiness is crucial. This involves tracking their financial performance, credit rating changes, and any other relevant factors that may impact their ability to fulfill their obligations. For this, we offer the Rubix EWS platform as described earlier.

Payment Processing and Collection: Throughout the payment processing and collection stage, it is important to ensure that the counterparty’s payments are made on the agreed terms. Timely and regular payment monitoring helps identify any potential credit issues or delinquencies early on. The Rubix B2B Structured Debt Collection process has been designed specifically for this task. It uses advanced analytics to identify high-risk accounts and prioritize collection efforts accordingly.

Finally, when contracts are up for renewal, it is an opportune time to reassess the counterparty’s creditworthiness and credit limits. The data collected by various Rubix solutions at each stage of the transaction cycle are vital inputs for dynamic risk scoring; the revised risk scores help businesses make prudent decisions about continuing the business relationship on existing terms, revising credit limits, or even terminating the contract. By promptly identifying and mitigating risks at each stage, our customers can safeguard their business interests.

TechGraph: Could you discuss how Rubix utilizes data analytics and machine learning algorithms to enhance credit risk management?

Mohan Ramaswamy: Data analytics, artificial intelligence, and machine learning are the backbone of many Rubix solutions:

Rubix Video KYC solution: AI-based OCR and face-matching technology embedded in this solution enable identity verification through live video-call, verification of identity documents against the Aadhar, PAN, and other statutory databases in India, facilitate live geo-tagging, provide real-time liveness checks of the individual being verified, and compare the video image of the individual with the photo in the identity documents. This helps ensure accurate identity verification. This solution is used in onboarding new counterparties in almost every industry. It is extensively used in the Banking, Financial Services, and Insurance (BFSI) sector in particular.

Rubix ARMS Platform: The Rubix Automated Risk Management and Monitoring System (Rubix ARMS) is a technology-based platform that identifies potential credit risks by analyzing large volumes of data about counterparties from internal and external sources, including financial statements, payment track records, transaction history, and more. For example, AI algorithms within the platform can rapidly identify financial red flags such as deterioration in key performance variables, financial ratios, etc.

They can automatically detect and highlight trends pertaining to delayed regulatory filings, employee payments, or deterioration in counterparties’ working capital position. This information can then be used to assess counterparties’ financial stability and determine if there is a risk of default.

The Rubix ARMS platform also moves a step further and analyses non-financial data, such as court records, media articles, social media, etc., to identify potential counterparty risks. Using proprietary risk scoring models, the Rubix ARMS platform leverages all the above data to assign a Rubix Risk Score to each entity.

The platform’s inbuilt Credit Limit Setting Models automatically recommend credit limits for each entity depending on its Rubix Risk Score. The Rubix ARMS platform limits human intervention in the credit-limit-setting process, reducing the scope for error or corruption.

Rubix EWS Platform: The Rubix Early Warning System (Rubix EWS) is a tech platform that monitors counterparty risk in near-real-time. Apart from structured data and traditional financial sources of data, the Rubix EWS platform is deployed by organizations to monitor news, litigation data, and social media posts related to their counterparties to identify any developments that can have a negative impact on their risk profile.

Based on the information collated, the Risk Scores of the counterparties are automatically adjusted by the dynamic risk scoring model deployed in Rubix EWS. Both the Rubix ARMS and EWS platforms are essential tools for any organization that seeks to monitor the B2B credit, supplier, and compliance risks of its counterparties.

TechGraph: How does Rubix ensure financial data security while providing risk management services to its clients?

Mohan Ramaswamy: Rubix obtains its data from over 120 public and proprietary data sources. We are ISO 27001 certified by LRQA and embed data privacy and security in all that we do. As required by the certifying agencies, we periodically assess our information security controls and perform vulnerability and penetration testing (VAPT) to ensure our data and systems’ security.

TechGraph: How does Rubix help organizations comply with regulatory requirements for credit risk management?

Mohan Ramaswamy: When companies carry out risk management of their supply chain partners, they get insight into whether the partners adhere to statutory compliances such as whether they have filed their GST on time, whether they are making PF payments without delay if they are filing annual reports and other forms as required by the Ministry of Corporate Affairs (for incorporated entities) periodically.

These compliance checks are important from a financial, reputational, and identity verification standpoint. Not only do defaulting vendors make it difficult for corporates to claim input tax credits, but they can also cause serious disruptions in the supply chain of important raw materials and inputs.

Supply chain partners or distributors/dealers who are non-compliant with local regulations (such as labor law, and pollution control regulations) or who have a lot of litigation also pose a risk to the company’s reputation.

TechGraph: Could you discuss any recent developments or upcoming initiatives at Rubix that focus on improving credit risk management services for its clients?

Mohan Ramaswamy: Rubix integrates risk assessment and monitoring with customer internal systems. To this end, Rubix is developing a credit workflow tool that helps our customers integrate Rubix Risk Scores with their internal credit workflow processes. In addition to this, credit information about late payments or defaults can help firms avoid truly risky situations.

TechGraph: Can you explain Rubix’s approach to credit risk management and how it differs from traditional risk management methods?

Mohan Ramaswamy: Rubix’s modern credit risk management platforms approach credit risk management by leveraging advanced technology, data analytics, automation, and integration capabilities. They differ from traditional methods in several ways:

Data-driven Decision Making: The Rubix ARMS and EWS platforms utilize vast amounts of data from 120+ sources, including financial statements, credit bureaus, statutory compliance and financial filings, and news and media.

This rich data is processed and analyzed using sophisticated algorithms and machine learning techniques to generate actionable insights for credit risk assessment and decision-making. Traditional methods often rely on limited data sources and manual analysis, which leads to less accurate risk assessments.

Near Real-time Monitoring: The Rubix EWS platform provides near real-time monitoring of counterparty credit risk by continuously tracking various parameters as discussed earlier. This enables the timely identification of emerging risks, early warning signals, and proactive risk mitigation. Traditional methods typically involve periodic reviews, which may miss important changes in a counterparty’s risk profile.

Automation and Efficiency: The Rubix ARMS and EWS platforms automate various credit risk management tasks, such as data collection, financial analysis, credit scoring, portfolio monitoring, and reporting. This improves efficiency, reduces manual errors, and enables faster decision-making.

Moreover, our solutions are cloud-based and designed to be flexible and scalable, making them cost-effective and easy to implement. Traditional methods often involve time-consuming, expensive, and labor-intensive manual processes, which are less efficient and prone to human error.

Advanced Risk Modelling: Rubix ARMS and EWS platforms employ advanced risk modeling techniques to assess credit risks more accurately. They use statistical models, machine learning algorithms, and predictive analytics to analyze historical data, identify risk patterns, and forecast future credit performance. These models can incorporate a broad range of risk factors, including macroeconomic indicators, industry-specific variables, and non-financial data. Traditional methods may rely on simple risk assessment models or subjective judgment.

Integration and Collaboration: Rubix’s plug-and-play solutions and platforms facilitate seamless integration with other systems, ERP platforms, and data sources within an organization. They enable collaboration between different credit risk management departments, such as credit, sales, finance, and compliance. This integration improves data accuracy, enhances risk assessment consistency, and promotes a holistic approach to credit risk management. Traditional methods often involve siloed processes and limited collaboration between departments.

Our clients agree that Rubix solutions help them with effective credit, supplier, and compliance risk management. This enables them to make informed risk decisions, minimize credit losses, and navigate the complex risk landscape more effectively.

THE SNAPSHOTS, IN YOUR INBOX

Get quick snaps of everyday happening, directly in your inbox.

We don’t spam! Read our privacy policy for more info.

- Advertisement -
Krishna Mali
Krishna Mali
Founder & Group Editor of TechGraph.
spot_imgspot_imgspot_imgspot_img

More Latest Stories

spot_img

Related Stories