The Importance of Analytics and Risk Management Platforms in B2B Risk Management

Risk management is evolving with technology, analytics, and data, enabling organizations to navigate the complex financial landscape effectively.

Risk management is a critical core competency that enables organisations to preserve their financial health and stability while continuing to grow. The availability of high-quality data and information is a prerequisite for developing a robust risk management plan that can deal with an ever-evolving inventory of risks.

Managing risk requires the creation of cultures and systems that facilitate the collection, analysis and communication of data elements that impact enterprise financial risk. As business models are increasingly becoming complex, traditional risk management tools are proving to be inadequate to assess, monitor and mitigate risk. Risk management has become daunting because of the large number of variables that can impact risk, and their volatility. It is here that predictive risk analytics can provide an edge to managers to assess and measure risk based on the interplay of multiple variables.  

The risk management industry has greatly benefitted from the evolution of technology in Big Data, analytics, mobile applications, cloud computing, Enterprise Resource Planning (ERP), and Governance, Risk, and Compliance (GRC) systems. Many next-generation risk management platforms leverage data, analytics, artificial intelligence, and machine learning to help finance teams identify, model, simulate, report and mitigate risks, and prevent fraud. These platforms enable companies to avoid financial losses and grow in a sustainable and compliant manner.

Technology and analytics-based platforms play an important role in different facets of Risk Management: 

Dynamic, Data-driven Risk Identification and Reporting

The days of manually poring over excel sheets and reams of risk reports are long past. Real-time risk reporting is becoming the norm and it requires continuous data gathering and analysis from line functions, staff functions, contractors, and departments on-premises as well as at remote sites. Workflow tools embedded in next-gen risk platforms allow teams to collaborate in real time, break silos, and share data instantly. These, in turn, help identify and monitor nascent or emerging risks and facilitate early action to minimise such risks. Regulatory requirements may also require rapid reporting of financial risks in various industries, for example, mark-to-market reporting requirements in the broking industry. It is nearly impossible to achieve this without sophisticated risk management platforms.

Risk Modelling and Simulation

Banks and financial institutions model risk at scale using huge volumes of data through risk simulations. They analyse portfolios by simulating a variety of risks and forecast the projected losses that would occur in different scenarios. The risks they cover include Credit Risk, Market Risk, Liquidity Risk and Operational Risk, amongst others. Such risk modelling helps determine capital requirements under different risk scenarios.  

Compliance Risk Assessment

To comply with Compliance Risk Assessment requirements, modern risk platforms use robotic process automation to trawl through large amounts of structured and unstructured data (including social media) and global statutory databases to find red flags about counterparties and key individuals. If something out-of-the-ordinary is found (e.g., negative Anti Money Laundering (AML) data), the transaction is held in abeyance, and the counterparty is flagged for further due diligence.

Fraud and Identity Verification

Risk Platforms incorporate Fraud and Identity Solutions, which carry out accurate KYC checks on counterparties by using Application Programming Interfaces (APIs) that instantly run checks on global identity databases such as the Legal Entity Identifier Index, national identity databases (e.g., Aadhar), taxation, and company registration databases (e.g., MCA database). In case there is no positive match for the individual identity or business, the counterparty gets red flagged. 

The proliferation of data-science-backed technology tools makes it feasible for corporates and banks to detect fraud risks early and take proactive steps to mitigate them, which helps to avoid or minimise financial losses.

Risk Scoring and Automated Credit Limit Setting

An important use case for Risk Platforms is the assessment, monitoring and mitigation of Credit Risk. Risk Platforms have scoring engines that generate Credit Scores for individual counterparties based on a plethora of financial and non-financial data elements. The Credit Score, when combined with the payment history of the counterparty, facilitates automated credit limit setting.

Conclusion

Enhanced availability of data helps make risk management more robust. However, the explosion in data volumes and data types (both structured and unstructured) makes the task challenging.  

CFOs and Finance Teams need Risk Management Platforms because they have the ability to assimilate, de-duplicate and organise data meaningfully before deploying risk analytics. These platforms do not just provide risk assessment by way of Risk Scores but also help monitor Risk by dynamically generating Risk Scores as and when Risk Variables change. They are capable of assessing the risk of individual counterparties or the entire portfolio (by region, the legal constitution of counterparties, etc.) and presenting the risk data visually in easy-to-understand charts and tables. Moreover, the output from these risk management platforms can be easily integrated into ERP systems and organisational workflows, which helps CFOs, finance teams, and all stakeholders (e.g., sales teams) to quickly focus their attention on the riskiest portions of the portfolio.

Written by Mohan Ramaswamy, CEO & Founder, Rubix Data Sciences