Daten & Technologie
Using Open Banking Data to Optimize Risk Scores in Banking
Learn how to use Open Banking data to build more accurate, comprehensive risk scores for lending decisions.
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What Is Open Banking?
Open Banking refers to a financial system in which banks and other financial institutions securely share customer data through standardized APIs (Application Programming Interfaces). This happens with the customer's consent and allows third-party providers to access banking data in order to offer innovative financial services. This data can include transaction histories, account balances, and other relevant information.
The rollout of Open Banking has been driven largely by regulatory initiatives such as the European Union's Payment Services Directive 2 (PSD2). PSD2 requires banks to grant third-party providers access to their customers' account information, provided the customer has given consent. The goal is to foster competition, drive innovation, and make financial services more transparent and accessible for consumers.
Using Data to Optimize Risk Scores in Banking
Using Open Banking data to optimize risk scores represents a major innovation in the banking sector. Through so-called "account insight" — a detailed view into a customer's account data — banks and lending institutions can assess a customer's creditworthiness and risk profile more precisely and holistically.
Standard Scores and Common Market Practices
Banking has well-established standards and methods for calculating risk scores. These scores are critical for assessing creditworthiness and managing credit risk. The best-known include:
FICO Score: A widely used credit score that assesses an individual's creditworthiness. It factors in payment history, debt level, length of credit history, new credit inquiries, and credit mix. The score ranges from 300 to 850, with higher values signaling better creditworthiness.
Schufa Score: In Germany, the Schufa score is one of the most important indicators of creditworthiness. It is produced by Schufa (the German credit bureau) and is based on a person's credit and payment history. The score ranges from 0 to 100, with a higher value indicating a lower probability of default.
VantageScore: An alternative credit score developed by the three major US credit bureaus. Similar to the FICO score, it factors in payment history, credit utilization, credit type and length, and new credit inquiries. This score also ranges from 300 to 850.
Using Open Banking Data to Improve Risk Scores
Integrating Open Banking data makes it possible to supplement traditional credit scores with additional, granular information — refining risk assessment in the process. Here are some specific approaches:
Enhanced income analysis: Account insight lets banks better track recurring income streams and their stability. This covers not just salary payments but also other income sources such as rental income, freelance fees, or social benefits. A stable, diversified income stream can significantly reduce the risk of default.
Detailed spending patterns: Analyzing expenses reveals a customer's financial discipline and consumption behavior. Account data shows recurring obligations like rent, utilities, and insurance, as well as discretionary spending. This lets banks build a more accurate picture of a customer's financial resilience.
Payment history and liabilities: Access to account data lets banks review the history of payments and existing liabilities. Consistent, on-time payment behavior improves the risk score, while late payments or frequent overdrafts can be flagged as risk factors.
Cash flow analysis: Cash flow analysis is especially critical for the self-employed and freelancers. Open Banking data makes it possible to account for seasonal income fluctuations and assess financial stability over a longer period.
Examples of Risk Score Optimization
Lending to freelancers: Traditional creditworthiness checks are often based on fixed salaries and permanent employment, which can put freelancers at a disadvantage. With account insight, banks can analyze freelancers' actual income streams and financial obligations and make a better-informed decision about their creditworthiness.
Personalized credit offers: Based on detailed account data, banks can create tailored credit offers that match a customer's individual financial needs and risk profile. For example, a customer with a stable income but high monthly expenses might receive a loan offer with a longer term and lower installments.
Early warning systems for financial difficulty: By continuously monitoring account data, banks can spot early signs of financial distress and take proactive steps to minimize credit risk. For instance, a bank might reach out to a customer after unusual withdrawals or a sudden drop in income to offer preventive solutions.
Conclusion
Using Open Banking and the account insight it enables to optimize risk scores in banking offers numerous benefits. Banks gain a more comprehensive and realistic view of their customers' financial situation, leading to more precise lending decisions and improved risk assessment. Customers benefit from tailor-made financial products and a fairer assessment of their creditworthiness. Overall, this represents a significant step forward for banking, delivering substantial benefits for both banks and customers.
Acceleraid@OpenBanking
As experts with more than 10 years in the financial industry, we have already delivered a wide range of projects with various financial institutions, issuers, and finance companies.
Get in touch if you'd like to learn more about how Open Banking can be applied at your company, and which data can be used to achieve which goals and evaluations!
Further reading: BaFin (Federal Financial Supervisory Authority) – Open Banking & Open Finance: https://www.bafin.de/DE/Aufsicht/FinTech/Geschaeftsmodelle/OpenBanking_OpenFinance/OpenBanking_OpenFinance_node.html