Overview of the Organization
The selected organization is Bausparkasse Schwabisch Hall (BSH). It is a German-based financial institution founded in 1931 and has worked excellently to become one of the prominent building organizations in Germany. Bausparkasse Schwabisch Hall is a credit organization providing contractual savings for housing and financing solutions to its customers. The main goal of this organization is to support and promote the development and preservation of private homes. With approximately 6.5 million people working under its umbrella, BSH has most customers based in Germany, making it a part of the German Cooperative Banking Network (SAS, n.d.). This organization may be among the 750 bank corporations with credit ratings reaching A+ and AA- respectively, suggesting low and shallow credit default risk (Kiene, 2022). Its S&P and Fitch ratings portray the organization’s loan quality and assist the investors and other borrowers in assessing and evaluating each bank’s fiscal health, resiliency, and risk exposure before they borrow funds.
Problem or the Need for the Application of Data Analytics
Occasionally, BSH experiences fraudulent activities in its transactions, forcing it to implement data analytics processes to curb these activities, which may facilitate huge losses. Some of the malicious activities experienced include document forgery, credit card fraud, tax fraud and social security fraud, which may lead to complex issues (Kiene, 2022). The abovementioned issues encourage fraudulent loan applicants to apply for loans, which may later cost the organization. In summary, the primary problem with this organization is loan application fraud (SAS, n.d.). This is an attempt or a process to use false documents to get money. Occasionally, fraudsters forge documents to indicate salary increases in their statements, making it appear that they satisfy the required creditworthiness threshold for a construction loan or a home.
The Data Analytic Methods Used to Solve the Problem
As stated and explained above, the main issue with BSH is loan application fraud, which needs technological intervention. Since the company experiences thousands of loan applicants monthly, BSH’s fraud checker team needed user-friendly software with intelligence, automation and visualization capabilities. As a result, it chose to use SAS Visual Investigator on SAS Viya (Bausparkasse et al., 2021). According to BSH’s fraud analyst, Theresa Grimm, the software would store several fraud prevention rules and regulations, which had to be self-explanatory and visually appealing. Optical Character Recognition software was integrated into this digitization project to read the salary statements of loan applicants automatically. Although the software does not refer to the employers to verify the salary statements, it is highly capable of detecting the documents which have been forged (Kiene, 2022). Additionally, it can scan various characters, including taxable income, salary and name.
In other cases, scammers can falsify salary statements by developing professional-like forged documents that cannot be easily differentiated from the actual salary statements. In order to counter this problem, BSH, through the Fraud Analyst Theresa Grimm, incorporated the joint rules into SAS Visual Investigator by moving 40 characteristics to an anti-fraud software solution (SAS, n.d.). After that, the software started to scan the documents for inconsistencies spontaneously. In this context, when a fraud activity is suspected, the system sends an alert and identifies the source of fraud.
The outcome of the Application of Data Analytics
Though the outcome of applying data algorithms in BSH is not entirely efficient, it can be considered positive. The data analytics tool can easily detect fraudulent activities related to the forgery of salary statements where fraudsters want to meet the set threshold to access construction loans (Bausparkasse, 2021). Also, the software is user-friendly, making it usable for all employees in the company. This increases efficiency since employees cannot make errors. Generally, BSH applies data analytic algorithms to prevent fraud.
Summary
Applying SAS Visual Investigator on SAS Viya by BSH is essential since it helps prevent fraud, which may lead to losses. The user-friendly system makes it easy for every user to apply it. Since the system facilitates automation, it is essentially used to view and analyze the documents presented by thousands of loan applicants each month they need to apply for home or construction loans. Therefore, the software prevents fraud due to its capability to scan salary statement documents and identify some of them that have been tampered with. This minimizes the risks of giving loans to fraudsters.
References
Bausparkasse Schwäbisch Hall AG. (2021). Investorenpräsentation Bausparkasse Schwäbisch Hall AG. https://www.schwaebisch-hall.de/content/dam/dambsh/unternehmen/investor-relations/2021-07_investorenpraesentation_lang.pdf
Kiene, M. (2022, May 9). Nord/lb issuer guide 2023 Nordic agencies. https://www.nordlb.com/my-nord/lb-portals/download/research-document-12211?cHash=88c7d9d421d18e33e6fde41c47f35731
SAS. (n.d.). Fighting loan application fraud with cutting-edge analytics | SAS. https://www.sas.com/en_us/customers/bausparkasse-schwabisch-hall.html
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