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Case Studies

Proof of concept: Optimizing loan approval process for a large CEE bank

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When a modern financial institution needed deeper insight into its loan approval processes, our consulting partner (one of the big four) relied on Minit to deliver data-based insights.

Process mining solution Minit delivered a more accurate picture of the business process than any previous approach. Minit was used to quickly and efficiently identify operational bottlenecks and verify process compliance. Based on the results of this project, the client is now planning to employ process mining across the entire organization.

The Customer's Business

Sector Financial Institution

Customer Profile A modern bank with a focus on retail clients, small and medium-sized enterprises, municipalities, and cities with an important role in financing large corporations and providing financial market services.

Company Size 10 000+ employees

The Challenge

When a major financial institution started losing clients and revenues due to bad customer experience and long wait times for approval of loans, it was time to overhaul its less-than-efficient loans approval process. The initiative came with a steep challenge: bring clarity into a process which was often handled in a non-standard way. Despite conducting several previous business analyses, resolution for fundamental problems remained out of reach. Analysis of the process, by the traditional method of conducting interviews, suffered from limited visibility, subjective point of view and omitted exceptions. The potential hidden in the data behind the process remained untapped.

The Solution

To analyze the loan process, our partner selected Minit to deliver a data-driven process analysis, with the goal of identifying key loan process bottlenecks and finding their remedies.

Using special algorithms, Minit analyzes Big Data extracted from ERPs, CRMs, Service Management systems, BPM, LOB systems, and more to show how business processes in the company really flow based on reality, not a subjective view of information gathered by traditional means of interviewing personnel.

To begin the loan process analysis, it was necessary to acquire data from LOB systems which would fulfill reasonable quality requirements and enable analysis of the whole process. This was achieved in three steps. The Analysts created ETL (Extract, Transform and Load) to pull data out of the source systems, in this case, SQL databases. Data extracts were prepared using R and loaded into Minit for process visualization and deep drill down.

Our partner relied on Minit‘s efficient computing capabilities to handle the information density of the extracted Big Data and analyze it within seconds. Minit used its intelligent algorithms to reduce the complexity of the data and categorize it in a way that allowed analysists to deduce all relevant information. Minit delivered thorough and detailed views into loaning process patterns and helped identify completely new correlations. In the initial analysis, over 30 000 events were analyzed. Instant analysis of this amount of data would not be possible by any other method. With Minit’s help analysists quickly found answers to customers business-related questions, reducing the costs and time necessary for completion of the project by up to 90%.

The main project objectives were:

  • Create detailed end-to-end process map of selected loan process
  • Identify the key bottlenecks in the selected process
  • Validate several clients’ business hypotheses

The process was analyzed from the Human perspective, focusing on the efficiency of the process, mainly time and labor wise. This was done by comparing the productivity of different teams handling similar tasks, taking a close look at the reasons for delays in the process, and identifying the most inefficient variants of the selected process.

As a result of the analysis:

  • Key bottlenecks, inefficient process variants, and their sources were uncovered
  • Differences in employee performance and their reasons were diagnosed
  • Process optimization points were uncovered

The Result

As the analysis showed, the main pain point was a lack of standardization of the loan approval process and multiple inefficient variants of the process. A lot of time was being wasted by “swimming against the flow” of the process and returning to an already passed point in the process flow multiple times.

Thanks to Minit’s powerful process visualization capabilities, our partner was able to demonstrate the loan process bottlenecks to client company’s broader management, identify optimization points and make recommendations to improve the loan approval process. The implementation plan for making the loan processes more efficient and simpler was put in place.

As a further result, this data-driven process analysis proved that process mining approach can be very efficient to help quickly identify the key process bottlenecks and to find their remedies. Furthermore, the client’s organization is planning to analyze dozens of processes in order to improve customer satisfaction and achieve operation excellence.

Process mining solution Minit was recognized as Microsoft Industry Awards Winner 2015 and mentioned as one of the top products by GARTNER.

Simona Parnicka Marketing Manager at Minit

10. 01. 2017