Process Transformation through Process Mining in Mortgage Industry
The key driver for the growth in the mortgage industry is customer satisfaction fueled by faster service and competitive time to market. The challenges with mortgage industry are heavy documentation, timely decisioning, and compliance with strict regulatory
guidelines. The mortgage industry also have time taking processes such which are handled either internally or outsourced to external vendors for example, property assessment, insurance, assessment of property damage. It is time to review their business processes
and streamline to stay ahead.
Process mining is becoming a game-changer in a quest to bring process transformation by revolutionizing the way companies operate and serve their customers. Process mining applies data science to discover process map, analyze inefficiencies across IT systems
used to run business, and improve workflow of processes. Financial institutions can use the event logs from their information systems to get X-ray views of business processes and associated manual activities, system performance and apply analytics to identify
bottlenecks and other areas of improvement.
Process Mining helps analyze and identifies frictions, bottlenecks, and inefficiencies from the footprints of such complex processes and associated manual activities in the workflow. Like many other lines of business, the mortgage industry is facing increasing
pressure to streamline operations, reduce costs, enhance customer experience, and ensuring compliance with ever-growing complex regulatory reporting. Process mining offers a fresh perspective on achieving these goals by providing a data-driven and analytical
approach to understanding, optimizing, and transforming mortgage processes.
Below are key areas that business managers should consider while adopting process mining.
- Data-Driven Insights: Process mining leverages the vast amount of digital data generated while servicing the customer, such as loan origination, underwriting, and customer management, to uncover valuable insights and hidden inefficiencies and bottlenecks.
It provides transparency into the end-to-end process by visualizing the entire journey from customer contact to loan closure. This helps in identifying areas where optimization and improvement through automation, and process optimization can be done resulting
in faster loan approvals and improved customer satisfaction.
- Continuous Improvement: Mortgage processes are complex and often involve multiple stakeholders, including borrowers, loan officers, underwriters, and compliance teams. Process mining facilitates continuous improvement by pinpointing areas for enhancement
and enabling organizations to track the impact of process changes over time.
- Compliance and Risk Mitigation: The mortgage industry is very regulated, and any non-compliance can result in hefty fines and reputational damage. Process mining can help ensure that processes adhere to regulatory requirements by identifying deviations
and non-conformance to set activities. This proactive approach reduces the risk of regulatory violations.
- Cost Reduction: Inefficiencies in mortgage processes can lead to higher operational costs. Process mining identifies cost drivers and areas where resources can be better allocated, ultimately reducing operational expenses, and increasing profitability.
- Predictive Analytics: Other than retrospective analysis, process mining can also be used for predictive analytics. Many tools provide AI-ML capabilities to identify conformance and non-conformance and perform the simulations on the existing process.
What can we achieve? Key KPI’s addressed by Process Mining
Process mining can help mortgage companies address various key performance indicators (KPIs) by providing insights and data-driven solutions. Below are some KPIs and use cases in the mortgage industry that can be improved and explored through the application
of process mining.
1. Loan Processing Time:
Insights using process mining:Process mining identifies bottlenecks, delays, and inefficiencies in the loan origination process. By streamlining and optimizing workflows, mortgage companies can reduce processing time, leading to faster loan approvals
2. Cost per Loan:
Insights using process mining: Process mining can pinpoint cost drivers within mortgage processes. By optimizing resource allocation, reducing manual work, and eliminating redundant tasks, organizations can lower the cost per loan.
3. Application Rejection and Turnaround Time:
Insights using process mining: Process mining can identify patterns of rejected loan applications. By analyzing these patterns, mortgage companies can refine underwriting criteria, improve communication with applicants, and reduce rejection rates.
By automating document verification and reducing manual handling, organizations can accelerate the verification process.
4. Compliance Adherence:
Insights using process mining: Mortgage processes must adhere to numerous regulatory requirements. Process mining helps identify deviations and non-compliance issues, allowing organizations to proactively address them and reduce the risk of regulatory
5. Optimum Resource Utilization and Loan Origination Costs:
Insights using process mining: By identifying inefficiencies in the loan origination process, process mining helps reduce the costs associated with acquiring new loans. Companies can use this information to optimize resource allocation and reduce
over- or under-utilization. This includes cutting down on administrative work and reducing the need for rework due to errors.
What can ensure the successful process transformation?
Process transformation does not happen alone by utilizing process mining tools – they provide the first view to improve inefficiencies. Transformation is the automation of manual tasks throughout the processes. Organizations should consider following in
conjunction with process mining to ensure complete action on eliminating inefficiencies.
- Automation of manual tasks (say through RPA automation)
- Adoption of digitalization in the process (Documentation, customer connections etc.)
- Use of Bots and APIs in the overall stream of work
In summary, process mining provides mortgage companies with valuable insights and tools to address key performance indicators. By optimizing processes and adopting digitalization and automation, mortgage organizations can achieve better outcomes in a highly
competitive and regulated industry. It enables mortgage companies to unlock the value of their data, improve efficiency, reduce costs, enhance compliance, and reduce time to market.
This blog is co-authored by Sivasakthi Dhandapani ( Solution Architect at Tata Consultancy Services)