The financial services sector is continuously evolving to match the customer’s growing expectations. In the penchant to offer enriching experiences to the customers, the banks have vigorously invested in ensuring seamless front-end operations.
Despite the front-end operations going digital-first, many back-end activities are still dependent on legacy systems and processes. From managing credit analysis to disbursing loans and processing the payments, many procedures are done manually.
A rough estimate by McKinsey suggests that close to 75-80% of the transactional banking operations and 40% of strategic operations can be automated in the banking segment. If banks reimagine their back-end processes with automation, it will increase their productivity and decrease costs.
Underwriters are tasked with the heavy lifting related to loan applications, and they evaluate the borrower's condition, capacity, and credit score.
The Credit Assessment Memorandum (CAM) creation process is labor and data-intensive and includes complex analysis by the underwriters. This can result in underwriter burnout, low closing rates, and at times inaccurate or inconsistent reports.
So, how can banking institutions support the underwriters to ensure the critical CAM reports are consistently accurate and reliable?
Automation solutions can address productivity and quality challenges, mitigate operational risks, and shield against malpractices. Faster data processing will make it easier for the institutes to detect anomalies and identify scams early.
An ideal automated CAM solution must provide three essential functions: financial analysis, fraud detection, and decision-making insights.
Financial data analysis serves as the foundation for the underwriter based on which the decision to lend or not to lend is taken. It helps to understand the repayment capacity of the borrower. For example, the underwriter will check the debt-to-income ratio to know if the debtor will pay back the borrowed amount.
To evaluate whether DTI is high or low, the underwriter will go through bank statements, tax and GST returns, and other income and spending proofs. It is a time-consuming task that requires much effort and involves a lot of documentation, data comparisons, and complicated data analysis.
The underwriters, at the moment, rely on spreadsheets to complete this task. This worksheet-based process hinders the underwriter’s performance and the progress of the financial institutions significantly. Lenders and underwriters are stuck in redundant systems and cycles and are losing their competitive edge.
Automating this process will mean getting accurate results in seconds and extracting the total value of borrower data from the applications. In addition, the automated procedures will compare the application against set parameters and help gauge if the application is genuine or not.
As frauds are becoming more commonplace, lenders have to expend more money to detect, track, investigate, prevent, and recoup the losses. To better equip themselves against these scams, lenders need to adopt more stringent measures for early detection. Some of the methods include:
● External Corroboration: Lenders can leverage automation to identify the truth of borrowers’ financial records. One of the ways to authenticate a financial document is having other data sources verify it. By having it referenced against alternate data, lenders can substantiate borrower claims.
● Multiple Document Cross-Analysis: This fraud identification method includes verifying data points by reconciling various submitted documents among themselves.
● Document Tampering: This is one of the most common ways used by fraudsters to dupe lenders. The automated solution should be able to detect any aberration and trigger alerts for inspection.
A solution that combines multiple detection methods would offer fraud prediction with increased efficiency.
Currently, this ability rests on the underwriter’s skills and discernment abilities. However, this manual process of staring and comparing data points is burdening the underwriter leading to stress and fatigue which can cause errors in CAM creation.
Automation solutions can complement the underwriters and enhance their performance. In addition, automated data analytics can offer rapid and large-scale process optimization and provide evidence-based decision-making insights for the underwriters’ scrutiny.
Powerful computing abilities combined with automation can generate insights derived from various data sources, making it easy for underwriters to evaluate risk. Moreover, lenders can supercharge their loan crediting process by augmenting underwriter teams with new technologies and decision-making reports.
Underwriters are highly qualified professionals who spend their time doing tedious, analog tasks to minimize risk. This can lead to lack of satisfaction since they have little time to use their specialized skills.
In addition, there are no specific models or data sets that they can use to compare the available results. The linear and lengthy underwriting process can lead to biased and inconsistent results.
There is a scarcity or, more accurately, absence of comprehensive solutions that can reduce the burden on underwriters and provide reports that can be assimilated readily.
On partnering with Perfios Solutions, lenders can stay ahead of the game between competition and fraudsters by supplementing their underwriters’ performance with automation technology.
Perfios CAM Pro is a holistic solution leveraging a confluence of its expertise in finance, data, and technology to transform the process of lending. It completely automates the underwriting process by integrating, analyzing, and verifying the borrower’s data from multiple sources.
It also provides an automated CAM report in a much shorter time than a traditional report, resolving the issue of time, money, and fraud, and frees up 10-12% of the underwriter’s time. The CAM report is developed after going through rigorous methods for detecting document tampering and fraud.
Perfios CAM Pro performs external data verification, multi-document reconciliation, industry insights, suspicious behavior identification, and document meta-data identification, leading to a 3-5% reduction in fraud losses.
CAM Pro’s industry insights play a significant role in profiling borrowers multi-dimensionally based on market sector, revenue, area of operations, and past credit history. Lenders can be alerted immediately if a borrower profile doesn’t match pre-set parameters based on these profiles.
This solution also provides cross-analysis across all data streams to provide an agile and real-time service to identify suspicious behavior patterns to aid the lender. The synergy between CAM Pro and an underwriter’s skill can deliver a dynamic lending workflow for improved efficiency.
Perfios CAM Pro aims to create a hybrid environment that leverages automation to boost productivity while enriching the experience of underwriters and consumers.
With the visibility of the industry’s eco-system and the five-step fraud detection cycle, Perfios CAM Pro provides an overarching independent solution for credit underwriting. It delivers an accurate and readily consumable report to assist underwriters in taking real-time credit decisions to the next level. It empowers the underwriters to focus more on their core competencies and offers a quick turnaround time for loan processing.