Assume you are panel consisting of world renowned leading experts and visionaries in following roles: Product manager, Project manager, business analysts, app developers, software architects, personal loan field sales agents, Loan processing operations and finance teams and process experts.

The panel has been requested to discuss amongst themselves and come to a consensus on optimizing and solving the following problem:

Context:
A traditional offline personal loan firm which used to operate mostly manually over emails and exchanging excel sheets as a means of data exchange is now looking to modernize.

Goal:
Our vision is to empower individual financial advisors through a comprehensive digital platform, enabling them to efficiently distribute multiple financial products like loans, credit cards, insurance, and savings accounts.

Trust remains a key challenge, with end customers often relying on personal relationships for financial services recommendations. Leveraging individual financial advisors who possess local trust and knowledge creates a scalable business model capable of tapping vast underserved populations.

There are two types of financial advisors in the traditional DSA market today, particularly in the context of loan servicing. Completely “self-serve” agents and “assisted-model” agents. 
self-serve agents are mainly associated with the DSA to have relationships with multiple banks while assisted-model agents rely on the DSA’s centralized or regional teams to convert the lead once its punched in. The DSA shares rate charts, gives unique bank codes for attribution, and occasionally gives updates on the customer’s loan application process. In both the processes, its key to verify agent level attribution so that commission is given correctly and agent relationship is maintained as the ticket sizes are usually large.

Self serve DSA mostly do their own thing, we setup bank affiliate/agent code for them across multiple banks and NBFC and provide support as an intermediary if they get stuck. In exchange they provide 0.3% of the sale as a commission to us. At month end, the bank provides us a master dump file, which we do a reconciliation check against the data the DSA has provided (excel) and the money we received as reported by our finance team (excel). They get money straight from bank.

Assisted DSA are far more reliant on our assistance, we provide them with Leads, Facilities for lead credit scoring/check, product catalog, Document Vetting and format adaptation for submission to different banks and NBFC (all having their own format requirements), affiliate/agent code setup, Post bank approval disbursement by our finance teams, Disbursement to customers, post disbursement support like balance transfer and helping bank the Demand Drafts. They get money via our finance teams. Commission we get from them is around 2.5%.

Our Operations teams also do the following: bank agent code generation and support as an intermediary. Maintain a knowledge base, Provide exception handling and priority support like Emergency disbursal of funds for medical emergencies etc. also based on descriptions above, include responsibilities typical to this role that I may have missed.

Our Finance teams also do the following: Reconciliation of fund movements from various sources such as bank dumps, DSA provided data etc. Commission adjustments like penalties and top-up funds, cash advancs etc. Actual disbursement of funds etc.

based on this information, understand the rational step by step flow of various processes from start to end, optimize them wherever possible.
Do a competitive analysis of our rivals android apps such as: Zet Partner, Oneandro, Ruloans (ruconnect), Turtlemint Pro etc. Make sure our solution out competes them on all aspects, especially in terms of UI/UX and intuitive process flow. 

Additional Features:
Multilingual capabilities and switchable localization for English, Hindi to start with.
Risk analysis when DSA is the primary audience of app.

A teams features where supervisor/proprietor and their subordinates can be relational mapped. supervisor can see subordinate operational and performance metrics.  discover Main requirements and implications for the teams feature.
Suggest Different Personas for the app audience and the roles they play.
Different roles that can currently exist in the system.

Investigate features that the other personas in the system require, things like contact centers and data/excel input/import feature.

design A simple offline first Lead Punch-in journey.
Provide dashboard/API access to back end processing teams, starting with simple excel import and export.

Initial users 10000 and potentially scaling up to 50000.

Design a simple clean rational cross platform deploy able app and its corresponding back end using open source stack Implementing cutting edge techniques and best practices based lean, agile, performant, low latency Infra as code solution in an Prototype and MVP first phased development approach, give approximate roadmap using developer hours and account in for typical productivity and typical over and under estimations.