{"id":10048,"date":"2026-09-01T09:02:32","date_gmt":"2026-09-01T09:02:32","guid":{"rendered":"https:\/\/decentro.tech\/blog\/?p=10048"},"modified":"2026-09-01T09:05:25","modified_gmt":"2026-09-01T09:05:25","slug":"fusion-finance-case-study","status":"publish","type":"post","link":"https:\/\/decentro.tech\/blog\/fusion-finance-case-study\/","title":{"rendered":"How Fusion Finance Lifted Promise-to-Pay to 40% With Neowise &#8211; A Decentro Company"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_17 counter-hierarchy\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><\/span><\/div>\n<nav><ul class=\"ez-toc-list ez-toc-list-level-1\"><li class=\"ez-toc-page-1 ez-toc-heading-level-1\"><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/decentro.tech\/blog\/fusion-finance-case-study\/#The_Rural_Lending_Opportunity_and_its_Collection_Challenge\" title=\"The Rural Lending Opportunity and its Collection Challenge \">The Rural Lending Opportunity and its Collection Challenge <\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-1\"><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/decentro.tech\/blog\/fusion-finance-case-study\/#About_Fusion_Finance\" title=\"About Fusion Finance\">About Fusion Finance<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-1\"><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/decentro.tech\/blog\/fusion-finance-case-study\/#The_Problem\" title=\"The Problem&nbsp;\">The Problem&nbsp;<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-1\"><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/decentro.tech\/blog\/fusion-finance-case-study\/#The_Solution\" title=\"The Solution\">The Solution<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-1\"><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/decentro.tech\/blog\/fusion-finance-case-study\/#Why_This_Matters_for_a_Rural_Lending_Platform\" title=\"Why This Matters for a Rural Lending Platform\">Why This Matters for a Rural Lending Platform<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-1\"><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/decentro.tech\/blog\/fusion-finance-case-study\/#Results_and_Impact\" title=\"Results and Impact\">Results and Impact<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-1\"><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/decentro.tech\/blog\/fusion-finance-case-study\/#In_Closing\" title=\"In Closing&nbsp;\">In Closing&nbsp;<\/a><\/li><\/ul><\/nav><\/div>\n\n<figure class=\"wp-block-image size-large featured-post-img\"><img loading=\"lazy\" width=\"1779\" height=\"1779\" src=\"https:\/\/decentro.tech\/blog\/wp-content\/uploads\/Fusion_Finance_InternalBanner-1.jpg\" alt=\"\" class=\"wp-image-10065\"\/><\/figure>\n\n\n\n<p>India&#8217;s rural lending sector is under pressure to scale collections and communication without scaling cost. <a href=\"https:\/\/neowise.money\/\" target=\"_blank\" rel=\"noreferrer noopener\">Neowise<\/a>, a Decentro company, enabled Fusion Finance to replace a field-agent-dependent process with an AI voice bot stack, turning every stage of the loan relationship, from disbursal to a customer&#8217;s most difficult moments, into an automated, multilingual touchpoint that runs without waiting on agent availability.<\/p>\n\n\n\n<h1><span class=\"ez-toc-section\" id=\"The_Rural_Lending_Opportunity_and_its_Collection_Challenge\"><\/span>The Rural Lending Opportunity and its Collection Challenge <span class=\"ez-toc-section-end\"><\/span><\/h1>\n\n\n\n<p>India&#8217;s microfinance sector serves a customer base that traditional banking has historically struggled to reach: rural borrowers taking small-ticket loans, repaid in EMIs, often in regions where digital infrastructure and formal banking touchpoints are thin. As microfinance institutions scale their rural footprint, the operational weight of collections and customer communication scales right alongside it.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"2500\" height=\"1690\" src=\"https:\/\/decentro.tech\/blog\/wp-content\/uploads\/Fusion_Finance_Bull_Run.jpg\" alt=\"Deposits and credit for Banks market \" class=\"wp-image-10053\"\/><\/figure>\n\n\n\n<p><a href=\"https:\/\/fusionfin.com\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Fusion Finance<\/a> sits inside this shift. As a microfinance lender serving rural customers across India, its business depends on reaching every borrower at every stage of their loan in a way that is timely, compliant, and understandable to them. That last part matters more than it sounds. A reminder call in Hindi to a customer who speaks Odia at home is not really a reminder at all.<\/p>\n\n\n\n<p>But reaching a rural customer base at scale comes with a structural limit that most lenders eventually hit: the field agent model.<\/p>\n\n\n\n<h1><span class=\"ez-toc-section\" id=\"About_Fusion_Finance\"><\/span>About Fusion Finance<span class=\"ez-toc-section-end\"><\/span><\/h1>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"2500\" height=\"3438\" src=\"https:\/\/decentro.tech\/blog\/wp-content\/uploads\/Fusion_Finance_Market_Cap_26_Key_Strengths.jpg\" alt=\"India's Top MFI companies\" class=\"wp-image-10054\"\/><\/figure>\n\n\n\n<p>Fusion Finance was founded on a simple premise: make formal credit accessible to India&#8217;s rural, underbanked women. By operating on the Grameen Joint Liability Group model \u2014 group-backed loans, doorstep-first service, and now AI-powered voice outreach \u2014 Fusion Finance has eliminated the barriers that kept rural entrepreneurs outside the formal banking system.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"2866\" height=\"1380\" src=\"https:\/\/decentro.tech\/blog\/wp-content\/uploads\/Screenshot-2026-09-01-at-1.19.38\u202fPM.png\" alt=\"Fusion Finance website\" class=\"wp-image-10061\"\/><\/figure>\n\n\n\n<p>Today, Fusion Finance operates with:<\/p>\n\n\n\n<ul><li>32 lakh+ active borrowers<\/li><li>1,571+ branches across 22 states and UTs<\/li><li>100% women client base in rural and semi-urban India<\/li><li>15,000+ employees<\/li><\/ul>\n\n\n\n<p>Its lending portfolio spans microfinance, MSME, and secured business loans, and its promise to these borrowers is reach and trust, in a language and manner they understand, from the day a loan is disbursed to the moment it&#8217;s repaid.<\/p>\n\n\n\n<h1><span class=\"ez-toc-section\" id=\"The_Problem\"><\/span>The Problem&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h1>\n\n\n\n<h3>Two Structural Gaps Limiting Collections at Scale<\/h3>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"2500\" height=\"1553\" src=\"https:\/\/decentro.tech\/blog\/wp-content\/uploads\/Fusion_Finance_The_Problem.jpg\" alt=\"The problem - Two Structural Gaps Limiting Collections at Scale\" class=\"wp-image-10055\"\/><\/figure>\n\n\n\n<p>For a lender whose customer base is spread across rural geography, every unreached customer is a missed reminder, a delayed EMI, or in some cases, a family that never learns about a benefit they are owed. Two structural gaps were driving this.<\/p>\n\n\n\n<p><strong>Field Agent Dependency: Resource-Heavy and Hard to Scale<\/strong>&nbsp;<\/p>\n\n\n\n<p>Coordinating a large network of on-field agents across dispersed rural areas is operationally expensive and difficult to standardise. Every agent interaction depends on individual availability, travel time, and local coverage, none of which scale in a straight line with loan book growth.<\/p>\n\n\n\n<p><strong>Manual Call Centre Overhead: A Ceiling on Reach<\/strong>&nbsp;<\/p>\n\n\n\n<p>Fusion Finance&#8217;s call centres were calling its entire customer base manually for reminders and collections outreach. This model required significant manual effort regardless of how routine or predictable a given call was. Every customer, from a first-time borrower to someone 90 days overdue, was going through the same manual process, with no way to prioritise agent time toward the conversations that actually needed a person.<\/p>\n\n\n\n<h1><span class=\"ez-toc-section\" id=\"The_Solution\"><\/span>The Solution<span class=\"ez-toc-section-end\"><\/span><\/h1>\n\n\n\n<h3>A Bot for Every Stage of the Loan<\/h3>\n\n\n\n<p>Neowise, a Decentro company, enabled Fusion Finance to build an AI voice bot system, via <a href=\"https:\/\/neowise.money\/neobot\/\" target=\"_blank\" rel=\"noreferrer noopener\">NeoBot<\/a>, that follows a customer through the complete lifecycle of their loan, in the language they speak at home, so that agent time is reserved for the moments that genuinely need a human.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"2500\" height=\"1690\" src=\"https:\/\/decentro.tech\/blog\/wp-content\/uploads\/Fusion_Finance_The_Sollution.jpg\" alt=\"Th solution via Neobot - A Bot for Every Stage of the Loan\" class=\"wp-image-10056\"\/><\/figure>\n\n\n\n<h4>Welcome Call Bot&nbsp;<\/h4>\n\n\n\n<p>Runs immediately after loan disbursal to confirm the process went smoothly and share key loan details and upcoming payment dates. How it works:<\/p>\n\n\n\n<ul><li>Bot calls the customer shortly after disbursal.<\/li><li>Confirms no unofficial commission or bribe was demanded during processing, escalating internally if flagged.<\/li><li>Shares Fusion Finance&#8217;s toll-free number and upcoming meeting or payment dates.<\/li><\/ul>\n\n\n\n<h4>First EMI Call Bot&nbsp;<\/h4>\n\n\n\n<p>A separate, warmer version of the reminder call reserved specifically for a customer&#8217;s very first EMI, designed to welcome new borrowers rather than simply remind them. How it works:<\/p>\n\n\n\n<ul><li>Triggered only on a customer&#8217;s first EMI cycle.<\/li><li>Uses a warmer script and tone than standard reminder bots.<\/li><li>Reinforces the customer&#8217;s place in Fusion Finance&#8217;s broader borrower relationship.<\/li><\/ul>\n\n\n\n<h4>Pre-Due Reminder Bot&nbsp;<\/h4>\n\n\n\n<p>Reaches customers ahead of their EMI due date, with a follow-up path that adjusts based on whether the first attempt connected. How it works:<\/p>\n\n\n\n<ul><li>Initial pre-due call placed ahead of the due date.<\/li><li>If the customer is reached, a confirmation-style follow-up bot runs.<\/li><li>If the customer is not reached, a different re-attempt bot runs.<\/li><\/ul>\n\n\n\n<h4>Fresh Overdue Bot (Day 1 to 30)&nbsp;<\/h4>\n\n\n\n<p>Covers the earliest stage of a missed payment, before an account moves into more serious collections territory. How it works:<\/p>\n\n\n\n<ul><li>Activates once a customer crosses 1 day past due on their last EMI.<\/li><li>Runs through day 30, reinforcing payment without escalation language.<\/li><\/ul>\n\n\n\n<h4>Litigation Warning Bots&nbsp;<\/h4>\n\n\n\n<p>Two bots that warn a customer of the possibility of loan recall and a formal demand notice if non-payment continues, used further along the overdue timeline.<\/p>\n\n\n\n<h4>90+ Settlement Bot&nbsp;<\/h4>\n\n\n\n<p>Offers a reduced settlement amount based on a customer&#8217;s financial hardship, rather than pursuing the full outstanding balance outright, once an account crosses 90 days past due.<\/p>\n\n\n\n<p>Built as two parallel use cases: one for MFI (microfinance) loans and one for MSME (secured business) loans, following the same process independently for each loan type.<\/p>\n\n\n\n<h4>90+ Settlement, Hybrid Model&nbsp;<\/h4>\n\n\n\n<p>For the hardest 90-plus-day accounts, a human agent conducts the call, with an AI bot providing real-time support. How it works:<\/p>\n\n\n\n<ul><li>The AI bot dials the entire pool of 90-plus day accounts, improving overall connectivity.<\/li><li>Agents are connected only once a call is live, so their time goes toward customers who picked up.<\/li><li>During the call, the bot surfaces pre-approved settlement bands based on the customer&#8217;s outstanding amount and financial profile.<\/li><li>Outcomes and follow-up commitments are logged in real time, giving agents context for future negotiation.<\/li><\/ul>\n\n\n\n<h4>Death Claim Settlement Bot&nbsp;<\/h4>\n\n\n\n<p>Contacts the family of a deceased borrower to explain that the loan carried life insurance coverage, and walks them through the claims process. How it works:<\/p>\n\n\n\n<ul><li>Bot reaches out to the registered next of kin or family contact.<\/li><li>Explains that the loan carried insurance coverage the family may not know about.<\/li><li>Walks the family through required documents and how to submit a claim.<\/li><\/ul>\n\n\n\n<h1><span class=\"ez-toc-section\" id=\"Why_This_Matters_for_a_Rural_Lending_Platform\"><\/span>Why This Matters for a Rural Lending Platform<span class=\"ez-toc-section-end\"><\/span><\/h1>\n\n\n\n<p>Unlike a platform where a delayed reminder is a minor inconvenience, Fusion Finance&#8217;s relationship with its customers is built on reach and trust across geography and language. A borrower who never gets a reminder in a language they understand is a borrower who falls behind through no fault of their own. A family that never learns about insurance coverage may never file a claim they are entitled to.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"2500\" height=\"1419\" src=\"https:\/\/decentro.tech\/blog\/wp-content\/uploads\/Fusion_Finance_Stage_by_stage.jpg\" alt=\"Stage by Stage deployment\" class=\"wp-image-10059\"\/><\/figure>\n\n\n\n<p>By enabling Fusion Finance with this bot stack, NeoBot addressed three risks simultaneously:<\/p>\n\n\n\n<ul><li><strong>Reach gaps:<\/strong> Rural customers spread across regions with limited language coverage were going unreached or misunderstanding communication meant to help them.<\/li><li><strong>Agent cost inflation:<\/strong> Manual calling and field visits applied the same level of effort to every customer, regardless of whether that customer needed it.<\/li><li><strong>Missed entitlements:<\/strong> Without a dedicated process, families of deceased borrowers risked never learning about or claiming life insurance coverage tied to the loan.<\/li><\/ul>\n\n\n\n<h1><span class=\"ez-toc-section\" id=\"Results_and_Impact\"><\/span>Results and Impact<span class=\"ez-toc-section-end\"><\/span><\/h1>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"2500\" height=\"2192\" src=\"https:\/\/decentro.tech\/blog\/wp-content\/uploads\/Fusion_Finance_Results_26_Impact.jpg\" alt=\"Results and Impact of the collaboration - Fusion Finance X Neowise\" class=\"wp-image-10058\"\/><\/figure>\n\n\n\n<p>Post-integration, Fusion Finance&#8217;s collections and communication process moved from a field-agent-dependent, uniformly manual model to a segmented, automated system that reserves agent time for the customers who need it most.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th scope=\"col\"><strong>Metric<\/strong><\/th><th scope=\"col\"><strong>Before Neobot<\/strong><\/th><th scope=\"col\"><strong>After Neobot<\/strong><\/th><\/tr><\/thead><tbody><tr><td>Reminder and collections outreach<\/td><td>Manual, agent- and call-centre-dependent<\/td><td>Automated via AI voice bots at every lifecycle stage<\/td><\/tr><tr><td>Language coverage<\/td><td>Primarily Hindi and English<\/td><td>12 to 13 regional and dialect-level languages, including Odia and Assamese<\/td><\/tr><tr><td>Agent time allocation<\/td><td>Applied uniformly across all customers<\/td><td>Reserved for follow-up and high-touch negotiation<\/td><\/tr><tr><td>90+ day account outreach<\/td><td>Manual dialling, low connectivity<\/td><td>AI-driven dialling with real-time agent support<\/td><\/tr><tr><td>Death claim awareness<\/td><td>No dedicated outreach process<\/td><td>Dedicated bot guiding families through the claims process<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>Beyond the table, the deployment has delivered the following results by use case since scaling up:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th scope=\"col\"><strong>Bot \/ Use Case<\/strong><\/th><th scope=\"col\"><strong>Total Loans<\/strong><\/th><th scope=\"col\"><strong>Customers Reached<\/strong><\/th><th scope=\"col\"><strong>Connectivity Rate<\/strong><\/th><th scope=\"col\"><strong>PTP Rate<\/strong><\/th><\/tr><\/thead><tbody><tr><td>Pre-Due, June<\/td><td>472<\/td><td>311<\/td><td>65.89%<\/td><td>25.08%<\/td><\/tr><tr><td>Pre-Due, July<\/td><td>17,539<\/td><td>14,886<\/td><td>84.87%<\/td><td>40.03%<\/td><\/tr><tr><td>Fresh Overdue Bot (Day 1 to 30)<\/td><td>21,168<\/td><td>14,756<\/td><td>69.71%<\/td><td>23.23%<\/td><\/tr><tr><td>90+ Settlement Bot, MFI<\/td><td>97,342<\/td><td>58,519<\/td><td>60.12%<\/td><td>5.97%<\/td><\/tr><tr><td>Death Claim Settlement, June<\/td><td>852<\/td><td>351<\/td><td>41.20%<\/td><td>N\/A<\/td><\/tr><tr><td>Death Claim Settlement, July<\/td><td>1,425<\/td><td>571<\/td><td>40.07%<\/td><td>N\/A<\/td><\/tr><tr><td>90+ Hybrid Model<\/td><td>104,115<\/td><td>47,873<\/td><td>45.98%<\/td><td>TBD<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"2500\" height=\"1535\" src=\"https:\/\/decentro.tech\/blog\/wp-content\/uploads\/Fusion_Finance_June_Vs_July.jpg\" alt=\"Pre-due reminder outcome\" class=\"wp-image-10057\"\/><\/figure>\n\n\n\n<p><strong><em>Pre-due reminder calls scaled from 472 loans in June to over 17,500 in July, and results held up at that larger volume: connectivity rose from 65.89 per cent to 84.87 per cent, and promise-to-pay rose from 25.08 per cent to 40.03 per cent over the same period.<\/em><\/strong><\/p>\n\n\n\n<h1><span class=\"ez-toc-section\" id=\"In_Closing\"><\/span>In Closing&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h1>\n\n\n\n<h3>Collections Infrastructure Is a Customer Relationship Problem<\/h3>\n\n\n\n<p>For Fusion Finance, automated voice outreach is not simply a way to cut collections costs. It is the infrastructure behind a relationship that follows a borrower from their first disbursal call to, in the hardest cases, helping their family through an insurance claim. By enabling Fusion Finance across the full loan lifecycle, in the languages its customers actually speak, Neowise, a Decentro company, helped convert a field-agent bottleneck into a system that reaches more customers, in less time, with agent effort reserved for the conversations that need it.<\/p>\n\n\n\n<p>Neowise&#8217;s debt collection and communication infrastructure, backed by Decentro, is built to scale with loan book growth and adapt to the language and regulatory realities of the markets it serves, so reach never becomes a ceiling on growth.<\/p>\n\n\n\n<p>Ready to automate your collections and customer communication?&nbsp;<\/p>\n\n\n\n<p><a class=\"decentro-homepage-signup\" href=\"https:\/\/neowise.money\/book-a-demo\/\" target=\"_blank\" rel=\"noreferrer noopener\">Let&#8217;s Connect<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>See how Neowise AI voice bots helped Fusion Finance reach rural borrowers in 12+ languages, lifting connectivity to 85% and promise-to-pay to 40%<\/p>\n","protected":false},"author":17,"featured_media":10067,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[70,144],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v15.7 - 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