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Time of India
30-07-2025
- Business
- Time of India
Account aggregator ecosystem facilitates loans worth Rs 1.6 lakh crore in FY25
Per a report by Sahamati—a bunch of entities within the AA ecosystem—titled 'Credit Reimagined: Account Aggregator (AA) Impact H2 FY25,' NBFCs led the usage of AA for lending, accounting for 60% of the overall lending in FY25. Tired of too many ads? Remove Ads Tired of too many ads? Remove Ads The Account Aggregator (AA) ecosystem facilitated loans worth more than Rs 1.6 lakh crore in the financial year 2025 , spanning 1.89 crore loan accounts, according to a report by Sahamati Sahamati—a collective of entities within the AA ecosystem—published the report titled 'Credit Reimagined: Account Aggregator (AA) Impact H2 FY25,' which collected the data from 12 lending institutions currently using the AA AA system, regulated by the Reserve Bank of India (RBI), enables individuals to securely share their financial data with service providers through consent. The companies that provide these services include Perfios-backed Anumati, CAMSfinserv, Setu AA and Finvu, among of June this year, close to 24.8 crore consent requests have been made through the AA system, said the report. The report further said that an estimated 12.73 crore Indians used the facility.'FY25 marks a turning point for the AA framework, moving from early-stage deployment to meaningful, large-scale adoption. Lenders are increasingly embedding AA into their core credit workflows—not just during onboarding, but throughout the entire credit lifecycle,' said Shalini Gupta, chief policy and advocacy officer at added, 'The next chapter for the ecosystem will be defined by how seamlessly AAs integrate across use cases, customer segments, and sectors, enabling more informed, consent-driven decision-making in financial services.'This comes as AAs, such as Protean eGov Technologies , will be equipped to offer access to the Aadhaar rails through a secured channel once the concerned ministry clears the proposal from these private companies, as reported by ET. Public sector banks reported the lowest contribution, accounting for less than 1%, said the financial institutions (NBFCs) lead the usage of AA for lending, accounting for 60% of the overall lending landscape in report further said that the ecosystem is no longer in pilot mode. The ecosystem, to move from scale to depth, needs to focus on adding on-ground staff for secured and MSME credit , requires proper monitoring of repayments, and needs diversification into areas like hyper-personalised financial products, the report added.


Time of India
29-07-2025
- Business
- Time of India
ET Make in India SME Regional Summits: How IDBI Bank is supporting Surat's MSMEs
Live Events Personal cash flow management: Promoters must handle cash flow personally rather than delegating this critical function Avoid fund diversion: Never use short-term working capital for long-term investments Personal wealth planning: Regularly set aside 0.5-1% of profits to build personal reserves as a safety net. The ET Make in India SME Regional Summits reached their fifth destination of 2025 on July 18, arriving in Surat to spotlight one of India's most critical industrial hubs. As the nation's leading platform for hyperlocal micro, small, and medium enterprise ( MSME ) engagement, these summits create vital connections between enterprises, industry enablers, and policy architects. The carefully-curated gatherings deliver precision networking that acknowledges the distinct advantages and challenges facing each regional the theme 'Make in Surat, scale for the world', the edition zeroed in on a city uniquely positioned at the intersection of traditional industrial strength and modern economic transformation. With 90% of the world's diamonds processed here through approximately 4,000 diamond factories and 30 million metres of fabric produced daily, Surat demonstrates unparalleled industrial concentration. The city's remarkable efficiency is rooted in the fact that it accounts for 25% of Gujarat's GDP despite accounting for less than 11% of the state's geographical area. And at the heart of Surat's growth are the thousands of MSMEs that form the backbone of its the unique needs of Surat's diverse MSME landscape, the summit's banking and lending partner IDBI Bank has developed a comprehensive suite of specialised services designed to address everything from cash flow management to foreign exchange risks. Speaking at the ET SME Summit - Surat, IDBI Bank Executive Director Nagaraj Garla outlined how the institution is supporting local entrepreneurs with tailored MSMEs, effective cash flow management determines the difference between success and failure. IDBI Bank has introduced a technology-enabled product that leverages Account Aggregator (AA) and digital end-to-end money lending infrastructure, enabling loan decisions within 10-15 minutes. Such rapid-fire lending addresses one of the most pressing concerns for small businesses operating in seasonal industries:"Cash flow management is absolutely critical," explained Mr. Garla. "If you were to identify one factor that distinguishes successful MSMEs from the rest, it's the effective management of cash flow."The bank also offers products to help MSMEs manage both receivables and payments, including participation in the TReDS and GeM Sahay platforms. Both allow businesses to quickly access funds against invoices, providing immediate liquidity when needed diamond industry faces unique challenges, particularly in managing foreign exchange risks and global payment uncertainties. IDBI Bank has positioned specialised treasury teams in Surat, Ahmedabad, and Mumbai to provide expert guidance on forex products, including forward contracts, options, and currency export-focused solutions include packing credit for pre-shipment funding, post-shipment credit in both INR and foreign currency, and ECGC-backed products. With new Free Trade Agreements being signed, particularly in textiles, the bank emphasises the importance of professional forex risk management for aspiring global banking usually requires substantial collateral, creating barriers for first-generation entrepreneurs and asset-light businesses. At the ET Make in India SME Regional Summit - Surat, Mr. Garla explained that IDBI has adapted to changing times, leveraging government schemes like CGTMSE coverage (extending up to ₹10 crore for most businesses and ₹20 crore for exporters and startups) and the new Individual Guarantee Scheme for capital expenditure up to ₹100 crore."While collateral remains important, its role has significantly reduced," he noted, acknowledging that viable businesses can now access funding without traditional security in the evening, IDBI Bank General Managers CS Arya and Sherine Mendez demonstrated how the institution has transformed its traditional industrial development expertise into a comprehensive MSME-focused banking ecosystem. This philosophy extends to traders, vendors, dealers, and entrepreneurs, ensuring that regardless of scale or profession, every enterprise finds appropriate financial presentation at the ET SME Summit Surat focused on the following:1) Innovation-driven working capital solutionsIDBI Bank has two products that eliminate traditional banking friction. MSME Express offers instant loan sanctions up to ₹25 lakh without requiring branch visits or prior banking relationships, while the PSU Supplier Loan provides collateral-free financing ranging from ₹40,000-₹10 lakh, with instant disbursal upon purchase order verification. These products reflect the bank's commitment to leveraging technology for seamless financial access, supported by robust trade finance capabilities that process approximately 200,000 invoices monthly across various platforms, maintaining a 5% market share in supply chain finance.2) Sector-specific expertise and global reachIDBI's sectoral specialisation spans services, manufacturing, construction equipment, healthcare, and food processing, offering both traditional products like working capital and letters of credit alongside innovative solutions such as trade credit and port international capabilities are equally impressive, providing export finance solutions in over 100 currencies, forex risk management, and collateral-free loans up to ₹10 crore under CGTMSE. This is reinforced by dedicated infrastructure, including specialist MSME branches, trained relationship managers, and centralised processing from over three decades of experience, Mr. Garla wrapped up his fireside chat by sharing three critical success principles for MSME entrepreneurs:As Surat continues to evolve as an MSME powerhouse, IDBI Bank demonstrated how financial institutions can adapt their services to meet the unique needs of regional industrial clusters. The ET Make in India SME Regional Summit - Surat was the perfect platform to showcase a broader strategy of understanding local business ecosystems and developing solutions that address specific industry challenges, from the diamond merchant managing currency fluctuations to the textile exporter seeking working capital during peak seasons. The ET Make in India SME Regional Summits , ET MSME Day, and ET MSME Awards are flagship initiatives to celebrate the versatility and success of India's MSME sector. If you lead or are part of a micro, small, or medium enterprise, register for the ET MSME Awards 2025 before August 31, 2025.


Time of India
11-07-2025
- Business
- Time of India
How satellite-based alternative data can revolutionize MSME credit access
Indian MSMEs are key drivers of our economy due to their significant contribution in the Indian financial ecosystem. Indian MSMEs in recent times are witnessing a strong increase in formal credit, yet there is a long distance to reach their entire potential. As per media news, as of end March 2025, total loans disbursed to MSMEs had risen to ₹40.4 lakh crore, a 20% rise from ₹33.6 lakh crore in March 2024, and a significant leap from ₹28.3 lakh crore in March 2023. However, despite this growth, a report by Avendus Capital highlights that only about 14% of MSMEs have access to credit. The remaining population depends on informal, often costly and exploitative sources of credit, which severely limit their potential for growth and expansion. This exclusion builds up a two-way challenge. MSMEs find it difficult to establish creditworthiness in the absence of proof of income or collateral, whereas institutions like banks, NBFCs, and fintechs have to bear high costs and operational challenges in determining risk by way of manual checks and field visits. These are not scalable solutions, particularly for small businesses within remote or semi-urban regions. India's Financial sector has reacted by innovative use of structures such as the Account Aggregator ecosystem, Udyam registration information, GST filing, and infrastructure like TReDS. Alternative models of data based on utility bill payments, supplier invoices, and transaction streams have made credit accessible to a subset of digitally connected MSMEs. Those solutions tend to benefit mainly units that already possess some digital or financial presence. The real challenge lies in accessing the "missing middle', the vast majority of MSMEs that are running but invisible to mainstream or digital credit systems , especially in rural and semi-urban locations. Several of these businesses operate in small-scale industries, service industries, or value chains linked with agriculture, etc. They may have a regular income and healthy cash flow but lack any official financial papers or collateral to establish their creditworthiness. It is here that emerging innovations in alternate credit models can make the biggest difference. One of the most promising innovations here is the application of satellite data . Satellite intelligence furnishes site-specific, real-time data that can verify business activity on the ground. Lenders can see physical signs such as land use, production cycles, infrastructure upgrades, and even local climatic or environmental risks through the help of high-resolution imaging and geospatial analytics. These signs are reliable surrogates for company health, especially where paperwork is non-existent or unreliable. For example, a Kirana shop in a rural or semi-urban setting might not have formal books of accounts or digital records of transactions. But satellite imagery can still identify evidence of steady business activity like regular patterns of foot traffic, stock deliveries, or even physical enlargement of the facility over time. These visual cues, when interpreted in context, will allow lenders to estimate the size of operations, stability, and growth prospects of the store, generating useful inputs for credit decisioning even in the absence of conventional financial information. Blending satellite data with other alternative sources, such as supply chain contacts, utility bill payments, mobile phone behavior, and geolocation history, taps into the true power of this idea. Together, they establish a comprehensive, multi-dimensional credit profile more dynamic and representative of true company performance than mere static financial statements. By integrating these diverse datasets, lenders can significantly enhance the accuracy and inclusiveness of credit scoring models enabling quicker, fairer, and more informed lending decisions. This approach empowers underserved MSMEs to access working capital and build a credit history that can eventually bring them into the formal financial system. But introducing alternative credit models and satellite intelligence is no easy task. Transparency, ethical application, and data privacy have to be a certainty. To build scalable, secure, and fair lending frameworks, it also necessitates cross-sector collaboration between fintechs, banks, data providers, and regulators. By merging these varied data sets, lenders can effectively improve the precision and comprehensiveness of credit scoring models, supporting quicker, more unbiased, and data-led lending decisions. This strengthens under-banked MSMEs' ability to secure working capital, establish financial credibility, and transition over time into the formal financial system. The silver lining is that the ecosystem is on the right path. With upcoming technologies such as satellite intelligence coming in and being more open to integration, the sector does have a serious chance to redefine credit inclusion on a scale. Through innovation and partnerships, we can derive the full potential of India's MSMEs fueling job growth, entrepreneurship, and inclusive economic growth for the long term.


Time of India
05-07-2025
- Business
- Time of India
Lending with empathy: Automation to Augmented Intelligence
It's 2.14 a.m. A loan application has just pinged the system at the bank. A home décor business owner in Jaipur is seeking a working capital loan. Her credit score sits at 680 – dragged down by delayed payments on a personal credit card 36 months ago and a limited history of formal borrowing. The old lending playbook might have flagged this as a red flag. But this time, the system doesn't just look at the pre- defined rules. It looks at her financial behaviour. With her consent, data flows in digitally via the Account Aggregator framework. Within 2 minutes, Artificial Intelligence (AI) parses her GST data, sees consistent filings since she started the business and spots steady exports. It identifies seasonal spikes in her banking transactions and cross-maps the invoices with the payments. It notices she's stocking up ahead for a festival and recognizes her as a regular vendor for a well-reputed lifestyle brand in the U.S. Playing by the rules of the old world, her file would have landed on an underwriter's desk, waiting for a decision: Should we give her a loan? Instead, the new playbook empathizes. An AI sales agent nudges a personalized smart product fit offer. An underwriter agent kicks in, reviewing the risk markers. An operations agent assures regulatory compliance, data validation and workflow orchestration. A GenAI assistant turns all of this into a clean, simple decision rationale, not just for credit officers but also for compliance, operations and sales teams. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Spots on face... Totally gone with Japan's Whitening Gel YUKINOUE雪之上 Learn More Undo The shift from automation to embedding intelligence to now, driving agentic autonomy is evident. With data at its core, the era of decision-capable AI is here. Too much data: The age of analysis paralysis Live Events The last decade saw financial institutions digitise processes, interfaces, and data capture. For example, one large public sector bank in India adopted a digital lending platform and was able to launch 15 products across retail, corporate, MSME, and agriculture. In just four years, they disbursed over ₹35,000 crores, processed more than 10 million digital transactions, and achieved 3x growth in their digital loan book. That was automation – the first phase of digitization. Necessary, but in today's context not enough. According to a BCG Report, productivity in mature markets has plateaued at just 1% CAGR – largely because digitization only automates the 'happy paths'. It's great for straight through journeys but when complexity kicks in – which is often – the system fails to deliver. As digital channels gained popularity financial institutions got access to a wealth of digitally sourced data. However, the challenge was in harnessing its full potential to drive growth effectively. Mukesh Ambani famously described data as 'the new oil' – but like oil, it's only valuable when refined. Traditional digitization ensured speed and efficiency, but it lacked one crucial element: insights. That's where AI flipped the script shifting the focus from automation to intelligence. The rise of behavioural intelligence A loan application isn't the end – it's the start of a relationship. Every transaction, pattern or moment of friction is a signal. The pressing question is: how do we decode these signals? That's where behavioural scoring steps in, especially when the borrower is new-to-credit or when their financial footprint doesn't fit neatly into legacy models. This is the reality for millions of individuals and MSMEs across emerging markets. By analyzing various factors like cashflow patterns, liquidity, collections efficiency, customer concentration, loan behaviour, governance quality, anomalous behaviour, etc., for individuals as well as for MSMEs - financial institutions are building richer, more dynamic borrower profiles. It's a data to DNA approach – every insight distilled in one powerful score that helps lenders drive growth across the customer lifecycle - acquisition, credit-decisioning, monitoring, portfolio analytics and cross-sell/up- sell. Leading Indian banks and NBFCs are adopting behavioural scores as part of their detailed customer assessment. One of the top private banks was able to build a ₹15,000 crore MSME loan book, propelling a substantial 40% growth within a year with an enhanced 'Go-No-Go' in under 2 minutes, all while maintaining a Gross Non-Performing Asset (GNPA) of less than 1%. A large NBFC has assessed 50,000+ applications in five months using a behavioural scoring approach and disbursed loans of upto ₹50,00,000 based on banking transactions alone. Intelligent signals for the MSME ecosystem The MSME sector is complex. Cashflow fluctuates due to seasonality or long, uncertain credit periods, and it is particularly vulnerable to macroeconomic shocks. A commodity price surge in China or a tariff shift in the US can ripple through supply chains and destabilize small enterprises overnight. That's why better signals are critical for everyone in the ecosystem: lenders, policymakers, and the MSMEs themselves. AI layered on multiple consent-led digitally sourced data points is a game changer. It distils deep insights into a single, adaptive behavioural score - one that evolves with the business. For MSMEs, it serves as a compass to reflect, and course correct. For lenders, it provides unbiased insights into the customers' business performance, credit behaviour and overall persona. Additionally, it provides entity- level, portfolio-level and macro-level insights highlighting potential risks and opportunities. For sectors facing challenges due to market dynamics, these insights help policymakers recalibrate schemes and deliver support when it's needed the most. From scoring to storytelling One score tells many tales, as it holds different meanings for different stakeholders, each viewing it through their own lens. GenAI translates complex insights into contextual and actionable conversations for every stakeholder. Trained on hundreds of thousands of lending interactions, portfolio trends, and sectoral signals, AI including GenAI can answer questions for all the stakeholders. For a lender the question might be: 'Which segment in my portfolio poses the highest risk under the current macroeconomic conditions?'. An MSME might ask: 'How can I boost my business performance through supply-chain optimization or an effective pricing strategy? And which government schemes am I eligible for?' A policymaker might ask: 'Which scheme or sectoral intervention will deliver the most on ground impact?' These valuable AI-driven insights that are accessible via systems, platforms, chatbots or voice assistants help underwriters, borrowers, and policymakers make decisions with confidence. A new kind of teamwork: Enter AI Agents Agentic AI is setting a new standard by introducing autonomous agents into the mix. It is redefining lending by making independent decisions, swiftly adapting to changing environments and acting purposefully to meet specific goals. Think of them as your digital coworkers. Crucially, this isn't about removing humans from the lending equation, it's about empowering them with intelligence. At every stage of the lending lifecycle, from sales to underwriting to operations – AI agents are stepping in. Whether it is for identifying smart product recommendations, generating credit decisions backed by behavioural scores or eliminating process bottlenecks, these agents unlock speed, scale and efficiency with precision. Lenders continue to maintain a 'human in the loop' approach. By starting in co-pilot mode and graduating to autopilot in low-risk cases, they can scale without compromising governance. The road ahead: From Artificial to Augmented Intelligence Ironically, AI powered decisioning isn't here to replace humans, it's here to restore the human touch. We're returning to a time when our bank truly knew us. Earlier, they knew us by our faces and our stories – they still know us through our stories but told by data. As we transition from automation to augmented intelligence, lenders are empowered to say yes more often to the right customers, at the right time and for the right reasons. 2.20 a.m. Application approved. Decisioned not by automation but by augmented intelligence. The writer is Founder & Managing Director at Jocata.


Economic Times
05-07-2025
- Business
- Economic Times
Lending with empathy: Automation to Augmented Intelligence
iStock AI for MSMEs serves as a compass to reflect, and course correct. For lenders, it provides unbiased insights into the customers' business performance, credit behaviour and overall persona. It's 2.14 a.m. A loan application has just pinged the system at the bank. A home décor business owner in Jaipur is seeking a working capital loan. Her credit score sits at 680 – dragged down by delayed payments on a personal credit card 36 months ago and a limited history of formal borrowing. The old lending playbook might have flagged this as a red flag. But this time, the system doesn't just look at the pre- defined rules. It looks at her financial behaviour. With her consent, data flows in digitally via the Account Aggregator framework. Within 2 minutes, Artificial Intelligence (AI) parses her GST data, sees consistent filings since she started the business and spots steady exports. It identifies seasonal spikes in her banking transactions and cross-maps the invoices with the payments. It notices she's stocking up ahead for a festival and recognizes her as a regular vendor for a well-reputed lifestyle brand in the U.S. Playing by the rules of the old world, her file would have landed on an underwriter's desk, waiting for a decision: Should we give her a loan? Instead, the new playbook empathizes. An AI sales agent nudges a personalized smart product fit offer. An underwriter agent kicks in, reviewing the risk markers. An operations agent assures regulatory compliance, data validation and workflow orchestration. A GenAI assistant turns all of this into a clean, simple decision rationale, not just for credit officers but also for compliance, operations and sales teams. The shift from automation to embedding intelligence to now, driving agentic autonomy is evident. With data at its core, the era of decision-capable AI is here. Too much data: The age of analysis paralysis The last decade saw financial institutions digitise processes, interfaces, and data capture. For example, one large public sector bank in India adopted a digital lending platform and was able to launch 15 products across retail, corporate, MSME, and agriculture. In just four years, they disbursed over ₹35,000 crores, processed more than 10 million digital transactions, and achieved 3x growth in their digital loan book. That was automation – the first phase of digitization. Necessary, but in today's context not enough. According to a BCG Report, productivity in mature markets has plateaued at just 1% CAGR – largely because digitization only automates the 'happy paths'. It's great for straight through journeys but when complexity kicks in – which is often – the system fails to deliver. As digital channels gained popularity financial institutions got access to a wealth of digitally sourced data. However, the challenge was in harnessing its full potential to drive growth effectively. Mukesh Ambani famously described data as 'the new oil' – but like oil, it's only valuable when refined. Traditional digitization ensured speed and efficiency, but it lacked one crucial element: insights. That's where AI flipped the script shifting the focus from automation to intelligence. The rise of behavioural intelligence A loan application isn't the end – it's the start of a relationship. Every transaction, pattern or moment of friction is a signal. The pressing question is: how do we decode these signals? That's where behavioural scoring steps in, especially when the borrower is new-to-credit or when their financial footprint doesn't fit neatly into legacy models. This is the reality for millions of individuals and MSMEs across emerging analyzing various factors like cashflow patterns, liquidity, collections efficiency, customer concentration, loan behaviour, governance quality, anomalous behaviour, etc., for individuals as well as for MSMEs - financial institutions are building richer, more dynamic borrower profiles. It's a data to DNA approach – every insight distilled in one powerful score that helps lenders drive growth across the customer lifecycle - acquisition, credit-decisioning, monitoring, portfolio analytics and cross-sell/up- Indian banks and NBFCs are adopting behavioural scores as part of their detailed customer assessment. One of the top private banks was able to build a ₹15,000 crore MSME loan book, propelling a substantial 40% growth within a year with an enhanced 'Go-No-Go' in under 2 minutes, all while maintaining a Gross Non-Performing Asset (GNPA) of less than 1%. A large NBFC has assessed 50,000+ applications in five months using a behavioural scoring approach and disbursed loans of upto ₹50,00,000 based on banking transactions alone. Intelligent signals for the MSME ecosystem The MSME sector is complex. Cashflow fluctuates due to seasonality or long, uncertain credit periods, and it is particularly vulnerable to macroeconomic shocks. A commodity price surge in China or a tariff shift in the US can ripple through supply chains and destabilize small enterprises overnight. That's why better signals are critical for everyone in the ecosystem: lenders, policymakers, and the MSMEs layered on multiple consent-led digitally sourced data points is a game changer. It distils deep insights into a single, adaptive behavioural score - one that evolves with the business. For MSMEs, it serves as a compass to reflect, and course correct. For lenders, it provides unbiased insights into the customers' business performance, credit behaviour and overall persona. Additionally, it provides entity- level, portfolio-level and macro-level insights highlighting potential risks and opportunities. For sectors facing challenges due to market dynamics, these insights help policymakers recalibrate schemes and deliver support when it's needed the most. From scoring to storytelling One score tells many tales, as it holds different meanings for different stakeholders, each viewing it through their own lens. GenAI translates complex insights into contextual and actionable conversations for every on hundreds of thousands of lending interactions, portfolio trends, and sectoral signals, AI including GenAI can answer questions for all the stakeholders. For a lender the question might be: 'Which segment in my portfolio poses the highest risk under the current macroeconomic conditions?'. An MSME might ask: 'How can I boost my business performance through supply-chain optimization or an effective pricing strategy? And which government schemes am I eligible for?' A policymaker might ask: 'Which scheme or sectoral intervention will deliver the most on ground impact?'These valuable AI-driven insights that are accessible via systems, platforms, chatbots or voice assistants help underwriters, borrowers, and policymakers make decisions with confidence. A new kind of teamwork: Enter AI Agents Agentic AI is setting a new standard by introducing autonomous agents into the mix. It is redefining lending by making independent decisions, swiftly adapting to changing environments and acting purposefully to meet specific goals. Think of them as your digital coworkers. Crucially, this isn't about removing humans from the lending equation, it's about empowering them with intelligence. At every stage of the lending lifecycle, from sales to underwriting to operations – AI agents are stepping in. Whether it is for identifying smart product recommendations, generating credit decisions backed by behavioural scores or eliminating process bottlenecks, these agents unlock speed, scale and efficiency with continue to maintain a 'human in the loop' approach. By starting in co-pilot mode and graduating to autopilot in low-risk cases, they can scale without compromising governance. The road ahead: From Artificial to Augmented Intelligence Ironically, AI powered decisioning isn't here to replace humans, it's here to restore the human touch. We're returning to a time when our bank truly knew us. Earlier, they knew us by our faces and our stories – they still know us through our stories but told by data. As we transition from automation to augmented intelligence, lenders are empowered to say yes more often to the right customers, at the right time and for the right reasons. 2.20 a.m. Application approved. Decisioned not by automation but by augmented intelligence. The writer is Founder & Managing Director at Jocata.